Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4, 1767-1782 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 5 February 2025; Revised: 7 April 2025; Accepted: 10 April 2025; Published: 19 April 2025 * Correspondence: jorge.esponda@unicach.mx Patterns of representation and discrimination in dating applications: Analysis and perspectives Jorge Alberto Esponda Pérez1*, Rubén Cervantes Hernández2, Julia María Marroquín Figueroa3, Juan Manuel Tapia de Aquino4, Tania Lucia Vila Cisneros5 1,5University of Sciences and Arts of Chiapas, Mexico; jorge.esponda@unicach.mx (J.A.E.P.) tania.vila@unicach.mx (T.L.V.C) 2Autonomous University of Zacatecas, Mexico; rubencervantesh1@gmail.com (R.C.H.). 3,4Autonomous University of Chiapas, Mexico; julia.marroquin@unach.mx (J.M.M.F.) juan.tapia@unach.mx (J.M.T.A.) Abstract: Dating applications have transformed the dynamics of social interaction, influencing users' self-representation and the construction of identities in digital environments. Platforms such as Tinder, Bumble, and Grindr not only facilitate encounters but also operate through algorithms that determine profile visibility and prioritization. However, these systems are not neutral, as they can reinforce stereotypes and biases, limiting the representation of certain groups and affecting the perception of diversity within these spaces. This study analyzes how algorithmic models on these platforms influence patterns of representation and discrimination, exploring their implications for equity and diversity in digital interactions. Through a critical literature review, the article examines two main axes: (1) the representation of diversity on these platforms and (2) discrimination and exclusion within their operation. The study concludes that the automation of these processes can amplify unconscious biases and restrict diversity in digital socialization, highlighting the need for strategies to mitigate these effects and promote greater equity in digital representation. Keywords: Algorithmic biases, Digital discrimination, Digital interactions, Identity and technology, Online dating Introducción. 1. Introduction Dating applications have transformed the dynamics of social interaction and the construction of identities in the digital age, becoming spaces where users negotiate their self-representation and establish emotional connections. Platforms such as Tinder, Bumble, and Grindr have not only facilitated the search for a partner but have also established algorithmic structures that determine profile visibility and prioritization. However, these systems are not neutral, as they can reinforce stereotypes and limit the representation of certain groups, shaping users' perceptions of themselves and others [1]. While the growth of these platforms has expanded socialization opportunities, their algorithms can perpetuate dynamics of discrimination and social exclusion. Nader [2] points out that recommendation systems in applications like Tinder or Hinge not only optimize matches based on user preferences but also reinforce racial biases and promote the homogenization of profiles by classifying them according to past behavioral patterns. In this sense, the automation of these processes is not impartial, as it can amplify unconscious prejudices, restrict diversity in digital socialization spaces, and limit representation opportunities for certain groups. Therefore, it is essential to analyze how these systems influence users' self-identification and their perception of diversity within these platforms. Analyzing the impact of algorithms on the representation of diversity within these platforms is essential to understanding how they shape digital interaction dynamics. While previous studies have addressed the influence of artificial intelligence on match selection, it is still necessary to delve deeper into how these processes affect users' self-identification and perception in these virtual environments. https://orcid.org/0000-0002-6821-5361 https://orcid.org/0000-0002-9390-9461 https://orcid.org/0000-0002-2263-3365 https://orcid.org/0009-0005-3290-8878 https://orcid.org/0009-0001-9030-2082 1768 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate This research aims to bridge that gap by providing a critical approach to the challenges marginalized groups face in these spaces and exploring possible strategies to enhance equity in digital representation. Despite the numerous studies that have analyzed the impact of algorithms on partner selection, gaps remain in understanding how these systems influence users' self-identification and the perception of diversity within these platforms. In this regard, it is essential to question to what extent algorithms contribute to the homogenization of profiles and what their implications are for the representation of diverse identities. Addressing these questions will allow for an assessment of the impact of artificial intelligence on the shaping of social dynamics within dating applications and a deeper understanding of the challenges this poses for digital inclusion. However, this dynamic presents a central issue: the reproduction of structural biases and the exclusion of those who do not conform to the standards of beauty and desirability imposed by these systems. In this context, the present study analyzes how algorithmic models in dating platforms influence patterns of representation and discrimination, as well as their impact on diversity and equity in digital interactions. The advancement of digitalization has radically transformed the ways in which social interactions and interpersonal relationships are built, giving rise to dynamics mediated by technological platforms. In this context, dating applications have taken on a central role in connecting individuals, not only facilitating encounters but also influencing the shaping of identities and the perception of diversity within the digital ecosystem. These platforms operate through recommendation systems based on personal data and preference patterns, which can introduce biases in the selection and classification of profiles. In this way, algorithms not only structure interactions but also reinforce prevailing sociocultural norms, favoring certain profiles while marginalizing others [3]. In this regard, the growing influence of algorithms in digital socialization has raised questions about their impact on equity and diversity within these platforms. Agudo and Matute [4] highlight that recommendation systems can persuade users to choose certain options without them being fully aware of this influence. Through four experiments, their study demonstrates that cognitive biases, such as familiarity and repeated exposure, can be exploited to modify user preferences, affecting the diversity of interactions and reinforcing stereotypes of attractiveness and desirability. This phenomenon generates what Onitiu [5] defines as "algorithmic bubbles," where the prioritization of certain traits over others limits diversity and perpetuates biased representations. The use of algorithms in dating applications not only influences profile visibility but also gives rise to strategic optimization practices by users. In the case of Blued, a dating app for gay men in China, users have developed strategies to manipulate the recommendation system and maximize their interaction opportunities [6]. These dynamics, known as data gaming, involve the deliberate modification of profile information, usage frequency, and interactions to improve positioning within the algorithm. This phenomenon reflects how algorithms are not merely neutral tools but actively shape users' self-representation and reinforce desirability hierarchies. Analyzing these mechanisms is essential to better understand how algorithmic models can contribute to the reproduction of exclusion within these platforms. The central issue lies in the fact that these processes challenge the supposed neutrality of algorithms and reveal how automated decisions can perpetuate dynamics of exclusion and inequality. This study analyzes patterns of representation in digital dating platforms, exploring the impact of algorithmic decisions on the equity and diversity of interactions, as well as potential mechanisms to mitigate discriminatory effects in these environments. In this context, analyzing the impact of algorithmic models on the representation of diversity is essential to understanding the challenges and biases that persist in these virtual spaces. Zhang, et al. [7] highlight that the way users present themselves and are perceived on these platforms is mediated by algorithmic patterns that can restrict equity in digital representation. Assessing how these applications shape the perception of diversity will help understand their implications for the 1769 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate construction of individual and collective identities and provide tools to mitigate their discriminatory effects. Over the past two decades, dating applications have profoundly transformed the dynamics of social interaction and identity construction in digital environments. Platforms such as Tinder, Bumble, and Grindr have grown exponentially, becoming spaces where individuals not only seek romantic or sexual relationships but also construct and negotiate their identities. However, these digital environments are not neutral—the algorithms that filter and recommend matches can reinforce stereotypes, gender biases, racialization, and other forms of exclusion. Through recommendation systems, these algorithms organize access to potential matches, determining who is visible and who is not within these virtual spaces. However, far from being impartial, these processes can reproduce pre-existing sociocultural and structural biases, reinforcing desirability norms that exclude or marginalize certain groups [8]. In this sense, dating applications not only mediate romantic interactions but also shape new dynamics of representation and identity within contemporary digital culture [9, 10]. This article analyzes patterns of representation and discrimination in dating applications, focusing on the influence of algorithms on profile visibility and the construction of digital identity. To achieve this, two main thematic axes will be explored: (1) the representation of diversity on these platforms and (2) discrimination and exclusion within their operation. Through a review of the existing literature, this study aims to provide a critical perspective on the challenges and opportunities these technologies present in terms of equity and inclusion. 2. Methodology This study is based on a qualitative approach through a systematic literature review on representation and discrimination in digital dating applications. Previous studies, scientific articles, and academic reports analyzing the influence of algorithms on profile visibility, the reproduction of biases, and users' self-representation strategies on platforms such as Tinder, Bumble, Grindr, and Blued were collected. The table below presents a summary of the main academic journals included in the review, along with their respective areas of specialization. These publications cover fields such as digital communication, sociology, cultural studies, business and marketing, public health, and discourse analysis, highlighting the interdisciplinary nature of the topic. Table 1. Areas of specialization of the journals. Journal Areas of specialization Plos One Multidisciplinary Sciences Journal of Business Research Business and Marketing Journal of Computer-Mediated Communication Digital Communication and Social Networks International Journal of Cultural Policy Cultural Policy and Identity Studies New Media & Society Digital Media and Society International Journal of Environmental Research and Public Health Public Health and Well-being Cultural Sociology Sociology and Cultural Studies Discourse & Society Discourse Analysis and Gender Studies Social Media+ Society Digital Media and Communication Journal of Family Issues Family Studies and Social Dynamics 2.1. Inclusion Criteria 1. Studies published in Scopus-indexed, peer-reviewed journals between 2020 and 2025. 2. Research addressing the influence of algorithms on profile visibility in dating applications. 3. Studies on algorithmic biases and their impact on digital discrimination within these platforms. 4. Articles analyzing the construction of digital identity in online dating environments. 5. Research focused on different population groups and their representation in these applications. 1770 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate 2.2. Exclusion Criteria 1. Studies without full-text access or with insufficient data for analysis. 2. Research that does not specifically address digital dating platforms or focuses on social networks without matchmaking functions. 3. Studies based solely on personal opinions or lacking a clear methodology. 4. Research that does not consider the impact of technology on discrimination or digital representation. 5. Publications in Spanish that are not indexed in Scopus. 2.3. The Analysis Was Structured Around Two Main Thematic Axes 1. Representation of diversity in dating applications, evaluating how algorithms shape users’ visibility and self-representation. 2. Algorithmic exclusion and discrimination, analyzing how recommendation systems can reinforce sociocultural biases and limit equity in digital interaction. This approach allowed for an examination of the implications of algorithmic models on equity and diversity within dating platforms and a discussion of strategies to mitigate discriminatory effects in these digital environments. The table below describes the essential aspects to consider, including the author and year of publication, the study title, its objective, the methodology used, the dating platforms analyzed, key variables, main findings, and conclusions obtained. Table 2. Main items for organizing information. Element Description Author(s) and year Study reference, including the year of publication. Study title Full title of the analyzed article or study. Study objective Purpose of the study and research questions addressed. Methodology Method used for data collection and analysis. Platform analyzed Specific dating applications examined in the study (Tinder, Bumble, Grindr, etc.). Key variables Main factors considered in the study, such as algorithmic discrimination, self- representation, racial biases, among others. PriMain findings Most relevant results regarding the influence of algorithms on representation and discrimination. Conclusions and recommendations General conclusions of the study and recommendations for future research or improvements in digital platforms. 3. Results As part of this systematic review, various studies exploring representation and discrimination in digital dating applications have been identified and analyzed. The table below summarizes the main findings. 1771 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate Table 3. Summary of included studies Author(s) and year Study objective Methodology Main conclusion Zhao, et al. [11] Explore how gay men in China construct their identity on Zhihu. Content analysis and semi- structured interviews. Gay men on Zhihu use detailed self- representation strategies. Regan [12] Analyze how dating applications shape 'sexual fields' and influence diversity. Comparative study of dating platforms. Dating apps establish desirability norms based on race, gender, and orientation. Wu and Trottier [13] Study the identities and dating practices of gay men in China. Interviews with 52 participants. Platforms structure hierarchies of desire based on class and geolocation. Christensen [14] Investigate 'sexual scripts' on Tinder and their impact on women's experiences. Interviews with 25 young female Tinder users. Women of color face additional barriers and exclusion on Tinder. Stacey and Forbes [15] Examine how dating apps reinforce racial hierarchies in desire. Profile analysis on dating platforms. Platforms reproduce racial hierarchies that reinforce inequalities. De Ridder [16] Explore the 'datafication of intimacy' in dating apps and its impact on identity. Interviews with young adults in London. Algorithmic rationalization redefines the management of desire and belonging. Pidoux [1] Analyze how digital dating architectures reinforce heteronormativity. Analysis of features and filters in dating platforms. Apps limit diversity by reinforcing traditional sexual norms. Bandinelli and Gandini [17] Study the commodification of intimacy and self- representation in digital dating. Qualitative study with young adults in London Strategic self- representation in digital dating generates uncertainty. Van Kampen, et al. [18] Explore the tension between authenticity and desirability in young people's digital identity. Qualitative interviews on self-representation. Women balance self- promotion with safety preservation and authenticity. García-Gómez [19] Examine the discursive representation of masculinity and femininity on Tinder and Grindr. Análisis de 200 Analysis of 200 heterosexual male profiles and 200 queer male profiles. Hegemonic masculinity predominates in digital self-representation 3.1. Construction of Identities and Representation of Diversity in Dating Applications Zhao, et al. [11] analyze how gay men in China construct their identity on Zhihu, a platform not originally designed for dating. Through content analysis and interviews, they identify that despite stigma and censorship, users optimize their self-representation to attract potential partners. The absence of geolocation reduces the fear of exposure, fostering greater openness. Additionally, the algorithm largely excludes heterosexual users, creating a predominantly queer space where the quality and quantity of personal information facilitate matches and challenge heterosexual normativity. Dating applications have emerged as spaces where individual and collective identities are negotiated and reconfigured, allowing for the expression of diversity in digital contexts. Through their algorithms and interaction dynamics, these platforms not only facilitate encounters but also reinforce, challenge, or transform stereotypes related to gender, sexual orientation, and ethnicity. In this sense, the representation of diversity in these digital environments is a process influenced both by users’ self- perception and by the technological structures that mediate their interactions, generating new forms of subjectivity and belonging in the digital age Wu and Trottier [20]. Regan [12] examines how dating applications shape "sexual fields" that influence identity and diversity in virtual environments. Through the study of Tinder, Grindr, Bumble, and Hinge, the research analyzes how profiles, filters, and platform features determine erotic and romantic capital. Each 1772 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate platform establishes desirability norms, reinforcing hierarchies of race, gender, and sexual orientation. While Grindr allows for greater LGBTQ+ flexibility, Bumble and Hinge impose binary restrictions. Search filters facilitate exclusion, reproducing inequalities and discrimination, highlighting that these applications do not merely mediate interactions but also reinforce preexisting social structures. Wu and Trottier [13] analyze how metropolitan gay men in China construct their identities and dating practices within a diverse landscape of dating applications, drawing on sexual field theory. Through interviews with 52 participants, they identify that apps such as Blued, Grindr, Aloha, and Tinder not only mediate interactions but also structure hierarchies of desire based on social class, geolocation, and technological access. While Blued, the most popular app, attracts a more diverse user base—leading to perceptions of lower quality in terms of erotic capital—apps like Aloha and Tinder are preferred by middle-class metropolitan men due to their design, which fosters more selective connections and restricts access through sociotechnological factors. The authors conclude that these platforms function as spaces of differentiation, where users seek to maximize their sexual capital within structures of desire that reflect existing social stratification. Christensen [14] analyzes how dating applications, particularly Tinder, shape young women's sexual scripts through their digital features. The research, based on 25 interviews, reveals the existence of a "hybrid script of dating and hookups" that reintroduces elements of traditional dating within a context where the expectation of casual sex remains present. However, this script is not experienced in the same way by all users, as women of color face additional barriers due to racial and sexist dynamics on the platform, often leading them to abandon the app. Additionally, Tinder’s design, with its swipe mechanics and algorithms, facilitates quick and informal interactions, reinforcing heteronormative norms and reproducing hierarchies of gender and desire. Christensen concludes that dating applications not only mediate personal interactions but also structure how sexual identities are represented and experienced in digital environments. Dating applications have transformed the dynamics of social interaction, facilitating the construction of identities through digital self-representation. However, this environment also amplifies processes of racialization and fetishization, shaping patterns of exclusion and inclusion based on stereotypes. Research shows that profiles on these platforms not only reflect personal preferences but also reproduce racial hierarchies that reinforce inequality. Through the explicit manifestation of racial preferences in profile descriptions and search filters, narratives are consolidated that limit diversity, promoting a marketplace of desire where certain groups are systematically marginalized Stacey and Forbes [15]. De Ridder [16] analyzes how the datafication of intimacy in mobile dating applications transforms identity construction and the representation of diversity in digital environments. Through interviews with young adults in London, the study reveals that reliance on these platforms is not only due to their functionality but also to their integration into daily life as tools for managing expectations, desire, and belonging. The rationalization and commercialization of love in these applications shape a "mathematical mode of dating" that turns intimacy into a measurable, predictable, and efficient process. However, users do not passively adopt these algorithmic structures but strategically navigate their possibilities and limitations. The research concludes that the datafication of intimacy does not eliminate individual agency but rather redefines how people negotiate their identity and experience emotional closeness in the digital age. Pidoux [1] introduced the concept of algorithmic heteronormativity to describe how the digital architectures of dating applications reinforce normative sexual ideologies. Through an analysis of the features and designs of platforms such as Tinder, Bumble, Hinge, and Grindr, the authors identify four predominant sexual ideologies: gendered desire, hetero- and homonormativity, mononormativity, and shame. These ideologies are reflected in the requirement to choose a gender identity, compatibility filters that prioritize monogamous models, and content restrictions that limit erotic self-expression. The study argues that these platforms not only mediate interactions but also shape and constrain the 1773 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate possibilities for representation and recognition of diverse identities, establishing a digital landscape where sexual diversity is regulated under traditional logics. Bandinelli and Gandini [17] analyzes how dating applications have commodified intimacy by introducing a model based on uncertainty and strategic self-representation. Through a qualitative study with young adults in London, the author argues that these platforms not only offer an algorithmic rationalization of romance but also generate a logic of self-entrepreneurship in which users present themselves as brands in a digital marketplace of desire. This dynamic compels participants to manage their identity through self-promotion strategies, constantly evaluating their attractiveness and optimizing their "preconfigured social capital." However, rather than reducing uncertainty in interpersonal relationships, dating applications reinforce the impossibility of making choices based on clear and stable criteria, reproducing a system where intimacy becomes a transaction based on ambiguous signals and a calculated management of risk. Van Kampen, et al. [18] explore how young people conceptualize and represent their identity on dating applications, highlighting the tension between authenticity and the need to project a desirable image. Through qualitative interviews, the study identifies three main axes: the integration of (in)security into digital identity, the influence of social norms and external validation in self- construction, and the commercialization of the "self" in the digital love market. The research highlights how the perception of risk leads women to restrict their self-representation, while the normalization of dating apps coexists with a persistent stigma that forces them to justify their use. Additionally, the article reveals that self-presentation on these platforms requires significant cognitive and emotional effort, as women balance self-promotion with the preservation of their security and authenticity values. Dating applications have emerged as digital spaces where users not only seek romantic or sexual interactions but also shape and negotiate their identity based on various sociocultural categories. In these environments, the representation of diversity is influenced by algorithms, filters, and self- expression practices that can either reinforce or challenge preexisting norms related to gender, sexual orientation, and ethnic belonging. Through profile customization and the selection of potential matches, these applications facilitate the construction of subjectivities that may align with inclusive discourses or, conversely, replicate dynamics of exclusion and stereotyping. This dual function of dating platforms highlights their role both as mechanisms for the visibility of diverse identities and as spaces where social hierarchies and implicit biases persist Zimmermann, et al. [21]. García-Gómez [19] examines how the discursive representation of masculinity and femininity on Tinder and Grindr reproduces gender hierarchies and reinforces the devaluation of femininity in digital contexts. Through the analysis of 200 heterosexual male profiles on Tinder and 200 queer male profiles on Grindr, the study reveals that self-representation on these platforms is shaped by hegemonic masculinity norms, where expressions of femininity are devalued and sanctioned, particularly within the LGBTQ+ community. On Tinder, men emphasize attributes such as power, authority, and sexual activity, while some adopt more sensitive and romantic self-presentation strategies to attract partners, though without challenging the patriarchal order. On Grindr, the preference for masculinity translates into the outright exclusion of users perceived as effeminate, highlighting the persistence of femophobia. Ang, et al. [22] explore how sexual racism structures identity representation on the Grindr app in Singapore, where users are classified within a hierarchy of desirability based on racial categories and stereotypes. The research reveals that majority users, primarily Chinese, are perceived as more attractive, while racial minorities, such as Malays and Indians, face exclusion or fetishization. Through interviews, the authors illustrate how minority users respond to this discrimination through strategies such as negotiating a more socially acceptable racial identity, adopting a cosmopolitan identity to minimize their ethnic background, or redefining their position within the sexual field. Additionally, the study highlights the role of Grindr’s interface in reproducing these hierarchies, as users engage in racial verification through profile photos and tags, reinforcing the perception of race as an immutable marker of desire and attractiveness. 1774 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate Degen and Kleeberg-Niepage [23] analyze how mobile dating applications shape users' self- representation through profile images, identifying patterns that align with implicit social norms and a logic of digital validation. Through a serial analysis of 542 profile images on Tinder, the authors identify eight types of self-presentation, ranging from spontaneous snapshots to professionally produced photographs. The research highlights that, although these platforms appear to offer a diverse range of options, most users follow standardized visual patterns that facilitate categorization and quick recognition within the fast-paced dynamics of swiping. Additionally, the authors argue that self- representation on these platforms not only reflects individual desires but also responds to collective expectations regarding attractiveness, status, and authenticity in the digital sphere. Digital platforms have reshaped the construction of ethno-racial identities through self- representation in visual environments, where users strategically select elements that either emphasize or downplay their identity traits based on prevailing social perceptions. Through a large-scale content analysis on Instagram, the study reveals that the digitalization of identity is mediated by algorithmic dynamics and sociocultural norms that influence the visibility and recognition of diversity. While these platforms provide spaces for expression, they also perpetuate inequalities by reinforcing standardized patterns of attractiveness and racial representation, highlighting how technology not only reflects but also actively shapes identity constructions in the digital age Bij de Vaate, et al. [24]. Gabarnet, et al. [25] study how the construction of the virtual self in digital environments impacts personal identity and its representation across various online platforms. Their review highlights that individuals can shape their virtual identity in idealized, authentic, or even divergent ways from their offline self, depending on the context and their levels of self-esteem or self-concept clarity. In the case of dating applications, this phenomenon is particularly relevant, as users strategically select which traits to emphasize or downplay based on social perception and desirability within these spaces. While these platforms allow for the exploration of alternative identities, they also perpetuate stereotypes related to gender, race, and physical attractiveness, limiting the true representation of diversity. Thus, dating applications not only facilitate romantic interactions but also function as spaces where identity is constantly negotiated and shaped. Roshchupkina, et al. [26] investigate how women perceive male self-representation on Tinder, highlighting the visual and contextual factors that influence the acceptance or rejection of a profile. Through a mixed-method study combining qualitative interviews and experiments with brain activity measurement, the authors conclude that profile evaluation is based on key visual cues such as facial clarity, facial expression, and image authenticity. The study identifies widespread rejection patterns, including overly edited photos, rigid poses, or displays of economic status, which can be interpreted as inauthentic self-representation strategies. This research connects to the construction of identities in dating applications by demonstrating how women develop profile interpretation strategies based on visual cues and cultural norms, ultimately influencing the representation of diversity within these digital spaces. When analyzing how dating applications have transformed self-perception and identity construction in digital environments, Labor [27] notes that users of apps such as Tinder and Grindr develop self- representation strategies that fluctuate between authenticity and idealization, aiming to maximize their attractiveness to potential partners. In this process, individuals negotiate their identity through the selection and curation of images, descriptions, and personal narratives, balancing sincerity with elements of self-editing.This phenomenon not only highlights the malleability of identity in digital environments but also reveals how dating applications can serve as spaces for social validation and identity experimentation. Additionally, the study shows that the representation of diversity within these platforms is conditioned by sociocultural norms, as exemplified by LGBTQ+ users who adapt their profiles based on the application and its target audience. This reflects an intersection between digital identity, social acceptance, and the expression of diversity in mobile contexts. Castro and Barrada [10] state that digital media have redefined identity construction and the representation of diversity in the contexts of gender and sexuality. From a multidisciplinary perspective, 1775 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate the authors highlight that digital platforms have expanded the possibilities for identity expression while simultaneously reinforcing normative discourses that shape how users self-represent.In the case of dating applications, this phenomenon is particularly relevant, as algorithms and interaction rules influence the visibility and recognition of diverse gender identities and sexual orientations. While these spaces can serve as tools for empowerment and affirmation of diversity, they also perpetuate preexisting inequalities by privileging certain bodies, practices, and narratives within the digital sphere. Thus, identity representation on these platforms becomes a field of visibility, where inclusion and exclusion are mediated by technological and sociocultural dynamics. Halversen, et al. [28] analyze how self-disclosure and rejection in dating applications impact digital identity and diversity. Their study on female Bumble users shows that self-disclosure is key to interaction, often reaching deeper levels than in face-to-face encounters. However, its reciprocity depends on the duration of the conversation and the perception of the other person. Although Bumble aims to provide women with greater autonomy, it still reproduces hegemonic patterns of validation and desirability. Thus, these platforms not only facilitate interactions but also reinforce or challenge preexisting social norms. Bury and Easton [29] analyze how the representation of masculinity and identity on digital platforms is mediated by dynamics of homosociality and heteronormative norms that shape user interactions. Through the study of the subreddit r/MassiveCock, the authors identify how digital spaces can both reinforce and challenge traditional constructions of male identity, revealing the coexistence of discourses that normalize the objectification of the male body while simultaneously allowing expressions of desire that destabilize the heterosexual-homosexual dichotomy.In the context of dating applications, these dynamics are replicated as users negotiate their self-representation within normative frameworks that limit diversity while also creating opportunities for experimentation with new forms of identity and expressions of desire. Thus, the study highlights how identity construction in digital environments is not static but rather a dynamic process influenced by power structures, sociocultural expectations, and interactions between users themselves. Wang and Zhou [30] examine how the algorithms of digital platforms such as Douyin and Zhihu shape the visibility and representation of gay identity in China, creating a paradox between inclusion and exclusion. Through the concept of cruel optimism, the authors explain how the apparent LGBTQ+ visibility on these platforms is driven more by profitability than by genuine social acceptance. On Douyin, for example, algorithms favor normative representations of homosexuality—young, athletic men in monogamous relationships—while other identities and gender expressions are marginalized. Meanwhile, on Zhihu, content related to HIV/AIDS is framed within narratives of self-help and personal growth, avoiding discussion of the real challenges faced by gay men living with this condition.This research connects to the construction of identities in dating applications by demonstrating how algorithms not only amplify certain narratives of diversity but also shape users' self- representation within a framework of social and commercial acceptability. Huang, et al. [31] analyze how folk theories—popular beliefs about dating applications—influence identity construction and the representation of diversity within these digital spaces. Their study reveals that users interpret and navigate these platforms through metaphors that reflect their understanding of online dating, highlighting perceptions such as "relationship shopping" or "the randomness of fate." These conceptualizations shape how individuals self-represent, as algorithms—though largely invisible to most users—structure interactions and determine the visibility of certain profiles based on unknown criteria. Additionally, users perceive algorithms as "filters" that select potential partners based on their activity within the platform, a process that can reinforce preexisting biases and limit the diversity of identity representation. Thus, dating applications function not only as spaces for socialization but also as regulators of identity perception and diversity through algorithmic dynamics that shape the construction of desire and compatibility. Akter, et al. [32] highlight that dating applications not only facilitate romantic interactions but also shape identity construction through algorithms and design structures that influence users' self- 1776 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate representation. Their study emphasizes that dating platforms promote the commodification of identity through self-branding strategies and profile optimization, where individuals adjust their descriptions and images to maximize their attractiveness within a digitized marketplace of desire. This phenomenon not only impacts how people present themselves but also affects diversity within these spaces, as algorithms tend to favor certain traits and normative categories of desirability. Thus, the representation of diversity in dating applications is shaped by an algorithmic filtering process that amplifies preexisting social biases and restricts the visibility of non-hegemonic identities. The study by Espín-Noboa, et al. [33] provides a detailed analysis of inequality and disparity in recommendation and ranking algorithms within digital social networks. The findings of the article reveal how these algorithms can amplify, diminish, or replicate the representation of minority groups in rankings. Specifically, the study demonstrates that homophily—the tendency to connect with similar individuals—and network structure directly influence the visibility of these groups within digital platforms. When majority groups exhibit high levels of homophily, minorities are relegated to lower- ranking positions within classification algorithms. Conversely, when majority groups display heterophilic patterns, minority groups can achieve greater visibility and presence in rankings. These results are crucial for understanding how digital dating applications not only reflect but also reinforce dynamics of exclusion and selective visibility within their digital environments. 3.2️. Algorithms, Biases, and Digital Exclusion in Dating Platforms The algorithmic design of dating applications not only influences user interactions but also reinforces digital exclusion through biases in profile recommendations. Nader [34] points out that Tinder has transformed partner searching into an immediate reward system, where algorithms prioritize profiles based on statistical desirability, favoring conventional standards of beauty and social normativity. This gamification turns interaction into a quantifiable validation process, driving profile optimization strategies. However, this logic excludes individuals who do not fit algorithmic criteria, reinforcing inequalities related to gender, race, and sexual orientation. Thus, algorithmic systems not only impact users’ self-esteem but also perpetuate exclusionary dynamics. Online dating platforms, despite presenting themselves as neutral spaces, reproduce and amplify discrimination through algorithms that rank desirability based on race and gender. Banks, et al. [35] highlight that Black women face digital racism and fetishization, often disguised as "personal preferences."Algorithms, influenced by Eurocentric beauty standards, reduce their opportunities for interaction while exposing them to hypersexualization and non-consensual objectification. This bias not only limits their romantic options but also reinforces the historical control over racialized bodies, perpetuating structural inequalities within an ostensibly inclusive digital environment. The algorithms used in dating applications do not operate neutrally; rather, they are designed based on criteria that reflect and reinforce preexisting social biases. As Martin [36] points out, the lack of algorithmic accountability in technological decision-making allows companies to evade responsibility for the discriminatory impacts of their recommendation models. In this sense, systems that filter and prioritize profiles based on past interaction patterns perpetuate dynamics of digital exclusion, particularly against racialized groups and individuals who do not fit dominant standards of beauty and desirability. This exclusion does not occur accidentally but rather as a result of business decisions aimed at maximizing profitability through engagement optimization, even at the cost of reinforcing structural inequalities. Martin describes this phenomenon as a "fog of responsibility," where the developers of these applications distance themselves from the harmful effects of their algorithms, claiming that they merely reflect user preferences when, in reality, they actively shape them. Digital dating platforms have transformed the way intimate relationships are built, but in doing so, they have also reinforced dynamics of digital exclusion and structural biases. As Kugelberg [37] points out, these applications not only facilitate user interactions but also act as gatekeepers of the sphere of desire through filtering mechanisms and algorithmic amplification. The lack of transparency in these 1777 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate processes reinforces discriminatory patterns based on race, gender, and socioeconomic status, limiting certain groups' opportunities to connect with potential partners. Moreover, machine learning in these platforms does not merely record individual preferences but solidifies them, reducing interaction diversity and perpetuating preexisting inequalities. Far from being neutral spaces, dating applications actively shape the marketplace of desire, determining who gains greater visibility and who is relegated in the digital competition for connection and social validation. The search for a partner in digital environments is mediated by sociocultural factors that shape user selection and visibility within dating platforms. As Shen and Qian [38] show, users in Shanghai do not only choose applications based on their purpose—whether for casual relationships or marriage—but also experience homophily effects, where education, socioeconomic status, and hukou influence partner matching. These trends are not merely an expression of personal preferences but are reinforced by recommendation algorithms that amplify preexisting inequalities and limit diversity in user interactions. By segmenting participants based on demographic characteristics and relationship goals, filtering systems consolidate structures of digital exclusion, where certain groups have a lower probability of being matched. In this sense, the online partner search process does not unfold in a neutral space but within an ecosystem designed to perpetuate socially constructed desirability criteria, restricting equity in access to interaction and connection opportunities. Interaction dynamics on dating platforms are not only mediated by individual expectations but also by digital narratives that shape users' perceptions of trust and risk. As Labor [27] explains, sentiment analysis on social media reveals how romantic fraud—exemplified in the case of The Tinder Swindler— relies on self-presentation strategies and algorithmic manipulation that exploit victims' emotional vulnerability. While the implementation of artificial intelligence in these platforms facilitates fraud detection, it also raises questions about the opacity of the algorithms that determine profile visibility and the possibility that certain users may be more prone to scams due to algorithmic segmentation patterns. In this context, digital exclusion is not only reflected in the lack of access to these platforms but also in how algorithms perpetuate biases and unequally distribute the risk of victimization within the digital dating ecosystem. Personal motivations and psychological factors significantly influence how users interact with dating applications, affecting both their level of usage and the risks associated with digital exclusion. As Vera Cruz, et al. [39] explain, problematic Tinder use is closely linked to coping motivations, the pursuit of emotional validation, and the desire for social connection, which can lead to patterns of digital dependency. This type of interaction not only reinforces compulsive usage dynamics but is also shaped by the platform’s algorithmic biases, which prioritize the visibility of certain profiles at the expense of others. Segmentation based on user behavior and past interaction patterns creates access barriers for those who do not fit the algorithm’s established popularity criteria, thereby perpetuating forms of digital exclusion. In this context, the relationship between recommendation algorithms and human behavior is not neutral; rather, it amplifies preexisting inequalities within the online dating ecosystem. Inequalities in profile recommendations within dating platforms are not a minor side effect but a direct consequence of the algorithmic models that govern user visibility. Christensen [14] highlight how traditional recommendation systems tend to concentrate exposure on a small number of highly valued profiles, creating an unequal distribution of interaction opportunities. These dynamic benefits certain users while relegating others to digital invisibility, exacerbating the effects of algorithmic exclusion. In response to this issue, the study introduces a bidirectional matching model designed to redistribute recommendation opportunities more equitably, thereby reducing the concentration of visibility among a few "superstars." However, these findings underscore the need to rethink the role of algorithms in dating platforms, as they are far from being neutral intermediaries. Instead, they actively shape the possibilities for connection and exclusion within the digital environment. Interaction within dating applications not only shapes matchmaking dynamics but also influences how users perceive and negotiate consent in sexual encounters. According to Smith, et al. [40] the growing normalization of objectification in these digital environments—driven by algorithmic systems 1778 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate that prioritize physical appearance over other attributes—affects communication about consent. The tendency of algorithms to reinforce attraction patterns based on aesthetic desirability not only limits diversity in partner selection but also contributes to digital exclusion, where certain profiles receive less visibility and fewer interaction opportunities. Moreover, the mistaken perception that online interactions—such as matching or direct messaging—imply consent highlights the impact of these platforms in reproducing biases and reducing explicit communication about consent in physical encounters. These findings underscore the need to examine how algorithms, far from being neutral, play an active role in shaping social norms within the digital dating ecosystem. The perception of abundance on dating platforms does not always enhance relationship opportunities; on the contrary, it can reinforce digital exclusion. Pronk and Denissen [41] identify the rejection mindset, where excessive exposure to options increases the tendency to systematically reject profiles.This behavior, driven by algorithms that prioritize certain profiles based on previous interactions, results in unequal segmentation. As users face a constant stream of choices, dissatisfaction grows, reducing matches and marginalizing those who do not fit dominant attraction standards. Thus, algorithms not only mediate interactions but also amplify biases that impact fairness in the digital matchmaking experience. Algorithmic decisions on digital platforms do not merely reflect technical criteria; they also incorporate social values and norms that can perpetuate exclusionary dynamics. Mišić [42] argues that technology governance cannot be limited to legal compliance alone but must integrate an anticipatory ethics framework to identify and mitigate biases before they become institutionalized in digital systems. In the context of dating applications, this lack of ethical foresight translates into algorithms that reinforce structural inequalities by prioritizing profiles based on predefined desirability standards, systematically excluding certain user groups. The automation of these processes without ethical oversight mechanisms fosters algorithmic discrimination and limits equitable access to social interaction. Thus, digital exclusion on dating platforms is not a spontaneous phenomenon but rather the result of technological design that, in the absence of robust ethical regulations, reproduces and amplifies preexisting societal biases. The removal of ethnic filters in dating applications, far from promoting equity, has intensified the digital exclusion of racial minorities. Zhou [43] argues that this measure, driven by efforts to combat digital racism, is based on the flawed assumption that all racial preferences are inherently discriminatory. However, these filters also served as tools of empowerment, allowing users to avoid fetishization and connect with like-minded communities. Their removal has resulted in mandatory interracial intimacy, where algorithms—designed within a predominantly white context—continue to privilege certain profiles while marginalizing others. Instead of increasing inclusion, this measure has amplified the invisibility of certain groups, limiting their opportunities for connection. Thus, digital exclusion on these platforms is not solely a result of user interactions but also stems from algorithmic and design decisions that perpetuate preexisting inequalities. The risks associated with using dating applications are not limited to privacy or security concerns; they also amplify dynamics of digital exclusion and algorithmic biases. Phan, et al. [44] highlight how the structure of these platforms not only facilitates interactions but also exposes certain groups to higher levels of vulnerability, including cyber harassment, technology-facilitated intimate partner violence, and discrimination based on gender or race. The collection and processing of personal data, along with the integration of geolocation tools, create inequalities in user exposure and matching processes, favoring certain profiles over others and reinforcing socially constructed desirability standards. Additionally, the opacity in algorithm governance allows platforms to evade accountability for systemic biases in their recommendation models. In this context, digital exclusion in dating applications is not merely about the lack of access to these technologies; it is also about how their systems reinforce patterns of structural discrimination under the guise of personalized and seemingly neutral experiences. 1779 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate Socioeconomic and demographic conditions significantly influence access to and use of digital platforms, exacerbating inequalities in the participation of certain groups within the digital environment. Wilson-Menzfeld, et al. [45] identify that digital exclusion is not solely due to a lack of access to devices or internet connectivity but also to structural barriers such as education, income level, and age—factors that shape how individuals interact with technology. In the context of dating platforms, these digital divides create unequal segmentation, where recommendation algorithms favor users with higher technological capital, while those with lower digital skills or limited access are marginalized within the matchmaking process. The absence of equity mechanisms in these recommendation systems reinforces preexisting biases and contributes to the digital invisibility of certain profiles, highlighting how dating platforms not only reflect but also amplify the structural inequalities present in society. Interactions in digital environments have been radically transformed by geolocation and matchmaking algorithms, creating new forms of inclusion and exclusion. Koch and Miles [46] analyze how dating applications have structured encounters with strangers, prioritizing the visibility of certain users while others remain on the digital periphery. This process reinforces biases related to race, gender, and social class, limiting interactions for those who do not fit the algorithmic criteria of desirability. Moreover, access is not solely dependent on internet connectivity or devices but also on digital literacy, creating new barriers to exclusion. Thus, dating applications do not merely mediate relationships but also reshape urban sociability, reinforcing dynamics of segregation and hierarchy within the digital ecosystem. Digital platforms not only facilitate user interactions but also regulate the visibility and accessibility of certain groups based on their algorithmic designs and implicit norms. Yue and Lim [47] analyze how dating applications and social networks play a crucial role in identity construction and community building for young LGBT individuals in contexts where sexual diversity faces legal and social restrictions. While algorithms can act as allies by recommending relevant content and fostering identity exploration, they also operate under norms that limit user agency, favoring the exposure of certain profiles while marginalizing others. In this sense, platforms do not merely reflect preexisting inequalities but amplify them by conditioning access to safe digital spaces and support networks. Digital exclusion in these environments is not only about technological access but also about how algorithmic systems determine who is seen, who can connect, and who is relegated within the digital structure of desire and social belonging. The access to and prolonged use of dating applications can generate behavioral patterns that reinforce digital exclusion and algorithmic biases within these platforms. Bonilla-Zorita, et al. [48] explore the concept of problematic online dating use, highlighting how certain personality traits—such as sensation-seeking, neuroticism, and low self-esteem—are associated with excessive use of these applications. This behavior is reinforced by recommendation algorithms, which prioritize the visibility of profiles with higher interaction and popularity, disadvantaging those who do not fit these criteria. Moreover, the machine learning models used in these platforms not only record users' preferences but also shape them, limiting the diversity of interactions and reinforcing structural inequalities. In this context, digital exclusion is not only a technological access barrier but also manifests in the invisibilization of certain profiles, creating a digital ecosystem where connection opportunities are distributed unequally. Differences in matchmaking orientation between those who use and those who do not use dating applications reflect dynamics that go beyond individual preferences and are mediated by the algorithms governing these platforms. Barrada, et al. [49] found that users of these applications tend to have a greater orientation toward short-term relationships, suggesting that algorithms may reinforce certain behavioral patterns by prioritizing the visibility of profiles that exhibit higher activity or interaction within the platform. Although no significant differences were identified in long-term orientation, the study highlights how algorithmic biases can shape users' experiences by favoring certain types of interactions over others. This phenomenon demonstrates that digital exclusion in dating applications is 1780 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate not only about technological access but also about how algorithms segment and rank users, limiting diversity and perpetuating inequalities in visibility and connection opportunities within the digital matchmaking ecosystem. Automation in dating platforms has redefined relationship formation but has also introduced biases and digital exclusion that limit certain groups' access to matchmaking. Sharabi [50] notes that algorithms have replaced traditional matchmakers, optimizing partner selection on a large scale while standardizing compatibility criteria. While humans consider emotional and contextual factors, algorithms rely on past patterns and self-reported preferences, reinforcing homogeneous trends and reducing diversity. This automated model restricts user agency, conditioning their options and favoring the visibility of certain profiles based on socially constructed norms of attraction. Thus, digital exclusion in these platforms is not merely about technological access but also about how algorithms determine who has greater opportunities for connection and who is marginalized in the digital dynamics of desire and compatibility. 4. Conclusion Dating applications have reshaped the dynamics of social interaction in the digital sphere, playing a crucial role in users' self-representation and the construction of online identities. However, far from being neutral platforms, the algorithms governing these applications reinforce patterns of exclusion and discrimination by filtering and prioritizing certain profiles over others. Throughout this review, it has been demonstrated how algorithmic decisions impact the representation of diversity, limiting the visibility of certain groups and reinforcing biases related to gender, race, and sexual orientation within these digital spaces. The findings suggest that automation in these platforms amplifies unconscious biases and reinforces hegemonic desirability structures, affecting equity in interaction opportunities. Additionally, gamification and algorithmic segmentation perpetuate dynamics of exclusion, where users must adopt profile optimization strategies to align with the system's criteria. This phenomenon not only influences the perception of digital identity but also shapes how users interact within these environments. To mitigate these effects, it is essential to implement strategies that promote greater equity in digital representation. This includes developing more transparent and ethically responsible algorithms, as well as integrating mechanisms that allow for greater diversity in profile selection. Additionally, future studies are needed to further explore the impact of these algorithmic models in different sociocultural contexts and propose solutions to reduce discrimination in digital environments. Dating applications not only mediate encounters and relationships but also shape norms of representation and belonging in the digital sphere. The review presented here highlights the need to continue researching these spaces from a critical perspective to promote greater equity and inclusion in the online dating ecosystem. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Copyright: © 2025 by the authors. This open-access article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). References [1] J. Pidoux, "A comparative study of algorithmic–user classification practices in online dating: a human–machine learning process," Porn Studies, vol. 10, no. 2, pp. 191-209, 2023. https://doi.org/10.1080/23268743.2022.2104352 https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1080/23268743.2022.2104352 1781 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate [2] K. Nader, "Dating through the filters," Social Philosophy and Policy, vol. 37, no. 2, pp. 237-248, 2020. https://doi.org/10.1017/S0265052521000133 [3] A. Chartrand and S. Duguay, "Sexual and geocultural algorithmic imaginaries: Examining approaches of participatory resignation among LGBTQ+ Instagrammers in Berlin and Montreal," International Journal of Cultural Studies, vol. 28, no. 1, pp. 241-259, 2025. https://doi.org/10.1177/1367877924126729 [4] U. Agudo and H. Matute, "The influence of algorithms on political and dating decisions," Plos one, vol. 16, no. 4, p. e0249454, 2021. https://doi.org/10.1371/journal.pone.0249454 [5] D. Onitiu, "Algorithmic abstractions of ‘fashion identity’and the role of privacy with regard to algorithmic personalisation systems in the fashion domain," AI & SOCIETY, vol. 37, no. 4, pp. 1749-1758, 2022. https://doi.org/10.1007/s00146-021-01235-8 [6] S. Wang, "Calculating dating goals: Data gaming and algorithmic sociality on Blued, a Chinese gay dating app," Information, Communication & Society, vol. 23, no. 2, pp. 181-197, 2020. https://doi.org/10.1080/1369118X.2018.1490796 [7] X. Zhang, Y. Chen, L. Hu, and Y. Wang, "The metaverse in education: Definition, framework, features, potential applications, challenges, and future research topics," Frontiers in Psychology, vol. 13, p. 1016300, 2022. https://doi.org/10.3389/fpsyg.2022.1016300 [8] C. Bandinelli, "Dating apps: Towards post-romantic love in digital societies," International Journal of Cultural Policy, vol. 28, no. 7, pp. 905-919, 2022. https://doi.org/10.1080/10286632.2022.2137157 [9] C. Orwat, "Algorithmic discrimination from the perspective of human dignity," Inclusión Social, vol. 12, pp. 1-18, 2024. https://doi.org/https://doi.org/10.17645/si.7160 [10] Á. Castro and J. R. Barrada, "Dating apps and their sociodemographic and psychosocial correlates: A systematic review," International journal of environmental research and public health, vol. 17, no. 18, p. 6500, 2020. https://doi.org/10.3390/ijerph17186500 [11] L. Zhao, J. Liu, and Z. Li, "Online dating beyond dating apps: An exploration of self-presentation of Chinese gay men dating on Zhihu," International Journal of Communication, vol. 16, p. 19, 2022. [12] H. Regan, "Fields, features, and filters: how dating applications construct sexual fields and romantic and erotic capital," Sexualities, vol. 26, no. 7, pp. 657-677, 2023. https://doi.org/10.1177/13634607211056878 [13] S. Wu and D. Trottier, "Constructing sexual fields: Chinese gay men’s dating practices among pluralized dating apps," Social Media+ Society, vol. 7, no. 2, p. 20563051211009014, 2021. https://doi.org/10.1177/2056305121100901 [14] M. A. Christensen, "“Tindersluts” and “Tinderellas”: Examining the digital affordances shaping the (hetero) sexual scripts of young womxn on Tinder," Sociological Perspectives, vol. 64, no. 3, pp. 432-449, 2021. https://doi.org/10.1177/0731121420950756 [15] L. Stacey and T. D. Forbes, "Feeling like a fetish: Racialized feelings, fetishization, and the contours of sexual racism on gay dating apps," The Journal of Sex Research, vol. 59, no. 3, pp. 372-384, 2022. https://doi.org/10.1080/00224499.2021.1979455 [16] S. De Ridder, "The datafication of intimacy: mobile dating apps, dependency, and everyday life," Television & New Media, vol. 23, no. 6, pp. 593-609, 2022. https://doi.org/10.1177/152747642110526 [17] C. Bandinelli and A. Gandini, "Dating apps: The uncertainty of marketised love," Cultural Sociology, vol. 16, no. 3, pp. 423-441, 2022. https://doi.org/10.1177/17499755211051559 [18] A. Van Kampen, M. J. Phillips, and S. Devenport, "Young women’s conceptualisation and self-representation in online dating: A qualitative analysis," SN Social Sciences, vol. 4, no. 11, p. 198, 2024. https://doi.org/10.1007/s43545-024-00996-5 [19] A. García-Gómez, "Discursive representation of masculinity and femininity in Tinder and Grindr: Hegemonic masculinity, feminine devaluation and femmephobia," Discourse & Society, vol. 31, no. 4, pp. 390-410, 2020. https://doi.org/10.1177/0957926520903523 [20] S. Wu and D. Trottier, "Dating apps: A literature review," Annals of the International Communication Association, vol. 46, no. 2, pp. 91-115, 2022. https://doi.org/10.1080/23808985.2022.2069046 [21] D. Zimmermann, A. Wehler, and K. Kaspar, "Self-representation through avatars in digital environments," Current Psychology, vol. 42, no. 25, pp. 21775-21789, 2023. https://doi.org/10.1007/s12144-022-03232-6 [22] M. W. Ang, J. C. K. Tan, and C. Lou, "Navigating sexual racism in the sexual field: Compensation for and disavowal of marginality by racial minority Grindr users in Singapore," Journal of Computer-Mediated Communication, vol. 26, no. 3, pp. 129-147, 2021. https://doi.org/10.1093/jcmc/zmab003 [23] J. L. Degen and A. Kleeberg-Niepage, "Profiling the self in mobile online dating apps: A serial picture analysis," Human Arenas, vol. 6, pp. 1-25, 2021. https://doi.org/10.1007/s42087-021-00195-1 [24] N. A. Bij de Vaate, J. Veldhuis, and E. A. Konijn, "Ethno-racial identity and digitalisation in self-presentation: A large-scale Instagram content analysis," Behaviour & Information Technology, vol. 42, no. 13, pp. 2210-2225, 2023. https://doi.org/10.1080/0144929X.2022.2112613 [25] A. Gabarnet, G. Feixas, and A. Montesano, "What is the psychological role of the virtual self in online worlds? A scoping review," Multimodal Technologies and Interaction, vol. 7, no. 12, p. 109, 2023. https://doi.org/10.3390/mti7120109 https://doi.org/10.1017/S0265052521000133 https://doi.org/10.1177/1367877924126729 https://doi.org/10.1371/journal.pone.0249454 https://doi.org/10.1007/s00146-021-01235-8 https://doi.org/10.1080/1369118X.2018.1490796 https://doi.org/10.3389/fpsyg.2022.1016300 https://doi.org/10.1080/10286632.2022.2137157 https://doi.org/https:/doi.org/10.17645/si.7160 https://doi.org/10.3390/ijerph17186500 https://doi.org/10.1177/13634607211056878 https://doi.org/10.1177/2056305121100901 https://doi.org/10.1177/0731121420950756 https://doi.org/10.1080/00224499.2021.1979455 https://doi.org/10.1177/152747642110526 https://doi.org/10.1177/17499755211051559 https://doi.org/10.1007/s43545-024-00996-5 https://doi.org/10.1177/0957926520903523 https://doi.org/10.1080/23808985.2022.2069046 https://doi.org/10.1007/s12144-022-03232-6 https://doi.org/10.1093/jcmc/zmab003 https://doi.org/10.1007/s42087-021-00195-1 https://doi.org/10.1080/0144929X.2022.2112613 https://doi.org/10.3390/mti7120109 1782 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 1767-1782, 2025 DOI: 10.55214/25768484.v9i4.6381 © 2025 by the authors; licensee Learning Gate [26] O. Roshchupkina, O. Kim, and E.-J. Lee, "Rules of attraction: Females perception of male self-representation in a dating app," Asia Marketing Journal, vol. 24, no. 4, pp. 169-177, 2023. https://doi.org/10.53728/2765-6500.1597 [27] J. S. Labor, "Mobile sexuality: Presentations of young filipinos in dating apps," Plaridel, vol. 17, no. 1, 2020. [28] A. Halversen, J. King, and L. Silva, "Reciprocal self-disclosure and rejection strategies on bumble," Journal of Social and Personal Relationships, vol. 39, no. 5, pp. 1324-1343, 2022. https://doi.org/10.1177/02654075211055759 [29] R. Bury and L. Easton, "Fun with dick and dick: Homosociality on r/MassiveCock," Sexualities, vol. 25, no. 4, pp. 326- 346, 2022. https://doi.org/10.1007/s12119-024-10273-5 [30] S. Wang and O. T. Zhou, "Being recognized in an algorithmic system: Cruel optimism in gay visibility on Douyin and Zhihu," Sexualities, vol. 27, no. 7, pp. 1185-1204, 2024. https://doi.org/10.1177/13634607221106912 [31] S. A. Huang, J. Hancock, and S. T. Tong, "Folk theories of online dating: Exploring people’s beliefs about the online dating process and online dating algorithms," Social Media+ Society, vol. 8, no. 2, p. 20563051221089561, 2022. https://doi.org/10.1177/20563051221089561 [32] S. Akter, Y. K. Dwivedi, S. Sajib, K. Biswas, R. J. Bandara, and K. Michael, "Algorithmic bias in machine learning- based marketing models," Journal of Business Research, vol. 144, pp. 201-216, 2022. https://doi.org/10.1016/j.jbusres.2022.01.083 [33] L. Espín-Noboa, C. Wagner, M. Strohmaier, and F. Karimi, "Inequality and inequity in network-based ranking and recommendation algorithms," Scientific reports, vol. 12, no. 1, p. 2012, 2022. https://doi.org/10.1038/s41598-022- 05434-1 [34] K. Nader, "The gamification of dating online," Theoria, pp. 1-17, 2024. https://doi.org/https://doi.org/10.1111/theo.12549 [35] J. Banks, M. Monier, M. Reynaga, and A. Williams, "From the auction block to the Tinder swipe: Black women’s experiences with fetishization on dating apps," New Media & Society, p. 14614448241235904, 2024. https://doi.org/10.1177/14614448241235904 [36] K. Martin, "Johnson’s algorithmic accountability and platform responsibility," Available at SSRN 4636695, 2024. http://dx.doi.org/10.2139/ssrn.4636695 [37] E. Kugelberg, "Dating apps and the digital sexual sphere," American Political Science Review, pp. 1-16, 2025. https://doi.org/10.1017/S000305542400128X [38] Y. Shen and Y. Qian, "How to find Mr/miss right? The mechanism of search among online daters in Shanghai," Journal of Family Issues, vol. 45, no. 5, pp. 1087-1115, 2024. https://doi.org/10.1177/0192513X231155603 [39] G. Vera Cruz, E. Aboujaoude, L. Rochat, F. Bianchi-Demicheli, and Y. Khazaal, "Online dating: Predictors of problematic tinder use," BMC Psychology, vol. 12, no. 1, p. 106, 2024. https://doi.org/10.1186/s40359-024-01566-3 [40] A. M. Smith, A. S. Mucedola, K. La, R. R. Ortiz, and Y. Tian, "Swipe, match, consent: Examining the relationship between dating app use and perceptions of sexual consent communication," Available at SSRN 5042901, 2024. http://dx.doi.org/10.2139/ssrn.5042901 [41] T. M. Pronk and J. J. Denissen, "A rejection mind-set: Choice overload in online dating," Social Psychological and Personality Science, vol. 11, no. 3, pp. 388-396, 2020. https://doi.org/10.1177/1948550619866189 [42] J. Mišić, "Ethics and governance in the digital age," European View, vol. 20, no. 2, pp. 175-181, 2021. https://doi.org/10.1177/17816858211061793 [43] Z. B. Zhou, "Compulsory interracial intimacy: Why does removing the ethnicity filter on dating apps not benefit racial minorities?," Media, Culture & Society, vol. 44, no. 5, pp. 1034-1043, 2022. https://doi.org/10.1177/01634437221104712 [44] A. Phan, K. Seigfried-Spellar, and K.-K. R. Choo, "Threaten me softly: A review of potential dating app risks," Computers in human behavior reports, vol. 3, p. 100055, 2021. https://doi.org/10.1016/j.chbr.2021.100055 [45] G. Wilson-Menzfeld et al., "Identifying and understanding digital exclusion: a mixed-methods study," Behaviour & Information Technology, pp. 1-18, 2024. https://doi.org/10.1080/0144929X.2024.2368087 [46] R. Koch and S. Miles, "Inviting the stranger in: Intimacy, digital technology and new geographies of encounter," Progress in Human Geography, vol. 45, no. 6, pp. 1379-1401, 2021. https://doi.org/10.1177/0309132520961881 [47] A. Yue and R. P. Lim, "Digital sexual citizenship and LGBT young people's platform use," International Communication Gazette, vol. 84, no. 4, pp. 331-348, 2022. https://doi.org/10.1177/17480485221094115 [48] G. Bonilla-Zorita, M. D. Griffiths, and D. J. Kuss, "Online dating and problematic use: A systematic review," International journal of mental health and addiction, vol. 19, pp. 2245-2278, 2021. https://doi.org/10.1007/s11469-020- 00318-9 [49] J. R. Barrada, Á. Castro, E. Fernández del Río, and P. J. Ramos-Villagrasa, "Do young dating app users and non-users differ in mating orientations?," PloS one, vol. 16, no. 2, p. e0246350, 2021. https://doi.org/10.1371/journal.pone.0246350 [50] L. L. Sharabi, "Love,(un) automated: Human matchmaking in the era of online dating," Journal of Social and Personal Relationships, vol. 41, no. 11, pp. 3293-3315, 2024. https://doi.org/10.1177/02654075241264720 https://doi.org/10.53728/2765-6500.1597 https://doi.org/10.1177/02654075211055759 https://doi.org/10.1007/s12119-024-10273-5 https://doi.org/10.1177/13634607221106912 https://doi.org/10.1177/20563051221089561 https://doi.org/10.1016/j.jbusres.2022.01.083 https://doi.org/10.1038/s41598-022-05434-1 https://doi.org/10.1038/s41598-022-05434-1 https://doi.org/https:/doi.org/10.1111/theo.12549 https://doi.org/10.1177/14614448241235904 http://dx.doi.org/10.2139/ssrn.4636695 https://doi.org/10.1017/S000305542400128X https://doi.org/10.1177/0192513X231155603 https://doi.org/10.1186/s40359-024-01566-3 http://dx.doi.org/10.2139/ssrn.5042901 https://doi.org/10.1177/1948550619866189 https://doi.org/10.1177/17816858211061793 https://doi.org/10.1177/01634437221104712 https://doi.org/10.1016/j.chbr.2021.100055 https://doi.org/10.1080/0144929X.2024.2368087 https://doi.org/10.1177/0309132520961881 https://doi.org/10.1177/17480485221094115 https://doi.org/10.1007/s11469-020-00318-9 https://doi.org/10.1007/s11469-020-00318-9 https://doi.org/10.1371/journal.pone.0246350 https://doi.org/10.1177/02654075241264720