Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 15, No. 2, 2024 265 Research on User Behavior and Content Consumption Trends in the Era of New Media Jianing Zhu Jinan New Channel -JUTES High School, Jinan, China * Corresponding author: Jianing Zhu (Email: 2387510422@qq.com) Abstract: This article aims to delve into the research on user behavior and content consumption trends in the era of new media, providing valuable insights into understanding contemporary cultural, economic, and social changes. Firstly, by analyzing the characteristics of user behavior in the new media era, it is revealed that user behavior exhibits features such as diversity, real- time interaction, and personalization, exhibiting strong interactivity in the digital environment. These characteristics reflect users' behavioral patterns and preferences in the digital landscape, significantly influencing content consumption. Secondly, the article explores the trends in content consumption during the new media era, including content personalization, diversification of content formats, and the rise of User-Generated Content (UGC). These trends not only reshape the way content is produced and disseminated but also profoundly impact user behavior and consumption patterns. Furthermore, the relationship between user behavior and content consumption is thoroughly examined, uncovering the interplay and influence between the two. Keywords: New media, User behavior, Content consumption, Personalization, Interactivity. 1. Introduction In the era of new media, user behavior and content consumption patterns are undergoing unprecedented changes. With technological advancements, new media platforms have proliferated, not only changing the way people access information but also reshaping the interactive relationship between users and content. This article delves into the three major characteristics of user behavior in the new media era: diversity, interactivity, and personalization, and how these characteristics influence content consumption trends. The article further analyzes the close relationship between user behavior and content consumption, especially in the aspects of mobility and real-time interaction, providing a comprehensive perspective for understanding user behavior and content consumption in the new media environment. 2. Characteristics of User Behavior in the Era of New Media 2.1. Diversity The users in the new media environment exhibit distinct diversity characteristics. With the continuous development of new media technologies, users have access to a rich and diverse array of media channels and content, encompassing various forms such as text, images, audio, and video. The differing characteristics of various media content and user interests result in a diverse user base. Different behaviors on new media platforms reflect varying demands for information and content. Lu Zheng's research [1] suggests that the new media era leads to a diversification of public demand, and, by reasonably stimulating diverse cultural values, new media positively shapes diverse public demands, serving as a positive effect of cultural trends leading the market. This diversity highlights different user interests and demands, posing challenges for content producers and platform operators in designing tailored content strategies and promotional methods. 2.2. Interactivity In the new media environment, users place greater emphasis on interactive and participatory experiences. Through social media, blogs, forums, and other platforms, users can actively engage and establish interactive relationships with media content. Users are no longer passive recipients of information; rather, they have become creators and disseminators of information, providing comments, reposting, and sharing media content. This has led to a more open and interactive user community, with users showcasing a range of interactive methods and frequencies on new media platforms, including commenting, liking, sharing, and participating in thematic discussions. Yao Peidong's research [2] has investigated the emotional resonance of social interaction among new media users, demonstrating that user interaction is not only a response to content but also a form of social communication among users, significantly impacting content dissemination and consumption. Platforms and content creators must promote and guide positive user interaction to facilitate content dissemination and enhance user engagement. 2.3. Personalization In the new media environment, users are increasingly focused on the satisfaction of personalized needs. With the support of internet technology, users can freely select and customize content based on their own interests, preferences, and needs. Through techniques such as recommendation algorithms and personalized content delivery, new media can offer content and services that better align with users' personalized needs, thereby enhancing the overall user experience. New media platforms leverage recommendation systems to provide personalized content recommendations based on users' interests and preferences. This application allows users to quickly discover content that aligns with their preferences, thereby increasing their engagement with the platform and their consumption of content. The emergence of personalized recommendations is aimed at better addressing 266 user needs in an era of information overload, ultimately enhancing the user experience. Scholar Yu Guoming suggests that personalized recommendations involve analyzing user behavior and relationships to uncover user content preferences and potential needs, automatically generating information that meets user demands [3]. This implies that the premise of personalized recommendations is a thorough understanding and collection of users' personal information, with the recommended content likely to sustain user interest and attention. In 2002, Google News first utilized algorithms to generate topic-based news, ranking news from various sources to provide users with personalized news pages [4]. Personalized recommendations not only increase user attention to specific content but also enhance their satisfaction with the platform, ultimately impacting their loyalty and consumption patterns. 3. Content Consumption Trends in the Era of New Media 3.1. Personalized Content Customization In the era of traditional media, people relied primarily on channels such as television, radio, and newspapers for content consumption. Regardless of the city in which you resided, the news you encountered was likely to be the same. However, in the age of internet media, the situation has changed significantly. An increasing number of internet platforms are employing personalized algorithms to provide tailored content recommendations based on users' interests and preferences. Content customization achieved through algorithms and artificial intelligence not only enhances user satisfaction, platform stickiness, and content consumption but also significantly influences user behavior. According to Fan Jinhui et al. [5], personalized recommendation systems help users discover content of interest, thereby increasing the duration and frequency of their content consumption. In recent years, with the rapid development of online audiovisual content, both content production and consumption exhibit a 'personalized' characteristic, with such "personalization" becoming a mindset that has entered the habitual thinking of producers and consumers. Personalization is an inevitable trend resulting from the development of socioeconomic levels and the improvement of people's living standards. "Personalization" directly impacts the "fragmentation" of social consumer strata and the personalization of consumer behavior, implying that the media market will form more segmented forms of consumption. Therefore, personalized recommendations and customized services have become important means of content consumption. By analyzing users' interests and behaviors, media platforms can recommend content that aligns with their personalized needs, enhancing user experience and satisfaction. Personalized recommendations not only increase user attention to specific content but also enhance their satisfaction with the platform, ultimately impacting their loyalty and consumption patterns. This kind of personalized customization not only enhances user experience but also has a positive impact on content consumption behavior. 3.2. Diversification of Content Formats Another prominent characteristic of content consumption trends in the era of new media is the diversification of content formats. In the past, people primarily obtained information through reading text. However, with the improvement of internet bandwidth and the widespread use of smartphones, consumption of content in forms such as video and audio has become increasingly common. For example, platforms like the video-sharing website YouTube and the short video app TikTok provide a wide variety of video content. People can acquire knowledge, entertainment, and inspiration through watching videos. Additionally, audio-based content such as podcasts and audiobooks is also gaining popularity. These diverse content formats enrich users' content choices and meet their needs for different forms of content. Diversified demand is another important trend in content consumption. Users' demand for content is no longer limited to traditional media's information and entertainment; they expect content to meet their personalized needs. Users increasingly seek interesting and profound content that captures their interest and stimulates their thinking. Simultaneously, users also pursue the practicality of content, hoping that it can help them solve problems and provide useful information. This trend of diversified demand prompts content creators to provide more diverse and personalized content to meet user needs. For example, video content excels at capturing user attention and promoting interaction, while text content excels at imparting in-depth information and knowledge. Research by Zheng Yuanyuan [6] indicates that diverse content formats meet users' different consumption needs, increasing their engagement and satisfaction with the content. Therefore, various content formats have different impacts on user behavior and content consumption. Platforms and content producers must design strategies based on the characteristics of different content formats to optimize user experience and content consumption outcomes. 3.3. The Rise of User-Generated Content (UGC) UGC is an abbreviation for User-Generated Content, referring to content created, published, and shared by ordinary users. Unlike content created by professional editors and production teams in traditional media, UGC is spontaneously generated by users and can include various forms such as text, images, videos, and audio. The rise of UGC has transformed traditional content production and distribution models, increasing user engagement and granting users more rights in content creation and expression. The emergence of user-generated content (UGC) has altered traditional content production and distribution models, significantly impacting user behavior and content consumption. According to Wang Zhiran and others, UGC products exhibit vividness, interactivity, and timeliness, all of which have varying degrees of direct impact on purchase intentions. By using video or image formats to enhance interactivity and timely release, UGC content increases user willingness to make purchases. The rise of UGC content promotes increased user engagement, enhances user platform stickiness, and enriches the diversity of content formats and topics on the platform. Users are more inclined to believe and engage with UGC content because it is closer to their lives, more authentic, and resonates emotionally [7]. Therefore, the rise of UGC content not only increases user engagement with the platform but also has a positive impact on content consumption and user behavior. 267 4. The Relationship between User Behavior and Content Consumption in the Era of New Media 4.1. The Interaction between User Behavior and Content Consumption There is a close and reciprocal relationship between user behavior and content consumption. On the one hand, the characteristics of user behavior influence content consumption trends; on the other hand, content consumption trends, in turn, impact user behavior choices. Firstly, the characteristics of user behavior influence content consumption trends. The demand for personalized content among users has prompted content creators to provide more diverse and personalized content. User behavior habits and interests also influence their content consumption behavior on different platforms. Some users prefer to browse and share interesting content on social media, while others are inclined to obtain practical information and news on news portals. On the other hand, content consumption trends also reciprocally influence user behavior choices. Research by Zhou Limei and others [8] found that content platforms' recommendation algorithms and personalized services can recommend content that aligns with users' interests and needs based on their behavior and consumption habits. This kind of personalized recommendation and service can alter user consumption habits and behavior, making them more inclined to consume specific types of content on specific platforms. The socialization and interactivity of content consumption also influence user behavior. Users sharing and commenting on content on social media can attract the attention and responses of other users, enhancing interaction between users and content. This trend of socialization and interactivity can prompt users to actively engage in content creation and sharing, thereby affecting their behavior and consumption habits. Therefore, there exists a close and reciprocal relationship between user behavior and content consumption. This relationship not only reflects the characteristics of user behavior and content consumption in the era of new media but also provides important reference and insights for content creators and media platforms. Content creators and media platforms need to provide more diverse and personalized content and services based on user behavior and consumption habits to meet user needs and expectations. At the same time, users also need to select content and platforms that align with their interests and needs to achieve a more satisfying content consumption experience. 4.2. How New Media Platforms Optimize User Behavior to Promote Content Consumption In the era of new media, many platforms utilize recommendation algorithms and personalized services to meet users' individualized needs. This type of personalized recommendation system analyzes users' behaviors and consumption habits to understand their interests and preferences, and then recommends content that aligns with their interests and needs. Personalized recommendations have a significant impact on user behavior and content consumption. Firstly, personalized recommendations can provide more precise content matching. By analyzing users' browsing history, click behaviors, collections, and subscriptions, recommendation systems can understand users' interests and preferences, thereby recommending content that better aligns with their interests. This precise matching can enhance user satisfaction, making them more willing to engage in content consumption guided by the recommendation system. Secondly, personalized recommendations can expand users' content consumption scope. Through the recommendation system, users can access content they may not have actively searched for or discovered on their own. The recommendation system, based on users' interests and preferences, recommends similar or related content, enriching users' content consumption experience. This expanded content selection can satisfy users' curiosity and desire for exploration, making them more willing to engage in content consumption on the platform. Additionally, personalized recommendations can also provide customized services. The recommendation system can tailor specific features and experiences for users based on their preferences and needs. According to users' preferences, the recommendation system can set personalized homepages, push notifications, or customized content subscription services. This personalized service can enhance user convenience and satisfaction, prompting them to use the platform more frequently for content consumption. Therefore, personalized recommendations have a significant impact on user behavior and content consumption. They offer precise content matching, expanded content selection, and personalized services, making users more willing to engage in content consumption guided by the recommendation system. 4.3. The Relationship between User Behavior and the Mobility and Immediacy of Content Consumption The relationship between user behavior and content consumption in the era of new media is closely tied to the mobility and immediacy brought about by mobile internet and instant communication technologies. The widespread adoption of mobile internet and instant communication technologies has allowed users to access and consume content anytime, anywhere through mobile devices, significantly impacting user behavior and content consumption patterns. Research by Ghose and others [9] demonstrates that mobile user behavior has made content access and consumption more convenient and flexible. Users are no longer confined to traditional computer terminals and can access the internet and various content platforms at any time and in any place using smartphones, tablets, and other mobile devices. Whether on public transportation, in cafes, or at home, users can engage in content consumption through mobile devices. This mobile behavior has led to more frequent content consumption and increased user exposure to content. Furthermore, the immediacy of user behavior has made their demand for content more urgent. In the new media era, there is an increasing demand for timely access to the latest information and instant interaction. Through mobile devices, users can instantly access news, social media updates, live events, and more. They can promptly respond and comment, engaging in real-time interaction and communication with other users. This immediacy has inclined users to focus on and consume content that provides real-time updates and interaction. The mobile nature and immediacy of user behavior also present new challenges and opportunities for content creators and media platforms. To meet the demands of mobile users, 268 content creators and media platforms need to provide content and interfaces tailored for mobile devices, ensuring a positive user experience on these platforms. Additionally, they need to offer real-time updates and interactive features to maintain close contact and interaction with users, thereby attracting their attention and engagement. Therefore, the mobility and immediacy of user behavior in the era of new media are closely intertwined. The widespread use of mobile devices allows users to engage in content consumption anytime, anywhere, while the development of instant communication technologies satisfies users' need for instant interaction and access to the latest information. This mobile and immediate behavior imposes new requirements on content creators and media platforms, necessitating them to adapt to user behavior patterns and provide content and services that align with user needs. 5. Conclusion The characteristics of user behavior in the new media era have profound effects on content consumption. The diverse, interactive, and personalized user behavior characteristics drive the personalized and diversified development of content consumption. Content producers and platform operators need to tailor content strategies and promotional methods based on user behavior characteristics to meet evolving user needs. Moreover, there is a close mutual relationship between user behavior and content consumption, and content consumption trends also affect user behavior choices. Therefore, new media platforms need to utilize recommendation algorithms and personalized services to meet users' personalized needs, providing precise content matching, expanded content choices, and personalized services to encourage users to consume content. Additionally, the mobility and immediacy of user behavior make users' content access and consumption more convenient and urgent, presenting new challenges and opportunities for content creators and media platforms. In summary, the relationship between user behavior and content consumption in the new media era is becoming increasingly intertwined. Content creators and platform operators need to fully understand user behavior characteristics, continuously optimize content and services, and enhance user experience to promote sustained growth in content consumption. References [1] Lu Zheng. (2013). A Reverse Thinking of Diverse Demands of the Public in the New Media Era. Editor's Friend, 9, 62-64. [2] Yao Peidong. (2021). Emotional Resonance in New Media User Social Interaction: A Case Study of WeChat's "Poke" Feature. New Media, 10, 28-30. [3] Yu Guoming & Li Huijuan. (2014). Transformation Path of Media Industry in the Big Data Era: An Analysis of Customized Content, Crowdsourced Production, and Cross- Border Integration Practice. Modern Communication (Journal of Communication University of China), 12, 1-5+11. [4] Liu Shichao. (2018). A New Perspective on Interpretation of Public Opinion: Analyzing New Media Events from the Perspective of Interaction Ritual Theory. Southeast, 10, 83-84. [5] Fan Jinhui, Shen Jiayi, & Liu Jianhong. (2011). Research on the Trend of TV Audience Content Consumption Demand and Industry Development. China Digital TV, 6, 67-70. [6] Zheng Yuanyuan. (2023). Research on Diversified Content Consumption Product Recommendation Method Based on Clustering and Reordering. Harbin: Harbin Institute of Technology. [7] Wang Zhiran, Wang Tiantian, Wu Jiangmeng, & Wang Ruoyu. (2024). The Impact of Social E-commerce UGC Sharing Recommendations on Consumer Purchase Intentions. China Market, 11, 121-125. [8] Zhou Limei & Wang Chunyan. (2024). Research on Data Mining of E-commerce Platform User Behavior and Consumer Behavior Prediction. Old Brand Marketing, 9, 18-20. [9] Ghose, A., & Han, S. (2011). User Content Generation and Usage Behavior on the Mobile Internet: An Empirical Analysis. Economics of Networks eJournal.