Selected Papers of #AoIR2024: The 25th Annual Conference of the Association of Internet Researchers Sheffield, UK / 30 Oct - 2 Nov 2024 Conner, V.A. (2024, October). Nostalgic Neighborhoods of TikTok: Mapping a Topology of Affective Publics. Paper presented at AoIR2024: The 25th Annual Conference of the Association of Internet Researchers. Sheffield, UK: AoIR. Retrieved from http://spir.aoir.org. NOSTALGIC NEIGHBORHOODS OF TIKTOK: MAPPING A TOPOLOGY OF AFFECTIVE PUBLICS Viki Askounis Conner University of Illinois-Chicago Nostalgia is a culturally resonant and politically potent sensemaking resource that frames how people see the past and understand their place in the world. Despite attention to how social media platform political economies and affordances affect nostalgic practices of remembering (e.g., Jacobsen & Beer, 2021; Niemeyer & Keightley, 2020; Pentzold & Menke, 2020), there is a lack of research applying network analytic methods to study its structure and social-semiotic function in digital networks which enable new forms of connective action (Bennett & Segerberg, 2013) based on discursive, affective, and mimetic bonds. While research indicates nostalgia’s dual-edge function in group dynamics of social solidarity and exclusion (e.g., Sedikides & Wildschut, 2019), these studies often take collective identity a priori. Through a content and semantic network analysis of the popular hashtag #nostalgia (>140B views) on TikTok, this study offers a first step toward understanding the meaning of nostalgia in networked processes of group identification by mapping the topology of the “nostalgic neighborhoods” on the platform emerging from the co-linkages of hashtags. As TikTok’s algorithmic affordances render affiliation networks opaque as they are less rooted in interpersonal social ties (Zulli & Zulli, 2022), this study contributes important insights into how the hashtag, as a semiotic technology (Zappavigna, 2018), structures nostalgic publics on a platform that has emerged as a popular site for nostalgia within youth cultures. Conceptualizing Networked Nostalgia This study brings the scholarship on nostalgia and media (e.g., Niemeyer, 2021) into dialogue with theories of social organization in the networked public sphere to define and operationalize networked nostalgia. While nostalgia has been differentially understood as a medical illness, an emotion, a zeitgeist, an aesthetic, and a rhetorical weapon during its short history as a modern named emotion (Becker, 2023), its etymology (nostos – return home; algia – pain) reveals its Homeric, locative meaning as nostalgia discursively and affectively orients a subject in time and space in the search of the “lost” home (Hepper, 2012). I offer that networked nostalgia is an emotive (Reddy, 2001), or performative emotion, that is semantically networked, linking understanding of nostalgia’s dimensions of time and space through affective and discursive modalities of sensemaking afforded by the structures of digital networks. As the literature on networked publics (boyd, 2010) and hashtag publics (Bruns et al, 2016) shows, hashtags are not only markers of location, as a technical affordance that aids in finding content and navigating platforms; they also serve socio-linguistic functions by discursively expressing ideas and sentiment, contributing to ambient forms of affiliation (Zappavigna, 2018, 2011). Thus, I argue that how people use its main hashtag, #nostalgia, both reveals and constitutes communities on the platform. Two questions guided this study: RQ1: What are the most popular hashtags connected to #nostalgia, and what semiotic functions do they serve within the overall co-hashtag network? RQ2: What do the co-occurrences of hashtags within the semantic neighborhoods of #nostalgia tell us about the meaning of nostalgia as basis for affiliation? Method As the first study of its kind, semantic network analysis (Danowski, 1993) permitted attention to the basic structure of nostalgia’s meaning at the level of the hashtag – one of TikTok’s primary affordances of visibility and association (Zulli & Zulli, 2022). Following Zappavigna (2018), I defined the hashtag as a semiotic technology with linguistic and technical functions permitted by a platform’s socio-technical affordances of visibility and association (Treem & Leonardi, 2013). I purposively selected #nostalgia as the entry point for this study given its direct semantic link to the term “nostalgia.” Data collection followed best practices identified by the Digital Methods Initiative at the University of Amsterdam as shared at the 2023 Association of Internet Researchers Annual Conference pre-conference. The final dataset included 975 videos over the timeframe May 19, 2019 to November 10, 2023. The network contained 2,737 nodes (hashtags) and 36,308 edges (co-occurrences). I measured the co-occurrence of hashtags in the network using Gephi and used its Louvain modularity algorithm to reveal the internal hierarchical structure of the network. After identifying twenty neighborhoods, I analyzed key statistical measures to assess their structural properties, manually coded the top 100 hashtags, and undertook a thematic content analysis of seven selected neighborhoods identified for deeper analysis. Summary Findings Based on the equivalence of these neighborhoods’ semantic structures and thematic meanings, I identified three types of affective publics (Papacharissi, 2015), below, that emerged in relation to different linguistic and technical functions of the hashtag. Given the centrality of technical hashtags (#fyp, #viral) in the overall co-tag network connected to #nostalgia (figure 1), I found the differential use of technical hashtags, as co-linked with affective and discursive hashtags, impacted the affective intensities and meanings of nostalgia within these publics. I argue these findings underscore the importance of TikTok’s socio-technical affordances in “wiring” semantic bonds of nostalgic affiliation and point to the difficulties of disentangling the logics of imitation (Zulli & Zulli, 2022) from the dynamics of affective publics on the platform (e.g., Hautea et al, 2021). • Play-grounds described dense fan or participatory cultures (Jenkins & Ito, 2015) marked by semantic variation, a joyful affective valence, and higher than average degree centrality scores. Two nostalgic neighborhoods typified this type of affective public – one centered around gaming (coded in pink) and another centered around celebrity and parasocial interaction (coded in gray). • Heart-lands (coded in green, taupe, and black) described less dense, but highly interconnected, affective memory worlds centered around nostalgic experiences and moods (e.g., “vibes”) typified by links to childhood objects, “-core” aesthetics, and music. While these neighborhoods were connected to the overall network through technical hashtags, these markers tended to be less virally articulated, such as #fyp or #greenscreen (in contrast to #viral or #meme), and used in ways that connoted their interpersonal meaning as a visibility or editability affordance. • Reflecting pools (coded in blue and orange) represented a third, hybrid type affective public. While structurally similar to heart-lands, reflecting pools more explicitly engaged with the mimetic templates TikTok affords for personal memory as expressed through its imitation logics and participation in mimetic repertoires such as the “then/now” meme and the “evolution” challenge. Future Directions This study laid important conceptual and empirical groundwork in mapping the social- semiotic terrain that constitutes nostalgic publics on TikTok. While limited by its focus on the semantic marker of the hashtag, future studies can incorporate multi-modal layers to augment view of the topology of the network revealed here. Recognizing nostalgia is often weaponized by far right-wing political actors (e.g., Menke & Wulf, 2021), future work might extend the metaphor of the neighborhood to identify the “networked gatekeepers” (Meraz & Papacharissi, 2013) of these publics to better understand the dynamics of power and information flow within this semantic network. References Abidin, C. 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Overall network (with degree centrality scores) Figure 2. Nostalgic neighborhoods selected for thematic analysis