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Sports leagues have stood out in the entertainment industry due to their great economic value and cultural impact. This is the case of the American sports leagues, with emphasis on the National Basketball Association (NBA), whose largest Latin American market lies on Brazil. The aforementioned league’s audience is constantly growing, a fact that can be partially explained by the encouragement provided for its viewers to interact through social media, in a phenomenon called social TV. Accordingly, the aim of the present study is to investigate how social TV works as a means for Brazilian fans to coproduce their NBA broadcasting enjoyment through social media interactions.

The authors conducted a netnography on the community of fans engaged in Twitter hashtag #NBAnaESPN, which was released by ESPN to promote audience integration during NBA games' broadcasting.

A theorization about the role played by social TV in the way fan culture articulates through social media to enjoy broadcasting media products was herein presented. The findings of this study have evidenced three categories concerning the role played by television broadcasting, social media and the fandom in NBA consumption by Brazilian fans. Based on these findings, the authors got to the conclusion that social TV establishes a mediatized environment where fan culture can be articulated through social media to enable interactions about television broadcasting.

The study was limited to members of the Brazilian NBA audience who engage in the official social media of the league’s broadcasting.

The study heads toward a theoretical generalization based on the research results.

Given the rise of sport non-fungible tokens (NFTs) and sponsorships from cryptocurrency companies in the sport industry during the coronavirus disease 2019 (COVID-19) pandemic, this paper aims to critically frame the partnerships between cryptocurrency and sport by exploring the reception of fan tokens amongst supporters of three English Premier League clubs: Manchester City, Everton and Crystal Palace.

Drawing upon the emerging critical scholarship on cryptocurrency and the political economy of professional football, this study uses digital ethnography in an attempt to understand the major themes emanating from the online forum discussions amongst fans in response to the issuance of fan tokens by the aforementioned three clubs, among other types of partnerships with crypto companies.

The supporters’ critical deliberations revolved around the contradictions of fan tokens (as a means for supposed “fan engagement” or for financial speculation) and the utility of cryptocurrency for the public. These reactions in turn showcase a larger tension underlying the financially unstable professional football industry: the contest between the owners and the fan bases over the exchange value (for profit) and use value (for community) of the clubs.

This paper is one of the first studies to adopt a critical framework to examine the emerging partnerships between sports and cryptocurrency companies during the COVID-19 pandemic. It also provides one of the first in-depth analyses of the critical receptions of sport NFTs amongst sport fans. While contributing to the literature on fan activism/protest in the context of the commercialization and commodification of sport, the paper also raises new questions on the responsible use of cryptocurrency/NFT in sport.

The purpose of this paper was (1) to examine the underexplored intersection of sports betting and favorite team loyalty, and (2) to assess differences in gambling behavior among sport bettors by varying levels of team loyalty.

A total of 1,555 National Football League (NFL) bettors and non-betting NFL fans were surveyed to assess media consumption across a mix of team loyalty attitudes and betting behaviors.

Statistically significant differences were found between four types of NFL fans (casual, team loyalty-dominant, betting-dominant and hybrid) as it relates to media consumption in various forms. Most notably, the results suggested symbiosis between the activities.

The symbiosis finding, though preliminary, suggests the activity provides an additional platform for consumers to connect with spectator sport. Furthermore, the act of betting, like participation in fantasy sports, appears to spur consumption of the NFL product generally. The study, however, was limited to NFL fans, did not specify the method for sports betting, nor the intensity of gambling.

Teams should not worry that betting detracts from fan engagement with the team product. Also, leagues and media providers should continue to highlight betting content as participants consume at higher rates than non-participating sports fans.

Team fandom may potentially moderate problem behavior among bettors. The betting results indicate being a loyal team fan lowers one’s gambling spend per month and largest bet compared to non-loyal bettors. However, the hybrid fan showed significantly higher media consumption levels.

Sports fans have more opportunities to interact and engage with their favorite games than ever before. However, consumers have limited amounts of time and money, and this study is one of the first to examine differences in fan interests and behaviors related to sport betting and team loyalty and the resulting viewership and consumption behavior.

Although many attempts to discover key segments of sport spectators have been extant, little segmentation effort has been made to reflect pandemic situations such as the COVID-19 pandemic. The purpose of this research is twofold: (1) to classify sport spectators into key segments based on perceived risks associated with a mass-gathered sporting event during the COVID-19 pandemic and (2) to identify each segment’s profiles.

Questionnaire surveys of spectators attending a Japanese rugby game during the COVID-19 pandemic (January–June 2021) were conducted (n = 1,410). A combination of hierarchical and non-hierarchical clustering methods was executed.

The results revealed the five-cluster solution as the optimal number of clusters representing the samples (i.e. spectators with extremely low-risk perception, those with low-risk perception, those with moderate-risk perception, those with high-risk perception and those with higher social risk perception). This five-cluster solution showed sufficient stability and validity. Moreover, each segment had different profiles regarding three background aspects – demographics, psychographics and behavioral variables.

This study is the first effort to segment sport spectators based on perceived risks associated with a mass-gathered sporting event in the pandemic situation. Despite extensive segmentation studies to explore sport fans, contribution reflecting the post-crisis situations is scant. Therefore, the findings provide insight into this realm by providing a new viewpoint for understanding sport spectators during a possible future pandemic era.

The identification of network user relationship in Fancircle contributes to quantifying the violence index of user text, mining the internal correlation of network behaviors among users, which provides necessary data support for the construction of knowledge graph.

A correlation identification method based on sentiment analysis (CRDM-SA) is put forward by extracting user semantic information, as well as introducing violent sentiment membership. To be specific, the topic of the implementation of topology mapping in the community can be obtained based on self-built field of violent sentiment dictionary (VSD) by extracting user text information. Afterward, the violence index of the user text is calculated to quantify the fuzzy sentiment representation between the user and the topic. Finally, the multi-granularity violence association rules mining of user text is realized by constructing violence fuzzy concept lattice.

It is helpful to reveal the internal relationship of online violence under complex network environment. In that case, the sentiment dependence of users can be characterized from a granular perspective.

The membership degree of violent sentiment into user relationship recognition in Fancircle community is introduced, and a text sentiment association recognition method based on VSD is proposed. By calculating the value of violent sentiment in the user text, the annotation of violent sentiment in the topic dimension of the text is achieved, and the partial order relation between fuzzy concepts of violence under the effective confidence threshold is utilized to obtain the association relation.

Conversations around diversity, race and science fiction and fantasy films/television have sparked in response to recent casting decisions made in the upcoming live-action The Little Mermaid, The Lord of the Rings: The Rings of Power and Star Wars' Obi-Wan Kenobi (Deggans, 2022; Romano, 2022). Backlash against casting of actors of Color in these genres highlights racial projects where a cultural memory of whiteness comes up against multicultural change. The authors of this paper feel that there is great potential in using current-day racial issues around fantasy films/television to explore these racial projects with students in social studies classes (Omi and Winant, 2014).

Using a qualitative textual analysis (Peräkylä, 2005), the authors examined online news media outlets addressing the casting of actors of Color in the aforementioned media pieces. After reviewing over twenty articles, the authors determined two major themes that would serve as the findings.

In this paper, themes of nostalgia for an imagined ‘way things were’ and future-based fears of how things will become emerged from the analysis, revealing a need for engaging students in the history of sci-fi and fantasy media, and the existing, diverse histories of storytelling featuring multiple races.

The authors argue that examining racial projects found in contemporary sci-fi and fantasy casting are chances for students to understand complex racial histories and how they blend into current-day cultural landscapes, and are opportunities to practice analysis of real-life racial histories and richly-imagined fantasy worlds, noticing how and why the two often collide when it comes to race.

Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

This study aimed to identify subgroups of esports players based on their gaming behavior patterns across game genres and compare self-efficacy, social efficacy, loneliness and three dimensions of quality of life between these subgroups.

324 participants were recruited from prolific academic to complete an online survey. We employed latent profile analysis (LPA) to identify subgroups of esports players based on their behavioral patterns across genres. Additionally, a one-way multivariate analysis of covariance (MANCOVA) was conducted to test the association between cluster memberships and development and well-being outcomes, controlling for age and gender as covariates.

LPA analysis identified five clusters (two single-genre gamer groups, two multigenre gamer groups and one all-genre gamer group). Univariate analyses indicated the significant effect of the clusters on social efficacy, psychological health and social health. Pairwise comparisons highlighted the salience of the physical enactment-plus-sport simulation genre group in these outcomes.

This study contributes to the understanding of the development and well-being benefits experienced by various esports consumers, as well as the role of specific gameplay in facilitating targeted outcomes among these consumer groups.

In a dynamic, continuously evolving sports landscape, social media have become an indispensable tool for sports organizations to cultivate meaningful connections with fans. The rapid pace of technological advancements has elevated these digital platforms from a supplementary role to a pivotal position within strategic management frameworks. The existing literature explores how football clubs can utilize social media, but analyzing social media strategies within the context of football leagues is lacking. The absence of comparative studies benchmarking clubs across different geographical regions while simultaneously analyzing multiple social media platforms is especially noteworthy. In this study, a comprehensive analysis of social media engagement is undertaken within esteemed football leagues spanning Europe, South America and North America.

Drawing on relationship marketing and employing content analysis as a methodological tool, the study examined 10,772 posts from the official accounts of eight football leagues on Facebook, Twitter and Instagram.

Across the leagues, the findings reveal that content quality drives engagement more than frequency. In addition, several format combinations were identified that facilitate engagement and Instagram emerged as the top social media platform for generating fan engagement.

This is one of the first empirical studies focusing on optimizing the use of social media to amplify fan engagement across various geographies and social media accounts and formats simultaneously.

Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media.

For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance.

The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts.

Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.