More Like this

1. Exploring Platform Migration Patterns between Twitter and Mastodon: A User Behavior Study

   Jeong, Ujun; Sheth, Paras; Tahir, Anique; Alatawi, Faisal; Bernard, H. Russell; Liu, Huan (August 2023, International AAAI Conference on Web and Social Media)

   A recent surge of users migrating from Twitter to alternative platforms, such as Mastodon, raised questions regarding what migration patterns are, how different platforms impact user behaviors, and how migrated users settle in the migration process. In this study, we elaborate how we investigate these questions by collecting data over 10,000 users who migrated from Twitter to Mastodon within the first ten weeks following Elon Musk's acquisition of Twitter. Our research is structured in three primary steps. First, we develop algorithms to extract and analyze migration patters. Second, by leveraging behavioral analysis, we examine the distinct architectures of Twitter and Mastodon to learn how different platforms shape user behaviors on each platform. Last, we determine how particular behavioral factors influence users to stay on Mastodon. We share our findings of user migration, insights, and lessons learned from the user behavior study. 

   more » « less
2. Profile update: the effects of identity disclosure on network connections and language

   https://doi.org/10.1140/epjds/s13688-024-00483-0  

   Choi, Minje; Romero, Daniel_M; Jurgens, David (June 2024, EPJ Data Science)

   Abstract Our social identities determine how we interact and engage with the world surrounding us. In online settings, individuals can make these identities explicit by including them in their public biography, possibly signaling a change in what is important to them and how they should be viewed. While there is evidence suggesting the impact of intentional identity disclosure in online social platforms, its actual effect on engagement activities at the user level has yet to be explored. Here, we perform the first large-scale study on Twitter that examines behavioral changes following identity disclosure on Twitter profiles. Combining social networks with methods from natural language processing and quasi-experimental analyses, we discover that after disclosing an identity on their profiles, users (1) tweet and retweet more in a way that aligns with their respective identities, and (2) connect more with users that disclose similar identities. We also examine whether disclosing the identity increases the chance of being targeted for offensive comments and find that in fact (3) the combined effect of disclosing identity via both tweets and profiles is associated with a reduced number of offensive replies from others. Our findings highlight that the decision to disclose one’s identity in online spaces can lead to substantial changes in how they express themselves or forge connections, with a lesser degree of negative consequences than anticipated. 

   more » « less
3. Political Elites in the Attention Economy: Visibility Over Civility and Credibility?

   https://doi.org/10.1609/icwsm.v19i1.35814  

   Biswas, Ahana; Lin, Yu-Ru; Tai, Yuehong Cassandra; Desmarais, Bruce A (June 2025, Proceedings of the International AAAI Conference on Web and Social Media)

   Elected officials have privileged roles in public communication. In contrast to national politicians, whose posting content is more likely to be closely scrutinized by a robust ecosystem of nationally focused media outlets, sub-national politicians are more likely to openly disseminate harmful content with limited media scrutiny. In this paper, we analyze the factors that explain the online visibility of over 6.5K unique state legislators in the US and how their visibility might be impacted by posting low-credibility or uncivil content. We conducted a study of posting on Twitter and Facebook (FB) during 2020-21 to analyze how legislators engage with users on these platforms. The results indicate that distributing content with low-credibility information attracts greater attention from users on FB and Twitter for Republicans. Conversely, posting content that is considered uncivil on Twitter receives less attention. A noticeable scarcity of posts containing uncivil content was observed on FB, which may be attributed to the different communication patterns of legislators on these platforms. In most cases, the effect is more pronounced among the most ideologically extreme legislators. Our research explores the influence exerted by state legislators on online political conversations, with Twitter and FB serving as case studies. Furthermore, it sheds light on the differences in the conduct of political actors on these platforms. This study contributes to a better understanding of the role that political figures play in shaping online political discourse. 

   more » « less
4. Analysis of and defense against crowd-retweeting based spam in social networks

   https://doi.org/10.1007/s11280-018-0613-y  

   Liu, Bo; Ni, Zeyang; Luo, Junzhou; Cao, Jiuxin; Ni, Xudong; Liu, Benyuan; Fu, Xinwen (June 2018, World Wide Web)

   Social networking websites with microblogging functionality, such as Twitter or Sina Weibo, have emerged as popular platforms for discovering real-time information on the Web. Like most Internet services, these websites have become the targets of spam campaigns, which contaminate Web contents and damage user experiences. Spam campaigns have become a great threat to social network services. In this paper, we investigate crowd-retweeting spam in Sina Weibo, the counterpart of Twitter in China. We carefully analyze the characteristics of crowd-retweeting spammers in terms of their profile features, social relationships and retweeting behaviors. We find that although these spammers are likely to connect more closely than legitimate users, the underlying social connections of crowd-retweeting campaigns are different from those of other existing spam campaigns because of the unique features of retweets that are spread in a cascade. Based on these findings, we propose retweeting-aware link-based ranking algorithms to infer more suspicious accounts by using identified spammers as seeds. Our evaluation results show that our algorithms are more effective than other link-based strategies. 

   more » « less
5. Analyzing the Engagement of Social Relationships during Life Event Shocks in Social Media

   https://doi.org/10.1609/icwsm.v17i1.22134  

   Choi, Minje; Jurgens, David; Romero, Daniel M. (June 2023, Proceedings of the International AAAI Conference on Web and Social Media)

   Individuals experiencing unexpected distressing events, shocks, often rely on their social network for support. While prior work has shown how social networks respond to shocks, these studies usually treat all ties equally, despite differences in the support provided by different social relationships. Here, we conduct a computational analysis on Twitter that examines how responses to online shocks differ by the relationship type of a user dyad. We introduce a new dataset of over 13K instances of individuals' self-reporting shock events on Twitter and construct networks of relationship-labeled dyadic interactions around these events. By examining behaviors across 110K replies to shocked users in a pseudo-causal analysis, we demonstrate relationship-specific patterns in response levels and topic shifts. We also show that while well-established social dimensions of closeness such as tie strength and structural embeddedness contribute to shock responsiveness, the degree of impact is highly dependent on relationship and shock types. Our findings indicate that social relationships contain highly distinctive characteristics in network interactions, and that relationship-specific behaviors in online shock responses are unique from those of offline settings. 

   more » « less