We use public data from Twitter to study the breakups of the romantic relationships of 661 couples. Couples are identified through profile references such as @user1 writing "@user2 is the best boyfriend ever!!". Using this data set we find evidence for a number of existing hypotheses describing psychological processes including (i) pre-relationship closeness being indicative of post-relationship closeness, (ii) "stonewalling", i.e., ignoring messages by a partner, being indicative of a pending breakup, and (iii) post-breakup depression. We also observe a previously undocumented phenomenon of "batch un-friending and being un-friended" where users who break up experience sudden drops of 15-20 followers and friends. Our work shows that public Twitter data can be used to gain new insights into psychological processes surrounding relationship dissolutions, something that most people go through at least once in their lifetime.
The only work we know of on studying romantic relationships on Twitter is @cite_8 . Using answers to specific questions (from surveys) from a few hundred users, they look at how Twitter mediates conflict between couples. They find evidence that active Twitter use leads to greater amounts of Twitter-related conflict among romantic partners, which in turn leads to infidelity, breakup, and divorce''.
@cite_8
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We use public data from Twitter to study the breakups of the romantic relationships of 661 couples. Couples are identified through profile references such as @user1 writing “@user2 is the best boyfriend ever!!”. Using this data set we find evidence for a number of existing hypotheses describing psychological processes including (i) pre-relationship closeness being indicative of post-relationship closeness, (ii) “stonewalling”, i.e., ignoring messages by a partner, being indicative of a pending breakup, and (iii) post-breakup depression. We also observe a previously undocumented phenomenon of “batch un-friending and being un-friended” where users who break up experience sudden drops of 15-20 followers and friends. Abstract In this study, we examined two behaviors that could evoke Facebook jealousy and cause relationship problems among romantic partners: (1) Facebook solicitation behaviors (i.e., making or accepting friend requests with romantic interests) while in the current relationship, and (2) having romantic interests on existing Facebook friends lists. In our sample of 148 undergraduates, those who had lower commitment to their partners were more likely to make and accept Facebook friend requests with romantic interests during their relationship. However, commitment was unrelated to the number of romantic alternatives contained on one’s Facebook friends list or the frequency of Facebook solicitation while single. Additionally, attachment anxiety predicted Facebook solicitation behaviors, but this relationship was mediated by Facebook jealousy. Our findings confirm that Facebook is used to solicit connections with romantic interests both while single and during committed relationships; however, it is only those connections that are made during the relationship that are markers of lower commitment. Moreover, our study adds to a growing body of research that connects face-to-face relationship theories to the virtual environment. We analyze the dynamics of the behavior known as 'unfollow' in Twitter. We collected daily snapshots of the online relationships of 1.2 million Korean-speaking users for 51 days as well as all of their tweets. We found that Twitter users frequently unfollow. We then discover the major factors, including the reciprocity of the relationships, the duration of a relationship, the followees' informativeness, and the overlap of the relationships, which affect the decision to unfollow. We conduct interview with 22 Korean respondents to supplement the quantitative results. They unfollowed those who left many tweets within a short time, created tweets about uninteresting topics, or tweeted about the mundane details of their lives. To the best of our knowledge, this work is the first systematic study of the unfollow behavior in Twitter. We investigate the breaking of ties between individuals in the online social network of Twitter, a hugely popular social media service. Building on sociology concepts such as strength of ties, embeddedness, and status, we explore how network structure alone influences tie breaks - the common phenomena of an individual ceasing to "follow" another in Twitter's directed social network. We examine these relationships using a dataset of 245,586 Twitter "follow" edges, and the persistence of these edges after nine months. We show that structural properties of individuals and dyads at Time 1 have a significant effect on the existence of edges at Time 2, and connect these findings to the social theories that motivated the study.