In 2015, Reddit closed several subreddits-foremost among them r/fatpeoplehate and r/CoonTown-due to violations of Reddit's anti-harassment policy. However, the effectiveness of banning as a moderation approach remains unclear: banning might diminish hateful behavior, or it may relocate such behavior to different parts of the site. We study the ban of r/fatpeoplehate and r/CoonTown in terms of its effect on both participating users and affected subreddits. Working from over 100M Reddit posts and comments, we generate hate speech lexicons to examine variations in hate speech usage via causal inference methods. We find that the ban worked for Reddit. More accounts than expected discontinued using the site; those that stayed drastically decreased their hate speech usage-by at least 80%. Though many subreddits saw an influx of r/fatpeoplehate and r/CoonTown "migrants," those subreddits saw no significant changes in hate speech usage. In other words, other subreddits did not inherit the problem. We conclude by reflecting on the apparent success of the ban, discussing implications for online moderation, Reddit and internet communities more broadly.

Social media is increasingly being adopted in health discourse. We examine the role played by identity in supporting discourse on socially stigmatized conditions. Specifically, we focus on mental health communities on reddit. We investigate the characteristics of mental health discourse manifested through reddit's characteristic 'throwaway' accounts, which are used as proxies of anonymity. For the purpose, we propose affective, cognitive, social, and linguistic style measures, drawing from literature in psychology. We observe that mental health discourse from throwaways is considerably disinhibiting and exhibits increased negativity, cognitive bias and self-attentional focus, and lowered self-esteem. Throwaways also seem to be six times more prevalent as an identity choice on mental health forums, compared to other reddit communities. We discuss the implications of our work in guiding mental health interventions, and in the design of online communities that can better cater to the needs of vulnerable populations. We conclude with thoughts on the role of identity manifestation on social media in behavioral therapy.

Twitter is often used in quantitative studies that identify geographically-preferred topics, writing styles, and entities. These studies rely on either GPS coordinates attached to individual messages, or on the user-supplied location field in each profile. In this paper, we compare these data acquisition techniques and quantify the biases that they introduce; we also measure their effects on linguistic analysis and textbased geolocation. GPS-tagging and selfreported locations yield measurably different corpora, and these linguistic differences are partially attributable to differences in dataset composition by age and gender. Using a latent variable model to induce age and gender, we show how these demographic variables interact with geography to affect language use. We also show that the accuracy of text-based geolocation varies with population demographics, giving the best results for men above the age of 40.

Many non-standard elements of ‘netspeak’ writing can be viewed as efforts to replicate the linguistic role played by nonverbal modalities in speech, conveying contextual information such as affect and interpersonal stance. Recently, a new non-standard communicative tool has emerged in online writing: emojis. These unicode characters contain a standardized set of pictographs, some of which are visually similar to well-known emoticons. Do emojis play the same linguistic role as emoticons and other ASCII-based writing innovations? If so, might the introduction of emojis eventually displace the earlier, user-created forms of contextual expression? Using a matching approach to causal statistical inference, we show that as social media users adopt emojis, they dramatically reduce their use of emoticons, suggesting that these linguistic resources compete for the same communicative function. Furthermore, we demonstrate that the adoption of emojis leads to a corresponding increase in the use of standard spellings, suggesting that all forms of non-standard writing are losing out in a competition with emojis. Finally, we identify specific textual features that make some emoticons especially likely to be replaced by emojis.

Stylistic variation in online social media writing is well attested: for example, geographical analysis of the social media service twitter has replicated isoglosses for many known lexical variables from speech, while simultaneously revealing a wealth of new geographical lexical variables, including emoticons, phonetic spellings, and phrasal abbreviations. however, less is known about the social role of variation in online writing. this article examines online writing variation in the context of audience design, focusing on affordances offered by twitter that allow users to modulate a message's intended audience. We find that the frequency of nonstandard lexical variables is inversely related to the size of the intended audience: as writers target smaller audiences, the frequency of lexical variables increases. in addition, these variables are more often used in messages that are addressed to individuals who are known to be geographically local. this phenomenon holds not only for geographically differentiated lexical variables, but also for nonstandard variables that are widely used throughout the United States. these findings suggest that users of social media are attuned to both the nature of their audience and the social meaning of lexical variation and that they customize their self-presentation accordingly.