The anatomy of Reddit: An overview of academic research <s> From the perspective of users <s> We introduce and validate a learning model of human behavior change in response to feedback on social media. People who participate in these types of websites, like Wikipedia, Reddit, and others, are learning agents whose choices about how to allocate their effort are dynamic and responsive to how they feel their efforts were received in the past. By explicitly taking into account the reinforcement effects of different types of feedback received on prior contributions, our model is able to significantly outperform all known baselines in predicting future contributions both on synthetic data and on real data collected from the social news site reddit.com. Our model has an intuitive interpretation as users playing mixed strategies in a game-like setting with thousands of other users and thousands of available pure strategies. In this interpretation, our task is then inverse reinforcement learning: recovering users' reward functions based on observed behavior. <s> BIB001 </s> The anatomy of Reddit: An overview of academic research <s> From the perspective of users <s> Session identification is a common strategy used to develop metrics for web analytics and perform behavioral analyses of user-facing systems. Past work has argued that session identification strategies based on an inactivity threshold is inherently arbitrary or has advocated that thresholds be set at about 30 minutes. In this work, we demonstrate a strong regularity in the temporal rhythms of user initiated events across several different domains of online activity (incl. video gaming, search, page views and volunteer contributions). We describe a methodology for identifying clusters of user activity and argue that the regularity with which these activity clusters appear implies a good rule-of-thumb inactivity threshold of about 1 hour. We conclude with implications that these temporal rhythms may have for system design based on our observations and theories of goal-directed human activity. <s> BIB002 </s> The anatomy of Reddit: An overview of academic research <s> From the perspective of users <s> Although analyzing user behavior within individual communities is an active and rich research domain, people usually interact with multiple communities both on- and off-line. How do users act in such multi-community environments? Although there are a host of intriguing aspects to this question, it has received much less attention in the research community in comparison to the intra-community case. In this paper, we examine three aspects of multi-community engagement: the sequence of communities that users post to, the language that users employ in those communities, and the feedback that users receive, using longitudinal posting behavior on Reddit as our main data source, and DBLP for auxiliary experiments. We also demonstrate the effectiveness of features drawn from these aspects in predicting users' future level of activity. One might expect that a user's trajectory mimics the "settling-down" process in real life: an initial exploration of sub-communities before settling down into a few niches. However, we find that the users in our data continually post in new communities; moreover, as time goes on, they post increasingly evenly among a more diverse set of smaller communities. Interestingly, it seems that users that eventually leave the community are "destined" to do so from the very beginning, in the sense of showing significantly different "wandering" patterns very early on in their trajectories; this finding has potentially important design implications for community maintainers. Our multi-community perspective also allows us to investigate the "situation vs. personality" debate from language usage across different communities. <s> BIB003 </s> The anatomy of Reddit: An overview of academic research <s> From the perspective of users <s> This article presents evidence of performance deterioration in online user sessions quantified by studying a massive dataset containing over 55 million comments posted on Reddit in April 2015. After segmenting the sessions (i.e., periods of activity without a prolonged break) depending on their intensity (i.e., how many posts users produced during sessions), we observe a general decrease in the quality of comments produced by users over the course of sessions. We propose mixed-effects models that capture the impact of session intensity on comments, including their length, quality, and the responses they generate from the community. Our findings suggest performance deterioration: Sessions of increasing intensity are associated with the production of shorter, progressively less complex comments, which receive declining quality scores (as rated by other users), and are less and less engaging (i.e., they attract fewer responses). Our contribution evokes a connection between cognitive and attention dynamics and the usage of online social peer production platforms, specifically the effects of deterioration of user performance. <s> BIB004 </s> The anatomy of Reddit: An overview of academic research <s> From the perspective of users <s> When large social-media platforms allow users to easily form and self-organize into interest groups, highly related communities can arise. For example, the Reddit site hosts not just a group called food, but also HealthyFood, foodhacks, foodporn, and cooking, among others. Are these highly related communities created for similar classes of reasons (e.g., true to distinguish one as a better community and advice to focus on helping fellow members)? How do users allocate attention between such close alternatives when they are available or emerge over time? Are there different types of relations between close alternatives such as sharing many users vs. a new community drawing away members of an older one vs. a splinter group failing to cohere into a viable separate community? We investigate the interactions between highly related communities using data from reddit.com consisting of 975M posts and comments spanning an 8-year period. We identify a set of typical affixes that users adopt to create highly related communities and build a taxonomy of affixes. One interesting finding regarding users’ behavior is: after a newer community is created, for several types of highly-related community pairs, users that engage in a newer community tend to be more active in their original community than users that do not explore, even when controlling for previous level of engagement. <s> BIB005 </s> The anatomy of Reddit: An overview of academic research <s> From the perspective of users <s> As crowd-sourced curation of news and information become the norm, it is important to understand not only how individuals consume information through social news Web sites, but also how they contribute to their ranking systems. In this paper, we introduce and make available a new data set containing the activity logs that recorded all activity for 309 Reddit users for one year. Using this newly collected data, we present findings that highlight the browsing and voting behavior of the study’s participants. We find that most users do not read the article that they vote on, and that, in total, 73% of posts were rated (i.e., upvoted or downvoted) without first viewing the content. We also show the evidence of cognitive fatigue in the browsing sessions of users that are most likely to vote. <s> BIB006 </s> The anatomy of Reddit: An overview of academic research <s> From the perspective of users <s> In order to keep up with the demand of curating the deluge of crowd-sourced content, social media platforms leverage user interaction feedback to make decisions about which content to display, highlight, and hide. User interactions such as likes, votes, clicks, and views are assumed to be a proxy of a content's quality, popularity, or news-worthiness. In this paper we ask: how predictable are the interactions of a user on social media? To answer this question we recorded the clicking, browsing, and voting behavior of 186 Reddit users over a year. We present interesting descriptive statistics about their combined 339,270 interactions, and we find that relatively simple models are able to predict users' individual browse- or vote-interactions with reasonable accuracy. <s> BIB007 </s> The anatomy of Reddit: An overview of academic research <s> From the perspective of users <s> Loyalty is an essential component of multi-community engagement. When users have the choice to engage with a variety of different communities, they often become loyal to just one, focusing on that community at the expense of others. However, it is unclear how loyalty is manifested in user behavior, or whether loyalty is encouraged by certain community characteristics. ::: In this paper we operationalize loyalty as a user-community relation: users loyal to a community consistently prefer it over all others; loyal communities retain their loyal users over time. By exploring this relation using a large dataset of discussion communities from Reddit, we reveal that loyalty is manifested in remarkably consistent behaviors across a wide spectrum of communities. Loyal users employ language that signals collective identity and engage with more esoteric, less popular content, indicating they may play a curational role in surfacing new material. Loyal communities have denser user-user interaction networks and lower rates of triadic closure, suggesting that community-level loyalty is associated with more cohesive interactions and less fragmentation into subgroups. We exploit these general patterns to predict future rates of loyalty. Our results show that a user's propensity to become loyal is apparent from their first interactions with a community, suggesting that some users are intrinsically loyal from the very beginning. <s> BIB008 </s> The anatomy of Reddit: An overview of academic research <s> From the perspective of users <s> A community's identity defines and shapes its internal dynamics. Our current understanding of this interplay is mostly limited to glimpses gathered from isolated studies of individual communities. In this work we provide a systematic exploration of the nature of this relation across a wide variety of online communities. To this end we introduce a quantitative, language-based typology reflecting two key aspects of a community's identity: how distinctive, and how temporally dynamic it is. By mapping almost 300 Reddit communities into the landscape induced by this typology, we reveal regularities in how patterns of user engagement vary with the characteristics of a community. ::: Our results suggest that the way new and existing users engage with a community depends strongly and systematically on the nature of the collective identity it fosters, in ways that are highly consequential to community maintainers. For example, communities with distinctive and highly dynamic identities are more likely to retain their users. However, such niche communities also exhibit much larger acculturation gaps between existing users and newcomers, which potentially hinder the integration of the latter. ::: More generally, our methodology reveals differences in how various social phenomena manifest across communities, and shows that structuring the multi-community landscape can lead to a better understanding of the systematic nature of this diversity. <s> BIB009
So far we emphasised the posts as the central pieces of information driving the dynamics of the platform. We now focus on the person that hides behind each post, comment, like or dislike, and review studies on the behavioral features of users. Activity patterns. Observing the actions of users on a website can lead to interesting conclusions. Glenski et al. BIB006 BIB007 have studied a dataset with all recorded activity of 309 Reddit users within one year. The activity log included the information on all clicks, pageloads and votes made within the REDDIT.COM domain. As expected, the majority of users prefer passive browsing and rarely interact with the content (only 16% of users produce more than 50% of interactions). Users mostly vote on posts on average after only browsing the title (73 % of posts), although a non-negligible fraction (17%) of participants follow the link of the post and browse the section of comments before giving a vote. It was noted that users' probability of interaction with a given post decreases with the ranking of the post on the top page of Reddit as well as on subreddits. Text analysis of post titles shows that the probability of interaction increases with the reading ease of the title, i.e. as they use shorter words, and smaller sentences. The authors used the concept of activity sessions, which are the periods of user activity starting from an interaction and finishing after 1 hour without consecutive interactions. This terminology and a 1-hour threshold were adopted from Halfhaker et al. BIB002 and Singer et al. BIB004 . The authors reported a mean session length of 53 minutes. However, most participants had much shorter sessions prevailing (>3 mins). Singer et al. BIB004 also studied performance deterioration within sessions of active commenting on Reddit, where sessions of increasing intensity, i.e. how many posts users produced during sessions, are associated with the production of shorter, progressively less complex comments, which receive declining score. In this work, the authors found a similar prevalence of short sessions, and sessions presented a daily circadian rhythms. Community loyalty. While some of the previous results also applied to other online platforms, this section is devoted specifically to Reddit, a platform where the content is by default submitted to thematic communities, or subreddits. These subreddits are in principle open to anyone, but users can follow particular subreddits of their interest in order to customizing their feed. Interestingly, subreddit sizes are close to have heavy-tailed distribution, and there exists a fraction of subredditsoutliers with a huge number of subscribers 5. Looking closer at those we find that many of these "top" subreddits are those which are proposed to sign up for by default at the registration of a new user. Tan and Lee BIB003 studied the posts of users across the subreddits and found that users on average tend to explore and continuously post in new communities, moreover they tend over time to share their activity evenly between a small number of communities with diverse interests. Differences in posting patterns of users may be used for prediction of the users' future settlement status in a community. Vagrant users, on average, post to more similar communities in comparison with the settling users, they use different language patterns from those existing in a community and their posts receive less attention in terms of score. Score of the first post may generally act as a predictor of further postings. The posting activity rate alone showed to be a bad predictor of the future settlement status in a community. An interesting finding is that the very same users tend to use different vocabulary when posting in different communities, therefore adapting to the community language. Hamilton et al. BIB008 defined loyal communities as the ones that retain their loyal users over time and find that such communities have smaller, but denser user interaction networkswith users as nodes, connected if there is a reply-to comment between them. These networks were found to be less assortative and less clustered, and thus show less fragmentation into groups. The authors then predicted whether a user will be loyal to the community, using a machine learning classifier with linguistic features of user's posts and comments, and achieve on average 63.6% classification accuracy. Reddit allows users to self-organize into interest communities, which leads to interesting dynamics of communities. Hessel et al. BIB005 Zhang et al. BIB009 Classify subreddits along "niche" and "volatile" dimensions, study user retention Reddit, dataset  Statistical analysis Das and Lavoie BIB001 Model users posting strategies with respect to community feedback