To generate a hypothesis about the effects of anonymity on user participation in online communities, comments on Youtube were analysed for effects of the change from allowing pseudonyms to Google+ with its real name policy. Small differences were detected, leading to the hypothesis that the option to remain anonymous leads to a less active environment for getting feedback, with less polite and less rude comments on the expense of neutral ones.
An important practical work is described by in @cite_7 . An online forum for soldiers gradually changed its account model from anonymity with pseudonyms to full civil identity. analysed the different stages and found that removing anonymity options led to fewer antisocial comments and fewer comments in total. This work heavily influenced our analysis in selecting possible hypotheses.
@cite_7
1979663951 84853486 2138969065 1594207996
In this paper, we analyze a natural experiment regarding anonymity options and participation in a large, successful online community of practice (CoP) for U.S. soldiers. We study the impacts of changes of anonymity options on comment quality for productive discussion and professionalism. Four levels of personal attribution or anonymity of comments are significantly correlated with comment quality under some, but not all, circumstances. Eliminating anonymity options produced significantly fewer antisocial comments and fewer comments overall, although it did not affect overall peripheral participation as measured by logins and page views. Online identity or reputation appears to be more of a factor than external culpability in shaping user behaviors. Attitudes of participants and the evolution of norms over time are presented, and implications for the design of online learning communities are discussed. The use of new technologies along with the popularity of social networks has given the power of anonymity to the users. The ability to create an alter-ego with no relation to the actual user, creates a situation in which no one can certify the match between a profile and a real person. This problem generates situations, repeated daily, in which users with fake accounts, or at least not related to their real identity, publish news, reviews or multimedia material trying to discredit or attack other people who may or may not be aware of the attack. These acts can have great impact on the affected victims’ environment generating situations in which virtual attacks escalate into fatal consequences in real life. In this paper, we present a methodology to detect and associate fake profiles on Twitter social network which are employed for defamatory activities to a real profile within the same network by analysing the content of comments generated by both profiles. Accompanying this approach we also present a successful real life use case in which this methodology was applied to detect and stop a cyberbullying situation in a real elementary school. User contributions in the form of posts, comments, and votes are essential to the success of online communities. However, allowing user participation also invites undesirable behavior such as trolling. In this paper, we characterize antisocial behavior in three large online discussion communities by analyzing users who were banned from these communities. We find that such users tend to concentrate their efforts in a small number of threads, are more likely to post irrelevantly, and are more successful at garnering responses from other users. Studying the evolution of these users from the moment they join a community up to when they get banned, we find that not only do they write worse than other users over time, but they also become increasingly less tolerated by the community. Further, we discover that antisocial behavior is exacerbated when community feedback is overly harsh. Our analysis also reveals distinct groups of users with different levels of antisocial behavior that can change over time. We use these insights to identify antisocial users early on, a task of high practical importance to community maintainers. We present two studies of online ephemerality and anonymity based on the popular discussion board b at 4chan.org: a website with over 7 million users that plays an influential role in Internet culture. Although researchers and practitioners often assume that user identity and data permanence are central tools in the design of online communities, we explore how b succeeds despite being almost entirely anonymous and extremely ephemeral. We begin by describing b and performing a content analysis that suggests the community is dominated by playful exchanges of images and links. Our first study uses a large dataset of more than five million posts to quantify ephemerality in b . We find that most threads spend just five seconds on the first page and less than five minutes on the site before expiring. Our second study is an analysis of identity signals on 4chan, finding that over 90 of posts are made by fully anonymous users, with other identity signals adopted and discarded at will. We describe alternative mechanisms that b participants use to establish status and frame their interactions.