human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "how community feedback shapes user behavior"
  Abstract: Social media systems rely on user feedback and rating mechanisms for personalization, ranking, and content filtering. However, when users evaluate content contributed by fellow users (e.g., by liking a post or voting on a comment), these evaluations create complex social feedback effects. This paper investigates how ratings on a piece of content affect its author's future behavior. By studying four large comment-based news communities, we find that negative feedback leads to significant behavioral changes that are detrimental to the community. Not only do authors of negatively-evaluated content contribute more, but also their future posts are of lower quality, and are perceived by the community as such. Moreover, these authors are more likely to subsequently evaluate their fellow users negatively, percolating these effects through the community. In contrast, positive feedback does not carry similar effects, and neither encourages rewarded authors to write more, nor improves the quality of their posts. Interestingly, the authors that receive no feedback are most likely to leave a community. Furthermore, a structural analysis of the voter network reveals that evaluations polarize the community the most when positive and negative votes are equally split.

Connected through hyperedge HE-1 (induced by source paper "trajectories of blocked community members redemption recidivism and departure"):
  with members:
    - "mind your pov convergence of articles and editors towards wikipedia s neutrality norm"
    - "forecasting the presence and intensity of hostility on instagram using linguistic and social features"
    - "the effect of extremist violence on hateful speech online"
    - "community interaction and conflict on the web"
    - "wikiconv a corpus of the complete conversational history of a large online collaborative community"
    - "the view from the other side the border between controversial speech and harassment on kotaku in action"
    - "conversations gone awry detecting early signs of conversational failure"
    - "characterizing and detecting hateful users on twitter"

Connected through hyperedge HE-2 (induced by source paper "content removal as a moderation strategy compliance and other outcomes in the changemyview community"):
  with members:
    - "trajectories of blocked community members redemption recidivism and departure"
    - "trouble on the horizon forecasting the derailment of online conversations as they develop"
    - "mind your pov convergence of articles and editors towards wikipedia s neutrality norm"
    - "forecasting the presence and intensity of hostility on instagram using linguistic and social features"
    - "reducing gender bias in abusive language detection"
    - "conversations gone awry detecting early signs of conversational failure"
    - "a warm welcome matters the link between social feedback and weight loss in r loseit"
    - "measuring offensive speech in online political discourse"

Connected through hyperedge HE-3 (induced by source paper "are all successful communities alike characterizing and predicting the success of online communities"):
  with members:
    - "network structure efficiency and performance in wikiprojects"
    - "tracing community genealogy how new communities emerge from the old"
    - "caveat emptor computational social science large scale missing data in a widely published reddit corpus"
    - "a warm welcome matters the link between social feedback and weight loss in r loseit"
    - "loyalty in online communities"
    - "social networks under stress"
    - "the effect of social feedback in a reddit weight loss community"
    - "all who wander on the prevalence and characteristics of multi community engagement"

Connected through hyperedge HE-4 (induced by source paper "intergroup contact in the wild characterizing language differences between intergroup and single group members in nba related discussion forums"):
  with members:
    - "this is why we play characterizing online fan communities of the nba teams"
    - "community interaction and conflict on the web"
    - "extracting inter community conflicts in reddit"
    - "me my echo chamber and i introspection on social media polarization"
    - "automated hate speech detection and the problem of offensive language"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "all who wander on the prevalence and characteristics of multi community engagement"
    - "antisocial behavior in online discussion communities"

Connected through hyperedge HE-5 (induced by source paper "sentiment dynamics in social media news channels"):
  with members:
    - "automated hate speech detection and the problem of offensive language"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "breaking the news first impressions matter on online news"
    - "characterizing the life cycle of online news stories using social media reactions"
    - "the pulse of news in social media forecasting popularity"
    - "good friends bad news affect and virality in twitter"
    - "using a model of social dynamics to predict popularity of news"
    - "predicting the popularity of online content"

Connected through hyperedge HE-6 (induced by source paper "can a user guess what her followers want"):
  with members:
    - "steering social activity a stochastic optimal control point of view"
    - "smart broadcasting do you want to be seen"
    - "when to post on social networks"
    - "learning economic parameters from revealed preferences"
    - "further optimal regret bounds for thompson sampling"
    - "efficiently learning from revealed preference"
    - "thompson sampling for contextual bandits with linear payoffs"

Connected through hyperedge HE-7 (induced by source paper "can a user anticipate what her followers want"):
  with members:
    - "steering social activity a stochastic optimal control point of view"
    - "when to post on social networks"
    - "learning economic parameters from revealed preferences"
    - "further optimal regret bounds for thompson sampling"
    - "efficiently learning from revealed preference"
    - "thompson sampling for contextual bandits with linear payoffs"

Connected through hyperedge HE-8 (induced by source paper "the wisdom of polarized crowds"):
  with members:
    - "ex machina personal attacks seen at scale"
    - "antisocial behavior in online discussion communities"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SI(Social and Information Networks)