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: "quantifying controversy in social media"
  Abstract: Which topics spark the most heated debates on social media? Identifying those topics is not only interesting from a societal point of view, but also allows the filtering and aggregation of social media content for disseminating news stories. In this paper, we perform a systematic methodological study of controversy detection by using the content and the network structure of social media. #R##N#Unlike previous work, rather than study controversy in a single hand-picked topic and use domain specific knowledge, we take a general approach to study topics in any domain. Our approach to quantifying controversy is based on a graph-based three-stage pipeline, which involves (i) building a conversation graph about a topic; (ii) partitioning the conversation graph to identify potential sides of the controversy; and (iii) measuring the amount of controversy from characteristics of the graph. #R##N#We perform an extensive comparison of controversy measures, different graph-building approaches, and data sources. We use both controversial and non-controversial topics on Twitter, as well as other external datasets. We find that our new random-walk-based measure outperforms existing ones in capturing the intuitive notion of controversy, and show that content features are vastly less helpful in this task.

Connected through hyperedge HE-1 (induced by source paper "language in our time an empirical analysis of hashtags"):
  with members:
    - "network embedding as matrix factorization unifying deepwalk line pte and node2vec"
    - "tagvisor a privacy advisor for sharing hashtags"
    - "hierarchical graph representation learning with differentiable pooling"
    - "you are your metadata identification and obfuscation of social media users using metadata information"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "ml leaks model and data independent membership inference attacks and defenses on machine learning models"
    - "twitter for sparking a movement reddit for sharing the moment metoo through the lens of social media"
    - "is saki delicious the food perception gap on instagram and its relation to health"

Connected through hyperedge HE-2 (induced by source paper "predicting the role of political trolls in social media"):
  with members:
    - "hunting for troll comments in news community forums"
    - "in search of credible news"
    - "semeval 2019 task 8 fact checking in community question answering forums"
    - "claimrank detecting check worthy claims in arabic and english"
    - "political discourse on social media echo chambers gatekeepers and the price of bipartisanship"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "fact checking in community forums"
    - "an army of me sockpuppets in online discussion communities"

Connected through hyperedge HE-3 (induced by source paper "conversational networks for automatic online moderation"):
  with members:
    - "impact of content features for automatic online abuse detection"
    - "one step and two step classification for abusive language detection on twitter"
    - "deceiving google s perspective api built for detecting toxic comments"
    - "graph based features for automatic online abuse detection"
    - "deep learning for user comment moderation"
    - "a community role approach to assess social capitalists visibility in the twitter network"
    - "antisocial behavior in online discussion communities"
    - "identifying the community roles of social capitalists in the twitter network"

Connected through hyperedge HE-4 (induced by source paper "community interaction and conflict on the web"):
  with members:
    - "false information on web and social media a survey"
    - "community identity and user engagement in a multi community landscape"
    - "an army of me sockpuppets in online discussion communities"
    - "contagion dynamics of extremist propaganda in social networks"
    - "representation learning on graphs methods and applications"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "everything i disagree with is fakenews correlating political polarization and spread of misinformation"
    - "loyalty in online communities"

Connected through hyperedge HE-5 (induced by source paper "polarization and fake news early warning of potential misinformation targets"):
  with members:
    - "polarization of the vaccination debate on facebook"
    - "misinformation spreading on facebook"
    - "it s always april fools day on the difficulty of social network misinformation classification via propagation features"
    - "leveraging the crowd to detect and reduce the spread of fake news and misinformation"
    - "fake news detection on social media a data mining perspective"
    - "automatically identifying fake news in popular twitter threads"
    - "tweet acts a speech act classifier for twitter"
    - "debunking in a world of tribes"

Connected through hyperedge HE-6 (induced by source paper "political discourse on social media echo chambers gatekeepers and the price of bipartisanship"):
  with members:
    - "balancing information exposure in social networks"
    - "the effect of collective attention on controversial debates on social media"
    - "a long term analysis of polarization on twitter"
    - "limited individual attention and online virality of low quality information"
    - "reducing controversy by connecting opposing views"
    - "partisan sharing facebook evidence and societal consequences"

Connected through hyperedge HE-7 (induced by source paper "tell me something my friends do not know diversity maximization in social networks"):
  with members:
    - "minimizing polarization and disagreement in social networks"
    - "balancing information exposure in social networks"
    - "joint non negative matrix factorization for learning ideological leaning on twitter"
    - "users polarization on facebook and youtube"
    - "reducing controversy by connecting opposing views"

Connected through hyperedge HE-8 (induced by source paper "viewpoint discovery and understanding in social networks"):
  with members:
    - "actionable and political text classification using word embeddings and lstm"
    - "societal controversies in wikipedia articles"
    - "controversy and sentiment in online news"

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)