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: "identifying the community roles of social capitalists in the twitter network"
  Abstract: In the context of Twitter, social capitalists are users trying to increase their number of followers and interactions by any means. They are not healthy for the service, because they introduce a bias in the way user influence and visibility are perceived. Understanding their behavior and position in the network is thus of important interest. In this work, we propose to do so by focusing on the community structure level. We first extend an existing method based on the notion of community role, on three different points: 1) handling of directed networks, 2) more precise modeling of the community-related connectivity and 3) unsupervised role identification. We then take advantage of an existing tool to detect social capitalists, and apply our method to analyze their organization and how their links spread across the network. The specific community roles they hold in the network let us know that they reach to obtain high visibility.

Connected through hyperedge HE-1 (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"
    - "quantifying controversy in social media"

Connected through hyperedge HE-2 (induced by source paper "a review of features for the discrimination of twitter users application to the prediction of offline influence"):
  with members:
    - "temporal multinomial mixture for instance oriented evolutionary clustering"
    - "klout score measuring influence across multiple social networks"
    - "detecting real world influence through twitter"
    - "who will retweet this automatically identifying and engaging strangers on twitter to spread information"
    - "understanding types of users on twitter"
    - "artex is another text summarizer"
    - "i wanted to predict elections with twitter and all i got was this lousy paper a balanced survey on election prediction using twitter data"
    - "comparative evaluation of community detection algorithms a topological approach"

Connected through hyperedge HE-3 (induced by source paper "a community role approach to assess social capitalists visibility in the twitter network"):
  with members:
    - "finding overlapping communities in social networks toward a rigorous approach"

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)