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: "who is authoritative understanding reputation mechanisms in quora"
  Abstract: As social Q&A sites gain popularity, it is important to understand how users judge the authoritativeness of users and content, build reputation, and identify and promote high quality content. We conducted a study of emerging social Q&A site Quora. First, we describe user activity on Quora by analyzing data across 60 question topics and 3917 users. Then we provide a rich understanding of issues of authority, reputation, and quality from in-depth interviews with ten Quora users. Our results show that primary sources of information on Quora are judged authoritative. Also, users judge the reputation of other users based on their past contributions. Social voting helps users identify and promote good content but is prone to preferential attachment. Combining social voting with sophisticated algorithms for ranking content might enable users to better judge others’ reputation and promote high quality content.

Connected through hyperedge HE-1 (induced by source paper "quantifying voter biases in online platforms an instrumental variable approach"):
  with members:
    - "quantifying the impact of cognitive biases in question answering systems"
    - "the size conundrum why online knowledge markets can fail at scale"
    - "guessthekarma a game to assess social rating systems"
    - "when sheep shop measuring herding effects in product ratings with natural experiments"
    - "caveat emptor computational social science large scale missing data in a widely published reddit corpus"
    - "consumers and curators browsing and voting patterns on reddit"
    - "rating effects on social news posts and comments"
    - "unbiased learning to rank with biased feedback"

Connected through hyperedge HE-2 (induced by source paper "competing topic naming conventions in quora predicting appropriate topic merges and winning topics from millions of topic pairs"):
  with members:
    - "universal sentence encoder"
    - "deep dive into anonymity a large scale analysis of quora questions"
    - "language use matters analysis of the linguistic structure of question texts can characterize answerability in quora"
    - "competition and selection among conventions"
    - "bieber blast bieberblast early prediction of popular hashtag compounds"
    - "analysis of named entity recognition and linking for tweets"
    - "distributed representations of sentences and documents"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-3 (induced by source paper "modeling and analysis of tagging networks in stack exchange communities"):
  with members:
    - "simplicial closure and higher order link prediction"
    - "choosing to grow a graph modeling network formation as discrete choice"
    - "motifs in temporal networks"
    - "subgraph frequencies mapping the empirical and extremal geography of large graph collections"
    - "discovering social circles in ego networks"
    - "social structure of facebook networks"
    - "the anatomy of the facebook social graph"
    - "collective dynamics of social annotation"

Connected through hyperedge HE-4 (induced by source paper "data driven approach for quality evaluation on knowledge sharing platform"):
  with members:
    - "deep learning for sentiment analysis a survey"
    - "going deeper with convolutions"

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)