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: "the follower count fallacy detecting twitter users with manipulated follower count"
  Abstract: Online Social Networks (OSN) are increasingly being used as platform for an effective communication, to engage with other users, and to create a social worth via number of likes, followers and shares. Such metrics and crowd-sourced ratings give the OSN user a sense of social reputation which she tries to maintain and boost to be more influential. Users artificially bolster their social reputation via black-market web services. In this work, we identify users which manipulate their projected follower count using an unsupervised local neighborhood detection method. We identify a neighborhood of the user based on a robust set of features which reflect user similarity in terms of the expected follower count. We show that follower count estimation using our method has 84.2% accuracy with a low error rate. In addition, we estimate the follower count of the user under suspicion by finding its neighborhood drawn from a large random sample of Twitter. We show that our method is highly tolerant to synthetic manipulation of followers. Using the deviation of predicted follower count from the displayed count, we are also able to detect customers with a high precision of 98.62%

Connected through hyperedge HE-1 (induced by source paper "retweet us we will retweet you spotting collusive retweeters involved in blackmarket services"):
  with members:
    - "collective classification of spam campaigners on twitter a hierarchical meta path based approach"
    - "the many faces of link fraud"
    - "botornot a system to evaluate social bots"
    - "the rise of social bots"

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)