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: "mytweet via instagram exploring user behaviour across multiple social networks"
  Abstract: We study how users of multiple online social networks (OSNs) employ and share information by studying a common user pool that use six OSNs -- Flickr, Google+, Instagram, Tumblr, Twitter, and YouTube. We analyze the temporal and topical signature of users' sharing behaviour, showing how they exhibit distinct behaviorial patterns on different networks. We also examine cross-sharing (i.e., the act of user broadcasting their activity to multiple OSNs near-simultaneously), a previously-unstudied behaviour and demonstrate how certain OSNs play the roles of originating source and destination sinks.

Connected through hyperedge HE-1 (induced by source paper "how impersonators exploit instagram to generate fake engagement"):
  with members:
    - "netspam a network based spam detection framework for reviews in online social media"
    - "in a world that counts clustering and detecting fake social engagement at scale"
    - "the rise of social bots"
    - "on the reliability of profile matching across large online social networks"
    - "a new anew evaluation of a word list for sentiment analysis in microblogs"

Connected through hyperedge HE-2 (induced by source paper "wearing many social hats how different are your different social network personae"):
  with members:
    - "caffe convolutional architecture for fast feature embedding"
    - "social bootstrapping how pinterest and last fm social communities benefit by borrowing links from facebook"
    - "big questions for social media big data representativeness validity and other methodological pitfalls"
    - "decaf a deep convolutional activation feature for generic visual recognition"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-3 (induced by source paper "characterization of cross posting activity for professional users across facebook twitter and google"):
  with members:
    - "social bootstrapping how pinterest and last fm social communities benefit by borrowing links from facebook"
    - "google or google dissecting the evolution of the new osn in its first year"
    - "the anatomy of the facebook social graph"
    - "four degrees of separation"

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)