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: "tweeting the mind and instagramming the heart exploring differentiated content sharing on social media"
  Abstract: Understanding the usage of multiple OSNs (Online Social Networks) has been of significant research interest as it helps in identifying the unique and distinguishing trait in each social media platform that contributes to its continued existence. The comparison between the OSNs is insightful when it is done based on the representative majority of the users holding active accounts on all the platforms. In this research, we collected a set of user profiles holding accounts on both Twitter and Instagram, these platforms being of prominence among a majority of users. An extensive textual and visual analysis on the media content posted by these users revealed that both these platforms are indeed perceived differently at a fundamental level with Instagram engaging more of the users' heart and Twitter capturing more of their mind. These differences got reflected in almost every microscopic analysis done upon the linguistic, topical and visual aspects.

Connected through hyperedge HE-1 (induced by source paper "tweeting ai perceptions of ai tweeters ait vs expert ai tweeters eait"):
  with members:
    - "efficient estimation of word representations in vector space"
    - "mark my words linguistic style accommodation in social media"

Connected through hyperedge HE-2 (induced by source paper "tweeting ai perceptions of lay vs expert twitterati"):
  with members:
    - "efficient estimation of word representations in vector space"
    - "mark my words linguistic style accommodation in social media"

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)