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: "what trends in chinese social media"
  Abstract: There has been a tremendous rise in the growth of online social networks all over the world in recent times. While some networks like Twitter and Facebook have been well documented, the popular Chinese microblogging social network Sina Weibo has not been studied. In this work, we examine the key topics that trend on Sina Weibo and contrast them with our observations on Twitter. We nd that there is a vast dierence in the content shared in China, when compared to a global social network such as Twitter. In China, the trends are created almost entirely due to retweets of media content such as jokes, images and videos, whereas on Twitter, the trends tend to have more to do with current global events and news stories.

Connected through hyperedge HE-1 (induced by source paper "a model for meme popularity growth in social networking systems based on biological principle and human interest dynamics"):
  with members:
    - "limited individual attention and online virality of low quality information"
    - "local variation of hashtag spike trains and popularity in twitter"
    - "seismic a self exciting point process model for predicting tweet popularity"
    - "inheritance patterns in citation networks reveal scientific memes"
    - "rising tides or rising stars dynamics of shared attention on twitter during media events"
    - "a bayesian approach for predicting the popularity of tweets"
    - "dynamical classes of collective attention in twitter"
    - "agents bookmarks and clicks a topical model of web navigation"

Connected through hyperedge HE-2 (induced by source paper "online social network analysis a survey of research applications in computer science"):
  with members:
    - "inheritance patterns in citation networks reveal scientific memes"
    - "who will retweet this automatically identifying and engaging strangers on twitter to spread information"
    - "networkit an interactive tool suite for high performance network analysis"
    - "networkit a tool suite for large scale complex network analysis"
    - "can cascades be predicted"
    - "exploring image virality in google plus"
    - "popularity prediction in microblogging network a case study on sina weibo"
    - "a scalable heuristic for viral marketing under the tipping model"

Connected through hyperedge HE-3 (induced by source paper "word network topic model a simple but general solution for short and imbalanced texts"):
  with members:
    - "dynamics of trends and attention in chinese social media"
    - "a practical algorithm for topic modeling with provable guarantees"
    - "the author topic model for authors and documents"

Connected through hyperedge HE-4 (induced by source paper "analyzing user behavior of the micro blogging website sina weibo during hot social events"):
  with members:
    - "what is the nature of chinese microblogging unveiling the unique features of tencent weibo"
    - "follow whom chinese users have different choice"

Connected through hyperedge HE-5 (induced by source paper "what are chinese talking about in hot weibos"):
  with members:
    - "analyzing user behavior of the micro blogging website sina weibo during hot social events"
    - "what is the nature of chinese microblogging unveiling the unique features of tencent weibo"
    - "follow whom chinese users have different choice"
    - "birds of a feather does user homophily impact information diffusion in social media"

Connected through hyperedge HE-6 (induced by source paper "a pointillism approach for natural language processing of social media"):
  with members:
    - "trends in social media persistence and decay"

Connected through hyperedge HE-7 (induced by source paper "artificial inflation the true story of trends in sina weibo"):
  with members:
    - "trends in social media persistence and decay"

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.CY(Computers and Society)