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: "birds of a feather does user homophily impact information diffusion in social media"
  Abstract: This article investigates the impact of user homophily on the social process of information diffusion in online social media. Over several decades, social scientists have been interested in the idea that similarity breeds connection: precisely known as "homophily". Homophily has been extensively studied in the social sciences and refers to the idea that users in a social system tend to bond more with ones who are similar to them than to ones who are dissimilar. The key observation is that homophily structures the ego-networks of individuals and impacts their communication behavior. It is therefore likely to effect the mechanisms in which information propagates among them. To this effect, we investigate the interplay between homophily along diverse user attributes and the information diffusion process on social media. In our approach, we first extract diffusion characteristics---corresponding to the baseline social graph as well as graphs filtered on different user attributes (e.g. location, activity). Second, we propose a Dynamic Bayesian Network based framework to predict diffusion characteristics at a future time. Third, the impact of attribute homophily is quantified by the ability of the predicted characteristics in explaining actual diffusion, and external variables, including trends in search and news. Experimental results on a large Twitter dataset demonstrate that choice of the homophilous attribute can impact the prediction of information diffusion, given a specific metric and a topic. In most cases, attribute homophily is able to explain the actual diffusion and external trends by ~15-25% over cases when homophily is not considered.

Connected through hyperedge HE-1 (induced by source paper "literature survey on interplay of topics information diffusion and connections on social networks"):
  with members:
    - "analysis and forecasting of trending topics in online media streams"
    - "the role of social networks in information diffusion"
    - "defining and evaluating network communities based on ground truth"
    - "user level sentiment analysis incorporating social networks"
    - "spatio temporal analysis of topic popularity in twitter"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"
    - "de anonymizing social networks"
    - "a model of internet topology using k shell decomposition"

Connected through hyperedge HE-2 (induced by source paper "u s religious landscape on twitter"):
  with members:
    - "friendship paradox redux your friends are more interesting than you"
    - "measuring the happiness of large scale written expression songs blogs and presidents"
    - "sabbath day home automation it s like mixing technology and religion"

Connected through hyperedge HE-3 (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"
    - "what trends in chinese social media"

Connected through hyperedge HE-4 (induced by source paper "nepotistic relationships in twitter and their impact on rank prestige algorithms"):
  with members:
    - "de retibus socialibus et legibus momenti"
    - "influence and passivity in social media"
    - "social networks that matter twitter under the microscope"

Connected through hyperedge HE-5 (induced by source paper "cross pollination of information in online social media a case study on popular social networks"):
  with members:
    - "predicting the popularity of online content"

Connected through hyperedge HE-6 (induced by source paper "using proximity to predict activity in social networks"):
  with members:
    - "what stops social epidemics"
    - "non conservative diffusion and its application to social network analysis"
    - "a probabilistic approach for learning folksonomies from structured data"
    - "stochastic models of user contributory web sites"
    - "novelty and collective attention"
    - "social information processing in news aggregation"
    - "social browsing on flickr"
    - "social networks and social information filtering on digg"

Connected through hyperedge HE-7 (induced by source paper "a framework for quantitative analysis of cascades on networks"):
  with members:
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"
    - "centrality metric for dynamic networks"
    - "analysis of social voting patterns on digg"

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)