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: "a large scale community structure analysis in facebook"
  Abstract: Understanding social dynamics that govern human phenomena, such as communications and social relationships is a major problem in current computational social sciences. In particular, given the unprecedented success of online social networks (OSNs), in this paper we are concerned with the analysis of aggregation patterns and social dynamics occurring among users of the largest OSN as the date: Facebook. In detail, we discuss the mesoscopic features of the community structure of this network, considering the perspective of the communities, which has not yet been studied on such a large scale. To this purpose, we acquired a sample of this network containing millions of users and their social relationships; then, we unveiled the communities representing the aggregation units among which users gather and interact; finally, we analyzed the statistical features of such a network of communities, discovering and characterizing some specific organization patterns followed by individuals interacting in online social networks, that emerge considering different sampling techniques and clustering methodologies. This study provides some clues of the tendency of individuals to establish social interactions in online social networks that eventually contribute to building a well-connected social structure, and opens space for further social studies.

Connected through hyperedge HE-1 (induced by source paper "uncovering complex overlapping pattern of communities in large scale social networks"):
  with members:
    - "community detection algorithm evaluation with ground truth data"
    - "the ground truth about metadata and community detection in networks"
    - "think locally act locally detection of small medium sized and large communities in large networks"
    - "identification of core periphery structure in networks"
    - "efficient detection of communities with significant overlaps in networks partial community merger algorithm"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "graph spectra and the detectability of community structure in networks"
    - "core periphery structure in networks"

Connected through hyperedge HE-2 (induced by source paper "latent space model for multi modal social data"):
  with members:
    - "structure and inference in annotated networks"
    - "analysis of a heterogeneous social network of humans and cultural objects"
    - "quantifying the effect of sentiment on information diffusion in social media"
    - "on facebook most ties are weak"
    - "online popularity and topical interests through the lens of instagram"
    - "the bursty dynamics of the twitter information network"
    - "can cascades be predicted"
    - "traveling trends social butterflies or frequent fliers"

Connected through hyperedge HE-3 (induced by source paper "network generation model based on evolution dynamics to generate benchmark graphs"):
  with members:
    - "communities and hierarchical structures in dynamic social networks analysis and visualization"
    - "social structure of facebook networks"
    - "defining and evaluating network communities based on ground truth"
    - "qualitative comparison of community detection algorithms"
    - "empirical comparison of algorithms for network community detection"
    - "a unified approach to mapping and clustering of bibliometric networks"

Connected through hyperedge HE-4 (induced by source paper "quantifying the effect of sentiment on information diffusion in social media"):
  with members:
    - "the rise of social bots"
    - "measuring emotional contagion in social media"
    - "on predictability of rare events leveraging social media a machine learning perspective"
    - "on facebook most ties are weak"
    - "evolution of online user behavior during a social upheaval"
    - "can cascades be predicted"
    - "romantic partnerships and the dispersion of social ties a network analysis of relationship status on facebook"
    - "predicting successful memes using network and community structure"

Connected through hyperedge HE-5 (induced by source paper "measuring emotional contagion in social media"):
  with members:
    - "on predictability of rare events leveraging social media a machine learning perspective"
    - "the simple rules of social contagion"
    - "quantifying the effect of sentiment on information diffusion in social media"
    - "on facebook most ties are weak"
    - "evolution of online user behavior during a social upheaval"
    - "can cascades be predicted"
    - "romantic partnerships and the dispersion of social ties a network analysis of relationship status on facebook"
    - "the digital evolution of occupy wall street"

Connected through hyperedge HE-6 (induced by source paper "analysis of a heterogeneous social network of humans and cultural objects"):
  with members:
    - "people are strange when you re a stranger impact and influence of bots on social networks"
    - "the digital evolution of occupy wall street"
    - "the geospatial characteristics of a social movement communication network"
    - "analyzing user behavior across social sharing environments"
    - "is the sample good enough comparing data from twitter s streaming api with twitter s firehose"
    - "topological features of online social networks"
    - "crawling facebook for social network analysis purposes"
    - "multidimensional social network in the social recommender system"

Connected through hyperedge HE-7 (induced by source paper "measure the similarity of nodes in the complex networks"):
  with members:
    - "tsallis information dimension of complex networks"
    - "on facebook most ties are weak"
    - "local structure entropy of complex networks"
    - "a new information dimension of complex networks"
    - "traveling trends social butterflies or frequent fliers"
    - "analyzing user behavior across social sharing environments"

Connected through hyperedge HE-8 (induced by source paper "tsallis entropy of complex networks"):
  with members:
    - "tsallis information dimension of complex networks"
    - "on facebook most ties are weak"
    - "a new information dimension of complex networks"
    - "analyzing user behavior across social sharing environments"

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)