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: "collective dynamics of social annotation"
  Abstract: The enormous increase of popularity and use of the worldwide web has led in the recent years to important changes in the ways people communicate. An interesting example of this fact is provided by the now very popular social annotation systems, through which users annotate resources (such as web pages or digital photographs) with keywords known as “tags.” Understanding the rich emergent structures resulting from the uncoordinated actions of users calls for an interdisciplinary effort. In particular concepts borrowed from statistical physics, such as random walks (RWs), and complex networks theory, can effectively contribute to the mathematical modeling of social annotation systems. Here, we show that the process of social annotation can be seen as a collective but uncoordinated exploration of an underlying semantic space, pictured as a graph, through a series of RWs. This modeling framework reproduces several aspects, thus far unexplained, of social annotation, among which are the peculiar growth of the size of the vocabulary used by the community and its complex network structure that represents an externalization of semantic structures grounded in cognition and that are typically hard to access.

Connected through hyperedge HE-1 (induced by source paper "from topic networks to distributed cognitive maps zipfian topic universes in the area of volunteered geographic information"):
  with members:
    - "transfer topic labeling with domain specific knowledge base an analysis of uk house of commons speeches 1935 2014"
    - "extracting and analyzing semantic relatedness between cities using news articles"
    - "bag of tricks for efficient text classification"
    - "semantic similarity from natural language and ontology analysis"
    - "machine learning in automated text categorization"

Connected through hyperedge HE-2 (induced by source paper "modeling and analysis of tagging networks in stack exchange communities"):
  with members:
    - "simplicial closure and higher order link prediction"
    - "choosing to grow a graph modeling network formation as discrete choice"
    - "motifs in temporal networks"
    - "subgraph frequencies mapping the empirical and extremal geography of large graph collections"
    - "who is authoritative understanding reputation mechanisms in quora"
    - "discovering social circles in ego networks"
    - "social structure of facebook networks"
    - "the anatomy of the facebook social graph"

Connected through hyperedge HE-3 (induced by source paper "human collective intelligence as distributed bayesian inference"):
  with members:
    - "the simple rules of social contagion"

Connected through hyperedge HE-4 (induced by source paper "the role of emotional variables in the classification and prediction of collective social dynamics"):
  with members:
    - "negative emotions boost user activity at bbc forum"
    - "twitter mood predicts the stock market"

Connected through hyperedge HE-5 (induced by source paper "extracting tag hierarchies"):
  with members:
    - "a probabilistic approach for learning folksonomies from structured data"
    - "constructing folksonomies from user specified relations on flickr"
    - "tagging folksonomy co renaissance of manual indexing"
    - "collaborative tagging as a tripartite network"
    - "collaborative tagging and semiotic dynamics"

Connected through hyperedge HE-6 (induced by source paper "reuse temporal dynamics interest sharing and collaboration in social tagging systems"):
  with members:
    - "towards a model of understanding social search"
    - "vocabulary growth in collaborative tagging systems"
    - "tracking user attention in collaborative tagging communities"

Connected through hyperedge HE-7 (induced by source paper "theoretical and technological building blocks for an innovation accelerator"):
  with members:
    - "how to create an innovation accelerator"
    - "a meta evaluation of scientific research proposals different ways of comparing rejected to awarded applications"

Connected through hyperedge HE-8 (induced by source paper "tag aware recommender systems a state of the art survey"):
  with members:
    - "bpr bayesian personalized ranking from implicit feedback"
    - "social knowledge based recommender system application to the movies domain"
    - "empirical comparison of algorithms for network community detection"
    - "collaborative filtering with diffusion based similarity on tripartite graphs"
    - "solving the apparent diversity accuracy dilemma of recommender systems"
    - "personalized recommendation via integrated diffusion on user item tag tripartite graphs"
    - "adaptive model for recommendation of news"
    - "collaborative tagging as a tripartite network"

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)