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: "collaborative tagging and semiotic dynamics"
  Abstract: Collaborative tagging has been quickly gaining ground because of its ability to recruit the activity of web users into effectively organizing and sharing vast amounts of information. Here we collect data from a popular system and investigate the statistical properties of tag co-occurrence. We introduce a stochastic model of user behavior embodying two main aspects of collaborative tagging: (i) a frequency-bias mechanism related to the idea that users are exposed to each other's tagging activity; (ii) a notion of memory - or aging of resources - in the form of a heavy-tailed access to the past state of the system. Remarkably, our simple modeling is able to account quantitatively for the observed experimental features, with a surprisingly high accuracy. This points in the direction of a universal behavior of users, who - despite the complexity of their own cognitive processes and the uncoordinated and selfish nature of their tagging activity - appear to follow simple activity patterns.

Connected through hyperedge HE-1 (induced by source paper "a standardized project gutenberg corpus for statistical analysis of natural language and quantitative linguistics"):
  with members:
    - "natural language statistical features of lstm generated texts"
    - "mapping the americanization of english in space and time"
    - "in narrative texts punctuation marks obey the same statistics as words"
    - "quantifying structure differences in literature using symbolic diversity and entropy criteria"
    - "the emotional arcs of stories are dominated by six basic shapes"
    - "text mixing shapes the anatomy of rank frequency distributions"
    - "rank diversity of languages generic behavior in computational linguistics"
    - "a practical approach to language complexity a wikipedia case study"

Connected through hyperedge HE-2 (induced by source paper "extracting tag hierarchies"):
  with members:
    - "a probabilistic approach for learning folksonomies from structured data"
    - "collective dynamics of social annotation"
    - "constructing folksonomies from user specified relations on flickr"
    - "tagging folksonomy co renaissance of manual indexing"
    - "collaborative tagging as a tripartite network"

Connected through hyperedge HE-3 (induced by source paper "how web 1 0 fails the mismatch between hyperlinks and clickstreams"):
  with members:
    - "agents bookmarks and clicks a topical model of web navigation"
    - "novelty and collective attention"

Connected through hyperedge HE-4 (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"
    - "collective dynamics of social annotation"
    - "adaptive model for recommendation of news"

Connected through hyperedge HE-5 (induced by source paper "niche as a determinant of word fate in online groups"):
  with members:
    - "folks in folksonomies social link prediction from shared metadata"
    - "using a model of social dynamics to predict popularity of news"
    - "beyond word frequency bursts lulls and scaling in the temporal distributions of words"
    - "collective dynamics of social annotation"
    - "predicting the popularity of online content"
    - "topical interests and the mitigation of search engine bias"

Connected through hyperedge HE-6 (induced by source paper "solving the apparent diversity accuracy dilemma of recommender systems"):
  with members:
    - "personalized recommendation via integrated diffusion on user item tag tripartite graphs"

Connected through hyperedge HE-7 (induced by source paper "personalized recommendation via integrated diffusion on user item tag tripartite graphs"):
  with members:
    - "improved collaborative filtering algorithm via information transformation"

Connected through hyperedge HE-8 (induced by source paper "collective dynamics of social annotation"):
  with members:
    - "semantic analysis of tag similarity measures in collaborative tagging systems"
    - "vocabulary growth in collaborative tagging systems"
    - "systematic topology analysis and generation using degree correlations"
    - "the structure of collaborative tagging systems"

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)