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: "human dynamics revealed through web analytics"
  Abstract: The increasing ubiquity of Internet access and the frequency with which people interact with it raise the possibility of using the Web to better observe, understand, and monitor several aspects of human social behavior. Web sites with large numbers of frequently returning users are ideal for this task. If these sites belong to companies or universities, their usage patterns can furnish information about the working habits of entire populations. In this work, we analyze the properly anonymized logs detailing the access history to Emory University's Web site. Emory is a medium-sized university located in Atlanta, Georgia. We find interesting structure in the activity patterns of the domain and study in a systematic way the main forces behind the dynamics of the traffic. In particular, we find that linear preferential linking, priority-based queuing, and the decay of interest for the contents of the pages are the essential ingredients to understand the way users navigate the Web.

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"
    - "what trends in chinese social media"

Connected through hyperedge HE-2 (induced by source paper "seasonal stochastic blockmodeling for anomaly detection in dynamic networks"):
  with members:
    - "seasonality in dynamic stochastic block models"
    - "stochastic block transition models for dynamic networks"
    - "dynamic stochastic blockmodels statistical models for time evolving networks"

Connected through hyperedge HE-3 (induced by source paper "seasonality in dynamic stochastic block models"):
  with members:
    - "stochastic block transition models for dynamic networks"
    - "dynamic stochastic blockmodels statistical models for time evolving networks"

Connected through hyperedge HE-4 (induced by source paper "are human interactivity times lognormal"):
  with members:
    - "social resilience in online communities the autopsy of friendster"
    - "are friends overrated a study for the social news aggregator digg com"

Connected through hyperedge HE-5 (induced by source paper "characterizing information spreading in online social networks"):
  with members:
    - "can cascades be predicted"

Connected through hyperedge HE-6 (induced by source paper "negative emotions boost user activity at bbc forum"):
  with members:
    - "emotional reactions and the pulse of public opinion measuring the impact of political events on the sentiment of online discussions"
    - "bloggers behavior and emergent communities in blog space"

Connected through hyperedge HE-7 (induced by source paper "agents bookmarks and clicks a topical model of web navigation"):
  with members:
    - "what s in a session tracking individual behavior on the web"
    - "remembering what we like toward an agent based model of web traffic"
    - "topical interests and the mitigation of search engine bias"

Connected through hyperedge HE-8 (induced by source paper "towards the characterization of individual users through web analytics"):
  with members:
    - "what s in a session tracking individual behavior on the web"
    - "remembering what we like toward an agent based model of web traffic"
    - "rhythms of social interaction messaging within a massive online network"
    - "novelty and collective attention"

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.HC(Human-Computer Interaction)