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: "from user comments to on line conversations"
  Abstract: We present an analysis of user conversations in on-line social media and their evolution over time. We propose a dynamic model that accurately predicts the growth dynamics and structural properties of conversation threads. The model successfully reconciles the differing observations that have been reported in existing studies. By separating artificial factors from user behaviors, we show that there are actually underlying rules in common for on-line conversations in different social media websites. Results of our model are supported by empirical measurements throughout a number of different social media websites.

Connected through hyperedge HE-1 (induced by source paper "nestpp modeling thread dynamics in online discussion forums"):
  with members:
    - "modelling structure and predicting dynamics of discussion threads in online boards"
    - "personalized thread recommendation for mooc discussion forums"
    - "expecting to be hip hawkes intensity processes for social media popularity"
    - "tideh time dependent hawkes process for predicting retweet dynamics"
    - "feature driven and point process approaches for popularity prediction"
    - "seismic a self exciting point process model for predicting tweet popularity"
    - "can cascades be predicted"

Connected through hyperedge HE-2 (induced by source paper "modelling structure and predicting dynamics of discussion threads in online boards"):
  with members:
    - "tideh time dependent hawkes process for predicting retweet dynamics"
    - "all who wander on the prevalence and characteristics of multi community engagement"
    - "local variation of hashtag spike trains and popularity in twitter"
    - "seismic a self exciting point process model for predicting tweet popularity"
    - "modeling and predicting popularity dynamics via reinforced poisson processes"
    - "can cascades be predicted"
    - "a likelihood based framework for the analysis of discussion threads"
    - "quantifying long term scientific impact"

Connected through hyperedge HE-3 (induced by source paper "the anatomy of reddit an overview of academic research"):
  with members:
    - "modelling structure and predicting dynamics of discussion threads in online boards"
    - "the aftermath of disbanding an online hateful community"
    - "tracing community genealogy how new communities emerge from the old"
    - "community interaction and conflict on the web"
    - "caveat emptor computational social science large scale missing data in a widely published reddit corpus"
    - "on the origins of memes by means of fringe web communities"
    - "conversation modeling on reddit using a graph structured lstm"
    - "identifying the social signals that drive online discussions a case study of reddit communities"

Connected through hyperedge HE-4 (induced by source paper "discussion quality diffuses in the digital public square"):
  with members:
    - "tweet2vec learning tweet embeddings using character level cnn lstm encoder decoder"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "distributed representations of sentences and documents"
    - "word2vec explained deriving mikolov et al s negative sampling word embedding method"
    - "how community feedback shapes user behavior"
    - "social influence in social advertising evidence from field experiments"

Connected through hyperedge HE-5 (induced by source paper "a continuous time mutually exciting point process framework for prioritizing events in social media"):
  with members:
    - "back to the past source identification in diffusion networks from partially observed cascades"
    - "coevolve a joint point process model for information diffusion and network co evolution"
    - "shaping social activity by incentivizing users"
    - "characterizing and curating conversation threads expansion focus volume re entry"

Connected through hyperedge HE-6 (induced by source paper "modelling page view dynamics on wikipedia"):
  with members:
    - "there is no deadline time evolution of wikipedia discussions"
    - "dynamical classes of collective attention in twitter"
    - "predicting the popularity of online content"
    - "novelty and collective attention"

Connected through hyperedge HE-7 (induced by source paper "characterizing and curating conversation threads expansion focus volume re entry"):
  with members:
    - "exploring text virality in social networks"
    - "you had me at hello how phrasing affects memorability"
    - "echoes of power language effects and power differences in social interaction"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"

Connected through hyperedge HE-8 (induced by source paper "a likelihood based framework for the analysis of discussion threads"):
  with members:
    - "using a model of social dynamics to predict popularity of news"
    - "predicting the popularity of online content"
    - "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.CY(Computers and Society)