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: "bigbirds never die understanding social dynamics of emergent hashtag"
  Abstract: We examine the growth, survival, and context of 256 novel hashtags during the 2012 U.S. presidential debates. Our analysis reveals the trajectories of hashtag use fall into two distinct classes: "winners" that emerge more quickly and are sustained for longer periods of time than other "also-rans" hashtags. We propose a "conversational vibrancy" framework to capture dynamics of hashtags based on their topicality, interactivity, diversity, and prominence. Statistical analyses of the growth and persistence of hashtags reveal novel relationships between features of this framework and the relative success of hashtags. Specifically, retweets always contribute to faster hashtag adoption, replies extend the life of "winners" while having no effect on "also-rans." This is the first study on the lifecycle of hashtag adoption and use in response to purely exogenous shocks. We draw on theories of uses and gratification, organizational ecology, and language evolution to discuss these findings and their implications for understanding social influence and collective action in social media more generally.

Connected through hyperedge HE-1 (induced by source paper "language in our time an empirical analysis of hashtags"):
  with members:
    - "network embedding as matrix factorization unifying deepwalk line pte and node2vec"
    - "tagvisor a privacy advisor for sharing hashtags"
    - "hierarchical graph representation learning with differentiable pooling"
    - "you are your metadata identification and obfuscation of social media users using metadata information"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "ml leaks model and data independent membership inference attacks and defenses on machine learning models"
    - "twitter for sparking a movement reddit for sharing the moment metoo through the lens of social media"
    - "is saki delicious the food perception gap on instagram and its relation to health"

Connected through hyperedge HE-2 (induced by source paper "cascades a view from audience"):
  with members:
    - "bieber blast bieberblast early prediction of popular hashtag compounds"
    - "can cascades be predicted"
    - "you had me at hello how phrasing affects memorability"
    - "on the interplay between social and topical structure"

Connected through hyperedge HE-3 (induced by source paper "the message or the messenger inferring virality and diffusion structure from online petition signature data"):
  with members:
    - "leadership without leaders starters and followers in online collective action"
    - "predicting successful memes using network and community structure"
    - "petition growth and success rates on the uk no 10 downing street website"

Connected through hyperedge HE-4 (induced by source paper "bieber blast bieberblast early prediction of popular hashtag compounds"):
  with members:
    - "predicting successful memes using network and community structure"
    - "mark my words linguistic style accommodation in social media"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"
    - "inferring networks of diffusion and influence"

Connected through hyperedge HE-5 (induced by source paper "greysanatomy vs yankees demographics and hashtag use on twitter"):
  with members:
    - "you are what apps you use demographic prediction based on user s apps"
    - "characterizing the demographics behind the blacklivesmatter movement"
    - "dynamical classes of collective attention in twitter"

Connected through hyperedge HE-6 (induced by source paper "whats in a country name twitter hashtag analysis of singapore"):
  with members:
    - "machine learning in automated text categorization"

Connected through hyperedge HE-7 (induced by source paper "topicality and impact in social media diverse messages focused messengers"):
  with members:
    - "can cascades be predicted"
    - "the role of information diffusion in the evolution of social networks"
    - "clustering memes in social media"
    - "virality prediction and community structure in social networks"
    - "real time discovery of dense clusters in highly dynamic graphs identifying real world events in highly dynamic environments"
    - "on the interplay between social and topical structure"
    - "folks in folksonomies social link prediction from shared metadata"
    - "influence and passivity in social media"

Connected through hyperedge HE-8 (induced by source paper "towards a standard sampling methodology on online social networks collecting global trends on twitter"):
  with members:
    - "geo located twitter as proxy for global mobility patterns"
    - "predicting crowd behavior with big public data"
    - "the role of information diffusion in the evolution of social networks"
    - "organization mining using online social networks"
    - "virality prediction and community structure in social networks"
    - "the anatomy of the facebook social graph"
    - "supervised random walks predicting and recommending links in social networks"

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)