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: "trends in social media persistence and decay"
  Abstract: Social media generates a prodigious wealth of real-time content at an incessant rate. From all the content that people create and share, only a few topics manage to attract enough attention to rise to the top and become temporal trends which are displayed to users. The question of what factors cause the formation and persistence of trends is an important one that has not been answered yet. In this paper, we conduct an intensive study of trending topics on Twitter and provide a theoretical basis for the formation, persistence and decay of trends. We also demonstrate empirically how factors such as user activity and number of followers do not contribute strongly to trend creation and its propagation. In fact, we find that the resonance of the content with the users of the social network plays a major role in causing trends.

Connected through hyperedge HE-1 (induced by source paper "toward maximizing the visibility of content in social media brand pages a temporal analysis"):
  with members:
    - "online popularity under promotion viral potential forecasting and the economics of time"
    - "multistage campaigning in social networks"
    - "when to post on social networks"
    - "klout score measuring influence across multiple social networks"
    - "dynamical classes of collective attention in twitter"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"
    - "predicting the popularity of online content"

Connected through hyperedge HE-2 (induced by source paper "mining social media for newsgathering a review"):
  with members:
    - "detection and resolution of rumours in social media a survey"
    - "discourse aware rumour stance classification in social media using sequential classifiers"
    - "supporting the use of user generated content in journalistic practice"
    - "semeval 2017 task 8 rumoureval determining rumour veracity and support for rumours"
    - "fake news detection on social media a data mining perspective"
    - "discriminative predicate path mining for fact checking in knowledge graphs"
    - "hoaxy a platform for tracking online misinformation"
    - "rapid classification of crisis related data on social networks using convolutional neural networks"

Connected through hyperedge HE-3 (induced by source paper "emtagger a word embedding based novel method for hashtag recommendation on twitter"):
  with members:
    - "literature survey on interplay of topics information diffusion and connections on social networks"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-4 (induced by source paper "do cascades recur"):
  with members:
    - "information evolution in social networks"
    - "the bursty dynamics of the twitter information network"
    - "can cascades be predicted"
    - "the untold story of the clones content agnostic factors that impact youtube video popularity"
    - "the role of social networks in information diffusion"
    - "information diffusion and external influence in networks"

Connected through hyperedge HE-5 (induced by source paper "style in the age of instagram predicting success within the fashion industry using social media"):
  with members:
    - "on facebook most ties are weak"
    - "online popularity and topical interests through the lens of instagram"
    - "clustering memes in social media streams"
    - "traveling trends social butterflies or frequent fliers"
    - "clustering memes in social media"

Connected through hyperedge HE-6 (induced by source paper "credibility and dynamics of collective attention"):
  with members:
    - "tweetcred real time credibility assessment of content on twitter"
    - "big questions for social media big data representativeness validity and other methodological pitfalls"
    - "dynamical classes of collective attention in twitter"
    - "novelty and collective attention"

Connected through hyperedge HE-7 (induced by source paper "a dynamical model of twitter activity profiles"):
  with members:
    - "the simple rules of social contagion"
    - "characterizing the life cycle of online news stories using social media reactions"
    - "the role of information diffusion in the evolution of social networks"
    - "information diffusion and external influence in networks"
    - "dynamical classes of collective attention in twitter"
    - "truthy mapping the spread of astroturf in microblog streams"
    - "trends prediction using social diffusion models"

Connected through hyperedge HE-8 (induced by source paper "temporal effects in trend prediction identifying the most popular nodes in the future"):
  with members:
    - "trend prediction in temporal bipartite networks the case of movielens netflix and digg"
    - "quantifying long term scientific impact"
    - "the pulse of news in social media forecasting popularity"
    - "using a model of social dynamics to predict popularity of news"
    - "harvesting collective intelligence temporal behavior in yahoo answers"
    - "predicting the popularity of online content"

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)