human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "using a model of social dynamics to predict popularity of news"):
  Abstract: Popularity of content in social media is unequally distributed, with some items receiving a disproportionate share of attention from users. Predicting which newly-submitted items will become popular is critically important for both companies that host social media sites and their users. Accurate and timely prediction would enable the companies to maximize revenue through differential pricing for access to content or ad placement. Prediction would also give consumers an important tool for filtering the ever-growing amount of content. Predicting popularity of content in social media, however, is challenging due to the complex interactions among content quality, how the social media site chooses to highlight content, and influence among users. While these factors make it difficult to predict popularity \emph{a priori}, we show that stochastic models of user behavior on these sites allows predicting popularity based on early user reactions to new content. By incorporating aspects of the web site design, such models improve on predictions based on simply extrapolating from the early votes. We validate this claim on the social news portal Digg using a previously-developed model of social voting based on the Digg user interface.

Includes members:
  Member "stochastic models of user contributory web sites":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "modeling the popularity of twitter hashtags with master equations")
  Member "predicting the popularity of online content":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "online convex optimization for caching networks")
  Member "analysis of social voting patterns on digg":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "popularity prediction on social platforms with coupled graph neural networks")
  Member "novelty and collective attention":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "modeling the popularity of twitter hashtags with master equations")
  Member "social information processing in news aggregation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "topicality and impact in social media diverse messages focused messengers")
  Member "social browsing on flickr":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the dynamics of social media popularity a youtube case study")
  Member "social networks and social information filtering on digg":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "systems applications of social networks")

Question: Please tell me which class the source paper 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)