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 "stochastic models predict user behavior in social media"):
  Abstract: User response to contributed content in online social media depends on many factors. These include how the site lays out new content, how frequently the user visits the site, how many friends the user follows, how active these friends are, as well as how interesting or useful the content is to the user. We present a stochastic modeling framework that relates a user's behavior to details of the site's user interface and user activity and describe a procedure for estimating model parameters from available data. We apply the model to study discussions of controversial topics on Twitter, specifically, to predict how followers of an advocate for a topic respond to the advocate's posts. We show that a model of user behavior that explicitly accounts for a user transitioning through a series of states before responding to an advocate's post better predicts response than models that fail to take these states into account. We demonstrate other benefits of stochastic models, such as their ability to identify users who are highly interested in advocate's posts.

Includes members:
  Member "friendship paradox redux your friends are more interesting than you":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "information diffusion in social networks friendship paradox based models and statistical inference")
  Member "collaborative topic regression with social matrix factorization for recommendation systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "semi supervised learning meets factorization learning to recommend with chain graph model")
  Member "social dynamics of digg":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep collaborative embedding for information cascade prediction")
  Member "using stochastic models to describe and predict social dynamics of web users":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "continuous time user modeling in the presence of badges a probabilistic approach")
  Member "stochastic models of user contributory web sites":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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-6 (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-7 (induced by source paper "popularity prediction on social platforms with coupled graph neural networks")
  Member "social information processing in news aggregation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "topicality and impact in social media diverse messages focused messengers")

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)