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 "anger is more influential than joy sentiment correlation in weibo"):
  Abstract: Recent years have witnessed the tremendous growth of the online social media. In China, Weibo, a Twitter-like service, has attracted more than 500 million users in less than five years. Connected by online social ties, different users might share similar affective states. We find that the correlation of anger among users is significantly higher than that of joy. While the correlation of sadness is surprisingly low. Moreover, there is a stronger sentiment correlation between a pair of users if they share more interactions. And users with larger number of friends possess more significant sentiment correlation with their neighborhoods. Our findings could provide insights for modeling sentiment influence and propagation in online social networks.

Includes members:
  Member "negative emotions boost user activity at bbc forum":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an agent based model for emotion contagion and competition in online social media")
  Member "twitter reciprocal reply networks exhibit assortativity with respect to happiness":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "networks of power analyzing world leaders interactions on social media")
  Member "happiness is assortative in online social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "friendship paradox biases perceptions in directed networks")
  Member "twitter mood predicts the stock market":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mining social media data for biomedical signals and health related behavior")
  Member "measuring the happiness of large scale written expression songs blogs and presidents":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mining social media data for biomedical signals and health related behavior")
  Member "thumbs up sentiment classification using machine learning techniques":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "description based text classification with reinforcement learning")

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.SI(Social and Information Networks)