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 "measuring the diversity of facebook reactions to research"):
  Abstract: Online and in the real world, communities are bonded together by emotional consensus around core issues. Emotional responses to scientific findings often play a pivotal role in these core issues. When there is too much diversity of opinion on topics of science, emotions flare up and give rise to conflict. This conflict threatens positive outcomes for research. Emotions have the power to shape how people process new information. They can color the public's understanding of science, motivate policy positions, even change lives. And yet little work has been done to evaluate the public's emotional response to science using quantitative methods. In this paper, we use a dataset of responses to scholarly articles on Facebook to analyze the dynamics of emotional valence, intensity, and diversity. We present a novel way of weighting click-based reactions that increases their comprehensibility, and use these weighted reactions to develop new metrics of aggregate emotional responses. We use our metrics along with LDA topic models and statistical testing to investigate how users' emotional responses differ from one scientific topic to another. We find that research articles related to gender, genetics, or agricultural/environmental sciences elicit significantly different emotional responses from users than other research topics. We also find that there is generally a positive response to scientific research on Facebook, and that articles generating a positive emotional response are more likely to be widely shared---a conclusion that contradicts previous studies of other social media platforms.

Includes members:
  Member "jointly learning to detect emotions and predict facebook reactions":
    also connected through other hyperedges:
      (none)
  Member "shared feelings understanding facebook reactions to scholarly articles":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "using arabic tweets to understand drug selling behaviors")
  Member "community interaction and conflict on the web":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ten social dimensions of conversations and relationships")
  Member "could scientists use altmetric com scores to predict longer term citation counts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mendeley reader counts for us computer science conference papers and journal articles")
  Member "social emotion mining techniques for facebook posts reaction prediction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cross lingual data transformation and combination for text classification")
  Member "anatomy of scholarly information behavior patterns in the wake of academic social media platforms":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "using arabic tweets to understand drug selling behaviors")
  Member "scholarly use of social media and altmetrics a review of the literature":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")
  Member "140 characters to victory using twitter to predict the uk 2015 general election":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on computational politics")

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)