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 "quantifying controversy in social media"):
  Abstract: Which topics spark the most heated debates on social media? Identifying those topics is not only interesting from a societal point of view, but also allows the filtering and aggregation of social media content for disseminating news stories. In this paper, we perform a systematic methodological study of controversy detection by using the content and the network structure of social media. #R##N#Unlike previous work, rather than study controversy in a single hand-picked topic and use domain specific knowledge, we take a general approach to study topics in any domain. Our approach to quantifying controversy is based on a graph-based three-stage pipeline, which involves (i) building a conversation graph about a topic; (ii) partitioning the conversation graph to identify potential sides of the controversy; and (iii) measuring the amount of controversy from characteristics of the graph. #R##N#We perform an extensive comparison of controversy measures, different graph-building approaches, and data sources. We use both controversial and non-controversial topics on Twitter, as well as other external datasets. We find that our new random-walk-based measure outperforms existing ones in capturing the intuitive notion of controversy, and show that content features are vastly less helpful in this task.

Includes members:
  Member "characterizing information diets of social media users":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "vocabulary based method for quantifying controversy in social media")
  Member "controversy and sentiment in online news":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "characterizing behavioral trends in a community driven discussion platform")
  Member "partisan sharing facebook evidence and societal consequences":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "political discussions in homogeneous and cross cutting communication spaces")
  Member "social determinants of content selection in the age of mis information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "vocabulary based method for quantifying controversy in social media")
  Member "data portraits connecting people of opposing views":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "language in our time an empirical analysis of hashtags")
  Member "efficient community detection in large networks using content and links":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "social science guided feature engineering a novel approach to signed link analysis")
  Member "modularity clustering is force directed layout":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "batchlayout a batch parallel force directed graph layout algorithm in shared memory")

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)