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 "are all successful communities alike characterizing and predicting the success of online communities"):
  Abstract: The proliferation of online communities has created exciting opportunities to study the mechanisms that explain group success. While a growing body of research investigates community success through a single measure - typically, the number of members - we argue that there are multiple ways of measuring success. Here, we present a systematic study to understand the relations between these success definitions and test how well they can be predicted based on community properties and behaviors from the earliest period of a community's lifetime. We identify four success measures that are desirable for most communities: (i) growth in the number of members; (ii) retention of members; (iii) long term survival of the community; and (iv) volume of activities within the community. Surprisingly, we find that our measures do not exhibit very high correlations, suggesting that they capture different types of success. Additionally, we find that different success measures are predicted by different attributes of online communities, suggesting that success can be achieved through different behaviors. Our work sheds light on the basic understanding on what success represents in online communities and what predicts it. Our results suggest that success is multi-faceted and cannot be measured nor predicted by a single measurement. This insight has practical implications for the creation of new online communities and the design of platforms that facilitate such communities.

Includes members:
  Member "network structure efficiency and performance in wikiprojects":
    also connected through other hyperedges:
      (none)
  Member "tracing community genealogy how new communities emerge from the old":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the pushshift reddit dataset")
  Member "caveat emptor computational social science large scale missing data in a widely published reddit corpus":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ten social dimensions of conversations and relationships")
  Member "a warm welcome matters the link between social feedback and weight loss in r loseit":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "content removal as a moderation strategy compliance and other outcomes in the changemyview community")
  Member "loyalty in online communities":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "trajectories of blocked community members redemption recidivism and departure")
  Member "social networks under stress":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "planted hitting set recovery in hypergraphs")
  Member "the effect of social feedback in a reddit weight loss community":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "ten social dimensions of conversations and relationships")
  Member "all who wander on the prevalence and characteristics of multi community engagement":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "content removal as a moderation strategy compliance and other outcomes in the changemyview community")

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)