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 "all who wander on the prevalence and characteristics of multi community engagement"):
  Abstract: Although analyzing user behavior within individual communities is an active and rich research domain, people usually interact with multiple communities both on- and off-line. How do users act in such multi-community environments? Although there are a host of intriguing aspects to this question, it has received much less attention in the research community in comparison to the intra-community case. In this paper, we examine three aspects of multi-community engagement: the sequence of communities that users post to, the language that users employ in those communities, and the feedback that users receive, using longitudinal posting behavior on Reddit as our main data source, and DBLP for auxiliary experiments. We also demonstrate the effectiveness of features drawn from these aspects in predicting users' future level of activity. One might expect that a user's trajectory mimics the "settling-down" process in real life: an initial exploration of sub-communities before settling down into a few niches. However, we find that the users in our data continually post in new communities; moreover, as time goes on, they post increasingly evenly among a more diverse set of smaller communities. Interestingly, it seems that users that eventually leave the community are "destined" to do so from the very beginning, in the sense of showing significantly different "wandering" patterns very early on in their trajectories; this finding has potentially important design implications for community maintainers. Our multi-community perspective also allows us to investigate the "situation vs. personality" debate from language usage across different communities.

Includes members:
  Member "evolution of reddit from the front page of the internet to a self referential community":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "characterizing behavioral trends in a community driven discussion platform")
  Member "how community feedback shapes user behavior":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "trajectories of blocked community members redemption recidivism and departure")
  Member "the untold story of the clones content agnostic factors that impact youtube video popularity":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "identifying the sentiment styles of youtube s vloggers")
  Member "exploring text virality in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "causal effects of brevity on style and success in social media")
  Member "do linguistic style and readability of scientific abstracts affect their virality":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "why do urban legends go viral")
  Member "you had me at hello how phrasing affects memorability":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "movie plot analysis via turning point identification")
  Member "good friends bad news affect and virality in twitter":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sentiment dynamics in social media news channels")
  Member "on the interplay between social and topical structure":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "modeling information diffusion in online social networks with partial differential equations")

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)