human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the lifecycles of apps in a social ecosystem"
  Abstract: Apps are emerging as an important form of on-line content, and they combine aspects of Web usage in interesting ways --- they exhibit a rich temporal structure of user adoption and long-term engagement, and they exist in a broader social ecosystem that helps drive these patterns of adoption and engagement. It has been difficult, however, to study apps in their natural setting since this requires a simultaneous analysis of a large set of popular apps and the underlying social network they inhabit. In this work we address this challenge through an analysis of the collection of apps on Facebook Login, developing a novel framework for analyzing both temporal and social properties. At the temporal level, we develop a retention model that represents a user's tendency to return to an app using a very small parameter set. At the social level, we organize the space of apps along two fundamental axes --- popularity and sociality --- and we show how a user's probability of adopting an app depends both on properties of the local network structure and on the match between the user's attributes, his or her friends' attributes, and the dominant attributes within the app's user population. We also devolop models that show the importance of different feature sets with strong performance in predicting app success.

Connected through hyperedge HE-1 (induced by source paper "are all successful communities alike characterizing and predicting the success of online communities"):
  with members:
    - "network structure efficiency and performance in wikiprojects"
    - "tracing community genealogy how new communities emerge from the old"
    - "caveat emptor computational social science large scale missing data in a widely published reddit corpus"
    - "a warm welcome matters the link between social feedback and weight loss in r loseit"
    - "loyalty in online communities"
    - "social networks under stress"
    - "the effect of social feedback in a reddit weight loss community"
    - "all who wander on the prevalence and characteristics of multi community engagement"

Connected through hyperedge HE-2 (induced by source paper "an experimental study of structural diversity in social networks"):
  with members:
    - "popularity prediction in microblogging network a case study on sina weibo"
    - "characterizing and curating conversation threads expansion focus volume re entry"
    - "virality prediction and community structure in social networks"
    - "social influence in social advertising evidence from field experiments"
    - "on the interplay between social and topical structure"

Connected through hyperedge HE-3 (induced by source paper "iphone s digital marketplace characterizing the big spenders"):
  with members:
    - "portrait of an online shopper understanding and predicting consumer behavior"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-4 (induced by source paper "the lifecycle and cascade of wechat social messaging groups"):
  with members:
    - "uncovering the small community structure in large networks a local spectral approach"
    - "can cascades be predicted"
    - "virality prediction and community structure in social networks"
    - "the role of social networks in information diffusion"
    - "inferring networks of diffusion and influence"

Question: Please tell me which class the center node 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)