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 "distinguishing between personal preferences and social influence in online activity feeds"):
  Abstract: Many online social networks thrive on automatic sharing of friends' activities to a user through activity feeds, which may influence the user's next actions. However, identifying such social influence is tricky because these activities are simultaneously impacted by influence and homophily. We propose a statistical procedure that uses commonly available network and observational data about people's actions to estimate the extent of copy-influence---mimicking others' actions that appear in a feed. We assume that non-friends don't influence users; thus, comparing how a user's activity correlates with friends versus non-friends who have similar preferences can help tease out the effect of copy-influence.   Experiments on datasets from multiple social networks show that estimates that don't account for homophily overestimate copy-influence by varying, often large amounts. Further, copy-influence estimates fall below 1% of total actions in all networks: most people, and almost all actions, are not affected by the feed. Our results question common perceptions around the extent of copy-influence in online social networks and suggest improvements to diffusion and recommendation models.

Includes members:
  Member "do social explanations work studying and modeling the effects of social explanations in recommender systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hybrid deep embedding for recommendations with dynamic aspect level explanations")
  Member "friends strangers and the value of ego networks for recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "studying and modeling the connection between people s preferences and content sharing")
  Member "the role of social networks in information diffusion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep learning approach on information diffusion in heterogeneous networks")
  Member "social influence in social advertising evidence from field experiments":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "locec local community based edge classification in large online social networks")
  Member "information contagion an empirical study of the spread of news on digg and twitter social networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "modeling information diffusion in online social networks with partial differential equations")
  Member "predicting influential users in online social networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sensing and modeling human behavior using social media and mobile data")

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)