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: "recommending targeted strangers from whom to solicit information on social media"
  Abstract: We present an intelligent, crowd-powered information collection system that automatically identifies and asks target-ed strangers on Twitter for desired information (e.g., cur-rent wait time at a nightclub). Our work includes three parts. First, we identify a set of features that characterize ones willingness and readiness to respond based on their exhibited social behavior, including the content of their tweets and social interaction patterns. Second, we use the identified features to build a statistical model that predicts ones likelihood to respond to information solicitations. Third, we develop a recommendation algorithm that selects a set of targeted strangers using the probabilities computed by our statistical model with the goal to maximize the over-all response rate. Our experiments, including several in the real world, demonstrate the effectiveness of our work.

Connected through hyperedge HE-1 (induced by source paper "recruiting hay to find needles recursive incentives and innovation in social networks"):
  with members:
    - "time critical social mobilization"

Connected through hyperedge HE-2 (induced by source paper "confiding in and listening to virtual agents the effect of personality"):
  with members:
    - "who will retweet this automatically identifying and engaging strangers on twitter to spread information"
    - "interpreting social cues to generate credible affective reactions of virtual job interviewers"

Connected through hyperedge HE-3 (induced by source paper "who will retweet this automatically identifying and engaging strangers on twitter to spread information"):
  with members:
    - "the role of social networks in information diffusion"
    - "information transfer in social media"
    - "influence and passivity in social media"
    - "smote synthetic minority over sampling technique"

Connected through hyperedge HE-4 (induced by source paper "is anyone out there unpacking q a hashtags on twitter"):
  with members:
    - "on the interplay between social and topical structure"

Connected through hyperedge HE-5 (induced by source paper "why are you more engaged predicting social engagement from word use"):
  with members:
    - "the role of social networks in information diffusion"

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)