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 "antagonism also flows through retweets the impact of out of context quotes in opinion polarization analysis"):
  Abstract: In this paper, we study the implications of the commonplace assumption that most social media studies make with respect to the nature of message shares (such as retweets) as a predominantly positive interaction. By analyzing two large longitudinal Brazilian Twitter datasets containing 5 years of conversations on two polarizing topics - Politics and Sports - we empirically demonstrate that groups holding antagonistic views can actually retweet each other more often than they retweet other groups. We show that assuming retweets as endorsement interactions can lead to misleading conclusions with respect to the level of antagonism among social communities, and that this apparent paradox is explained in part by the use of retweets to quote the original content creator out of the message's original temporal context, for humor and criticism purposes. As a consequence, messages diffused on online media can have their polarity reversed over time, what poses challenges for social and computer scientists aiming to classify and track opinion groups on online media. On the other hand, we found that the time users take to retweet a message after it has been originally posted can be a useful signal to infer antagonism in social platforms, and that surges of out-of-context retweets correlate with sentiment drifts triggered by real-world events. We also discuss how such evidences can be embedded in sentiment analysis models.

Includes members:
  Member "quote rts on twitter usage of the new feature for political discourse":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on computational politics")
  Member "user level sentiment analysis incorporating social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "jnet learning user representations via joint network embedding and topic embedding")

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)