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 "characterization of local attitudes toward immigration using social media"):
  Abstract: Migration is a worldwide phenomenon that may generate different reactions in the population. Attitudes vary from those that support multiculturalism and communion between locals and foreigners, to contempt and hatred toward immigrants. Since anti-immigration attitudes are often materialized in acts of violence and discrimination, it is important to identify factors that characterize these attitudes. However, doing so is expensive and impractical, as traditional methods require enormous efforts to collect data. In this paper, we propose to leverage Twitter to characterize local attitudes toward immigration, with a case study on Chile, where immigrant population has drastically increased in recent years. Using semi-supervised topic modeling, we situated 49K users into a spectrum ranging from in-favor to against immigration. We characterized both sides of the spectrum in two aspects: the emotions and lexical categories relevant for each attitude, and the discussion network structure. We found that the discussion is mostly driven by Haitian immigration; that there are temporal trends in tendency and polarity of discussion; and that assortative behavior on the network differs with respect to attitude. These insights may inform policy makers on how people feel with respect to migration, with potential implications on communication of policy and the design of interventions to improve inter-group relations.

Includes members:
  Member "topic supervised non negative matrix factorization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "toward an interdisciplinary methodology to solve new old transportation problems")
  Member "encouraging diversity and representation awareness in geographically centralized content":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "data portraits and intermediary topics encouraging exploration of politically diverse profiles")
  Member "finding intermediary topics between people of opposing views a case study":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "data portraits and intermediary topics encouraging exploration of politically diverse profiles")

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)