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 "mining cross cultural relations from wikipedia a study of 31 european food cultures"):
  Abstract: For many people, Wikipedia represents one of the primary sources of knowledge about foreign cultures. Yet, different Wikipedia language editions offer different descriptions of cultural practices. Unveiling diverging representations of cultures provides an important insight, since they may foster the formation of cross-cultural stereotypes, misunderstandings and potentially even conflict. In this work, we explore to what extent the descriptions of cultural practices in various European language editions of Wikipedia differ on the example of culinary practices and propose an approach to mine cultural relations between different language communities trough their description of and interest in their own and other communities' food culture. We assess the validity of the extracted relations using 1) various external reference data sources (i.e., the European Social Survey, migration statistics), 2) crowdsourcing methods and 3) simulations.

Includes members:
  Member "you are what you eat and drink identifying cultural boundaries by analyzing food drink habits in foursquare":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards business partnership recommendation using user opinion on facebook")
  Member "highlighting entanglement of cultures via ranking of multilingual wikipedia articles":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "capturing the influence of geopolitical ties from wikipedia with reduced google matrix")
  Member "the tower of babel meets web 2 0 user generated content and its applications in a multilingual context":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "measuring the importance of user generated content to search engines")

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)