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 "using sentiment induction to understand variation in gendered online communities"):
  Abstract: We analyze gendered communities defined in three different ways: text, users, and sentiment. Differences across these representations reveal facets of communities' distinctive identities, such as social group, topic, and attitudes. Two communities may have high text similarity but not user similarity or vice versa, and word usage also does not vary according to a clearcut, binary perspective of gender. Community-specific sentiment lexicons demonstrate that sentiment can be a useful indicator of words' social meaning and community values, especially in the context of discussion content and user demographics. Our results show that social platforms such as Reddit are active settings for different constructions of gender.

Includes members:
  Member "community identity and user engagement in a multi community landscape":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "trajectories of blocked community members redemption recidivism and departure")
  Member "loyalty in online communities":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "trajectories of blocked community members redemption recidivism and departure")
  Member "ultradense word embeddings by orthogonal transformation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "improving pre trained multilingual models with vocabulary expansion")
  Member "talking to the crowd what do people react to in online discussions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the anatomy of reddit an overview of academic research")
  Member "gender identity and lexical variation in social media":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "personalized dialogue generation with diversified traits")
  Member "how to ask for a favor a case study on the success of altruistic requests":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "conversations gone awry detecting early signs of conversational failure")

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.CL(Computation and Language)