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 "fact checking in community forums"):
  Abstract: Community Question Answering (cQA) forums are very popular nowadays, as they represent effective means for communities around particular topics to share information. Unfortunately, this information is not always factual. Thus, here we explore a new dimension in the context of cQA, which has been ignored so far: checking the veracity of answers to particular questions in cQA forums. As this is a new problem, we create a specialized dataset for it. We further propose a novel multi-faceted model, which captures information from the answer content (what is said and how), from the author profile (who says it), from the rest of the community forum (where it is said), and from external authoritative sources of information (external support). Evaluation results show a MAP value of 86.54, which is 21 points absolute above the baseline.

Includes members:
  Member "semeval 2015 task 3 answer selection in community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "training neural response selection for task oriented dialogue systems")
  Member "semeval 2016 task 3 community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "review guided helpful answer identification in e commerce")
  Member "semeval 2017 task 3 community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a pilot study on multiple choice machine reading comprehension for vietnamese texts")
  Member "semanticz at semeval 2016 task 3 ranking relevant answers in community question answering using semantic similarity based on fine tuned word embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "automatic fact checking using context and discourse information")
  Member "analysing how people orient to and spread rumours in social media by looking at conversational threads":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "two path deep semi supervised learning for timely fake news detection")
  Member "leveraging joint interactions for credibility analysis in news communities":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "checkthat at clef 2020 enabling the automatic identification and verification of claims in social media")

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)