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 "learning class specific word representations for early detection of hoaxes in social media"):
  Abstract: As people increasingly use social media as a source for news consumption, its unmoderated nature enables the diffusion of hoaxes, which in turn jeopardises the credibility of information gathered from social media platforms. To mitigate this problem, we study the development of a hoax detection system that can distinguish true and false reports early on. We introduce a semi-automated approach that leverages the Wikidata knowledge base to build large-scale datasets for veracity classification, which enables us to create a dataset with 4,007 reports including over 13 million tweets, 15% of which are fake. We describe a method for learning class-specific word representations using word embeddings, which we call multiw2v. Our approach achieves competitive results with F1 scores over 72% within 10 minutes of the first tweet being posted, outperforming other baselines. Our dataset represents a realistic scenario with a real distribution of true and false stories, which we release for further use as a benchmark in future research.

Includes members:
  Member "detection and resolution of rumours in social media a survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "discover your social identity from what you tweet a content based approach")
  Member "fake news detection on social media a data mining perspective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "benchmark performance of machine and deep learning based methodologies for urdu text document classification")
  Member "some like it hoax automated fake news detection in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "detecting fake news with capsule neural networks")
  Member "distributed representations of words and phrases and their compositionality":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")

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)