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 "combating fake news a survey on identification and mitigation techniques"):
  Abstract: The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news, and mitigation of its widespread impact on public opinion. While much of the earlier research was focused on identification of fake news based on its contents or by exploiting users' engagements with the news on social media, there has been a rising interest in proactive intervention strategies to counter the spread of misinformation and its impact on society. In this survey, we describe the modern-day problem of fake news and, in particular, highlight the technical challenges associated with it. We discuss existing methods and techniques applicable to both identification and mitigation, with a focus on the significant advances in each method and their advantages and limitations. In addition, research has often been limited by the quality of existing datasets and their specific application contexts. To alleviate this problem, we comprehensively compile and summarize characteristic features of available datasets. Furthermore, we outline new directions of research to facilitate future development of effective and interdisciplinary solutions.

Includes members:
  Member "the web of false information rumors fake news hoaxes clickbait and various other shenanigans":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an emotional analysis of false information in social media and news articles")
  Member "adversarial classification on social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "topological effects on attacks against vertex classification")
  Member "all in one multi task learning for rumour verification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "two path deep semi supervised learning for timely fake news detection")
  Member "fakenewsnet a data repository with news content social context and dynamic information for studying fake news on social media":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "discover your social identity from what you tweet a content based approach")
  Member "fever a large scale dataset for fact extraction and verification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the microsoft toolkit of multi task deep neural networks for natural language understanding")
  Member "detection and resolution of rumours in social media a survey":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "discover your social identity from what you tweet a content based approach")
  Member "me my echo chamber and i introspection on social media polarization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "beyond trolling malware induced misperception attacks on polarized facebook discourse")
  Member "fake news detection in social networks via crowd signals":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "attributed multi relational attention network for fact checking url recommendation")

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.LG(Machine Learning)