human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "everything i disagree with is fakenews correlating political polarization and spread of misinformation"
  Abstract: An important challenge in the process of tracking and detecting the dissemination of misinformation is to understand the political gap between people that engage with the so called "fake news". A possible factor responsible for this gap is opinion polarization, which may prompt the general public to classify content that they disagree or want to discredit as fake. In this work, we study the relationship between political polarization and content reported by Twitter users as related to "fake news". We investigate how polarization may create distinct narratives on what misinformation actually is. We perform our study based on two datasets collected from Twitter. The first dataset contains tweets about US politics in general, from which we compute the degree of polarization of each user towards the Republican and Democratic Party. In the second dataset, we collect tweets and URLs that co-occurred with "fake news" related keywords and hashtags, such as #FakeNews and #AlternativeFact, as well as reactions towards such tweets and URLs. We then analyze the relationship between polarization and what is perceived as misinformation, and whether users are designating information that they disagree as fake. Our results show an increase in the polarization of users and URLs associated with fake-news keywords and hashtags, when compared to information not labeled as "fake news". We discuss the impact of our findings on the challenges of tracking "fake news" in the ongoing battle against misinformation.

Connected through hyperedge HE-1 (induced by source paper "online disinformation and the role of wikipedia"):
  with members:
    - "citation needed a taxonomy and algorithmic assessment of wikipedia s verifiability"
    - "the wisdom of polarized crowds"
    - "auditing radicalization pathways on youtube"
    - "the fact extraction and verification fever shared task"
    - "exposing deepfake videos by detecting face warping artifacts"
    - "fake news a survey of research detection methods and opportunities"
    - "fever a large scale dataset for fact extraction and verification"
    - "strategies and influence of social bots in a 2017 german state election a case study on twitter"

Connected through hyperedge HE-2 (induced by source paper "community interaction and conflict on the web"):
  with members:
    - "false information on web and social media a survey"
    - "community identity and user engagement in a multi community landscape"
    - "an army of me sockpuppets in online discussion communities"
    - "contagion dynamics of extremist propaganda in social networks"
    - "representation learning on graphs methods and applications"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "loyalty in online communities"
    - "kek cucks and god emperor trump a measurement study of 4chan s politically incorrect forum and its effects on the web"

Question: Please tell me which class the center node 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)