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: "disinformation warfare understanding state sponsored trolls on twitter and their influence on the web"
  Abstract: Over the past couple of years, anecdotal evidence has emerged linking coordinated campaigns by state-sponsored actors with efforts to manipulate public opinion on the Web, often around major political events, through dedicated accounts, or "trolls." Although they are often involved in spreading disinformation on social media, there is little understanding of how these trolls operate, what type of content they disseminate, and most importantly their influence on the information ecosystem. #R##N#In this paper, we shed light on these questions by analyzing 27K tweets posted by 1K Twitter users identified as having ties with Russia's Internet Research Agency and thus likely state-sponsored trolls. We compare their behavior to a random set of Twitter users, finding interesting differences in terms of the content they disseminate, the evolution of their account, as well as their general behavior and use of the Twitter platform. Then, using a statistical model known as Hawkes Processes, we quantify the influence that these accounts had on the dissemination of news on social platforms such as Twitter, Reddit, and 4chan. Overall, our findings indicate that Russian troll accounts managed to stay active for long periods of time and to reach a substantial number of Twitter users with their messages. When looking at their ability of spreading news content and making it viral, however, we find that their effect on social platforms was minor, with the significant exception of news published by the Russian state-sponsored news outlet RT (Russia Today).

Connected through hyperedge HE-1 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities"):
  with members:
    - "characterizing the use of images by state sponsored troll accounts on twitter"
    - "characterizing the use of images in state sponsored information warfare operations by russian trolls on twitter"
    - "what is gab a bastion of free speech or an alt right echo chamber"
    - "a quantitative approach to understanding online antisemitism"
    - "who let the trolls out towards understanding state sponsored trolls"
    - "mobilizing the trump train understanding collective action in a political trolling community"
    - "false information on web and social media a survey"
    - "on the origins of memes by means of fringe web communities"

Connected through hyperedge HE-2 (induced by source paper "the web of false information rumors fake news hoaxes clickbait and various other shenanigans"):
  with members:
    - "what is gab a bastion of free speech or an alt right echo chamber"
    - "false information on web and social media a survey"
    - "it s always april fools day on the difficulty of social network misinformation classification via propagation features"
    - "liar liar pants on fire a new benchmark dataset for fake news detection"
    - "detection and analysis of 2016 us presidential election related rumors on twitter"
    - "this just in fake news packs a lot in title uses simpler repetitive content in text body more similar to satire than real news"
    - "fake news mitigation via point process based intervention"
    - "an efficient randomized algorithm for rumor blocking in online social networks"

Connected through hyperedge HE-3 (induced by source paper "still out there modeling and identifying russian troll accounts on twitter"):
  with members:
    - "analysis of strategy and spread of russia sponsored content in the us in 2017"
    - "unsupervised machine learning of open source russian twitter data reveals global scope and operational characteristics"
    - "who let the trolls out towards understanding state sponsored trolls"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "who falls for online political manipulation"
    - "the spread of low credibility content by social bots"
    - "the spread of fake news by social bots"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"

Connected through hyperedge HE-4 (induced by source paper "characterizing the use of images in state sponsored information warfare operations by russian trolls on twitter"):
  with members:
    - "tracking the digital traces of russian trolls distinguishing the roles and strategy of trolls on twitter"
    - "still out there modeling and identifying russian troll accounts on twitter"
    - "analysis of strategy and spread of russia sponsored content in the us in 2017"
    - "senator we sell ads analysis of the 2016 russian facebook ads campaign"
    - "a quantitative approach to understanding online antisemitism"
    - "who let the trolls out towards understanding state sponsored trolls"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "mobilizing the trump train understanding collective action in a political trolling community"

Connected through hyperedge HE-5 (induced by source paper "political elections under social fire analysis and detection of propaganda on twitter"):
  with members:
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "election campaigning on social media politicians audiences and the mediation of political communication on facebook and twitter"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "deep neural networks for bot detection"
    - "the paradigm shift of social spambots evidence theories and tools for the arms race"
    - "online human bot interactions detection estimation and characterization"
    - "botornot a system to evaluate social bots"
    - "measuring user influence on twitter"

Connected through hyperedge HE-6 (induced by source paper "textrolls identifying russian trolls on twitter from a textual perspective"):
  with members:
    - "partisanship propaganda and post truth politics quantifying impact in online debate"
    - "still out there modeling and identifying russian troll accounts on twitter"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "who falls for online political manipulation"
    - "tweet2vec character based distributed representations for social media"
    - "sifting robotic from organic text a natural language approach for detecting automation on twitter"

Connected through hyperedge HE-7 (induced by source paper "can whatsapp counter misinformation by limiting message forwarding"):
  with members:
    - "on microtargeting socially divisive ads a case study of russia linked ad campaigns on facebook"
    - "whatsapp doc a first look at whatsapp public group data"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "navigating the massive world of reddit using backbone networks to map user interests in social media"
    - "the role of social networks in information diffusion"
    - "image labeling on a network using social network metadata for image classification"

Connected through hyperedge HE-8 (induced by source paper "on the influence of twitter trolls during the 2016 us presidential election"):
  with members:
    - "tracking the digital traces of russian trolls distinguishing the roles and strategy of trolls on twitter"
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "who let the trolls out towards understanding state sponsored trolls"
    - "botornot a system to evaluate social bots"
    - "distributed representations of sentences and documents"

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)