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: "botornot a system to evaluate social bots"
  Abstract: While most online social media accounts are controlled by humans, these platforms also host automated agents called social bots or sybil accounts. Recent literature reported on cases of social bots imitating humans to manipulate discussions, alter the popularity of users, pollute content and spread misinformation, and even perform terrorist propaganda and recruitment actions. Here we present BotOrNot, a publicly-available service that leverages more than one thousand features to evaluate the extent to which a Twitter account exhibits similarity to the known characteristics of social bots. Since its release in May 2014, BotOrNot has served over one million requests via our website and APIs.

Connected through hyperedge HE-1 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning"):
  with members:
    - "analysing user identity via time sensitive semantic edit distance t sed a case study of russian trolls on twitter"
    - "still out there modeling and identifying russian troll accounts on twitter"
    - "red bots do it better comparative analysis of social bot partisan behavior"
    - "arming the public with artificial intelligence to counter social bots"
    - "senator we sell ads analysis of the 2016 russian facebook ads campaign"
    - "characterizing the 2016 russian ira influence campaign"
    - "who let the trolls out towards understanding state sponsored trolls"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"

Connected through hyperedge HE-2 (induced by source paper "how many bots are you following"):
  with members:
    - "do you really follow them automatic detection of credulous twitter users"
    - "arming the public with artificial intelligence to counter social bots"
    - "fake news a survey of research detection methods and opportunities"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "the paradigm shift of social spambots evidence theories and tools for the arms race"
    - "online human bot interactions detection estimation and characterization"
    - "botivist calling volunteers to action using online bots"
    - "the rise of social bots"

Connected through hyperedge HE-3 (induced by source paper "uncovering coordinated networks on social media"):
  with members:
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "identifying and analyzing cryptocurrency manipulations in social media"
    - "bot electioneering volume visualizing social bot activity during elections"
    - "an unsupervised approach to detect spam campaigns that use botnets on twitter"
    - "the spread of low credibility content by social bots"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "the paradigm shift of social spambots evidence theories and tools for the arms race"
    - "online human bot interactions detection estimation and characterization"

Connected through hyperedge HE-4 (induced by source paper "ginger cannot cure cancer battling fake health news with a comprehensive data repository"):
  with members:
    - "nela gt 2018 a large multi labelled news dataset for the study of misinformation in news articles"
    - "propagation from deceptive news sources who shares how much how evenly and how quickly"
    - "fakenewsnet a data repository with news content social context and dynamic information for studying fake news on social media"
    - "fake news a survey of research detection methods and opportunities"
    - "liar liar pants on fire a new benchmark dataset for fake news detection"
    - "beyond news contents the role of social context for fake news detection"
    - "csi a hybrid deep model for fake news detection"
    - "some like it hoax automated fake news detection in social networks"

Connected through hyperedge HE-5 (induced by source paper "a multi layer approach to disinformation detection on twitter"):
  with members:
    - "investigating italian disinformation spreading on twitter in the context of 2019 european elections"
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "fake news detection on social media using geometric deep learning"
    - "defending against neural fake news"
    - "anatomy of an online misinformation network"
    - "polarization and fake news early warning of potential misinformation targets"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "the spread of low credibility content by social bots"

Connected through hyperedge HE-6 (induced by source paper "twitter bot detection using bidirectional long short term memory neural networks and word embeddings"):
  with members:
    - "on the use of bert for neural machine translation"
    - "dual fofe net neural models for entity linking with pagerank"
    - "online human bot interactions detection estimation and characterization"
    - "dna inspired online behavioral modeling and its application to spambot detection"
    - "the rise of social bots"
    - "speech recognition with deep recurrent neural networks"
    - "distributed representations of words and phrases and their compositionality"
    - "improving neural networks by preventing co adaptation of feature detectors"

Connected through hyperedge HE-7 (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"
    - "disinformation warfare understanding state sponsored trolls on twitter and their influence on the web"
    - "mobilizing the trump train understanding collective action in a political trolling community"
    - "false information on web and social media a survey"

Connected through hyperedge HE-8 (induced by source paper "combating fake news a survey on identification and mitigation techniques"):
  with members:
    - "the web of false information rumors fake news hoaxes clickbait and various other shenanigans"
    - "adversarial classification on social networks"
    - "all in one multi task learning for rumour verification"
    - "fakenewsnet a data repository with news content social context and dynamic information for studying fake news on social media"
    - "fever a large scale dataset for fact extraction and verification"
    - "detection and resolution of rumours in social media a survey"
    - "me my echo chamber and i introspection on social media polarization"
    - "fake news detection in social networks via crowd signals"

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)