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: "on the influence of social bots in online protests"
  Abstract: Social bots can affect online communication among humans. We study this phenomenon by focusing on #YaMeCanse, the most active protest hashtag in the history of Twitter in Mexico. Accounts using the hashtag are classified using the BotOrNot bot detection tool. Our preliminary analysis suggests that bots played a critical role in disrupting online communication about the protest movement.

Connected through hyperedge HE-1 (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"
    - "botornot a system to evaluate social bots"

Connected through hyperedge HE-2 (induced by source paper "arming the public with artificial intelligence to counter social bots"):
  with members:
    - "anatomy of an online misinformation network"
    - "deep neural networks for bot detection"
    - "an unsupervised approach to detect spam campaigns that use botnets on twitter"
    - "deception strategies and threats for online discussions"
    - "the spread of low credibility content by social bots"
    - "a deep reinforcement learning chatbot"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "early detection of promoted campaigns on social media"

Connected through hyperedge HE-3 (induced by source paper "information pollution by social bots"):
  with members:
    - "arming the public with artificial intelligence to counter social bots"
    - "the role of bot squads in the political propaganda on twitter"
    - "identifying and analyzing cryptocurrency manipulations in social media"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "deep neural networks for bot detection"
    - "quantifying biases in online information exposure"
    - "the spread of low credibility content by social bots"
    - "how algorithmic popularity bias hinders or promotes quality"

Connected through hyperedge HE-4 (induced by source paper "boostnet bootstrapping detection of socialbots and a case study from guatemala"):
  with members:
    - "socialbots whitewashing contested elections a case study from honduras"
    - "early detection of promoted campaigns on social media"
    - "online human bot interactions detection estimation and characterization"
    - "botornot a system to evaluate social bots"
    - "the rise of social bots"
    - "sifting robotic from organic text a natural language approach for detecting automation on twitter"

Connected through hyperedge HE-5 (induced by source paper "who falls for online political manipulation"):
  with members:
    - "arming the public with artificial intelligence to counter social bots"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "early detection of promoted campaigns on social media"
    - "the paradigm shift of social spambots evidence theories and tools for the arms race"
    - "botornot a system to evaluate social bots"
    - "the darpa twitter bot challenge"
    - "the rise of social bots"

Connected through hyperedge HE-6 (induced by source paper "disinformation and social bot operations in the run up to the 2017 french presidential election"):
  with members:
    - "the paradigm shift of social spambots evidence theories and tools for the arms race"
    - "botivist calling volunteers to action using online bots"
    - "the darpa twitter bot challenge"
    - "the rise of social bots"
    - "science vs conspiracy collective narratives in the age of misinformation"
    - "measuring emotional contagion in social media"
    - "quantifying the effect of sentiment on information diffusion in social media"
    - "reverse engineering socialbot infiltration strategies in twitter"

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.CY(Computers and Society)