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 "the spread of fake news by social bots"):
  Abstract: The massive spread of fake news has been identified as a major global risk and has been alleged to influence elections and threaten democracies. Communication, cognitive, social, and computer scientists are engaged in efforts to study the complex causes for the viral diffusion of digital misinformation and to develop solutions, while search and social media platforms are beginning to deploy countermeasures. However, to date, these efforts have been mainly informed by anecdotal evidence rather than systematic data. Here we analyze 14 million messages spreading 400 thousand claims on Twitter during and following the 2016 U.S. presidential campaign and election. We find evidence that social bots play a key role in the spread of fake news. Accounts that actively spread misinformation are significantly more likely to be bots. Automated accounts are particularly active in the early spreading phases of viral claims, and tend to target influential users. Humans are vulnerable to this manipulation, retweeting bots who post false news. Successful sources of false and biased claims are heavily supported by social bots. These results suggests that curbing social bots may be an effective strategy for mitigating the spread of online misinformation.

Includes members:
  Member "how algorithmic popularity bias hinders or promotes quality":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on bias and fairness in machine learning")
  Member "limited individual attention and online virality of low quality information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mining social media data for biomedical signals and health related behavior")
  Member "online human bot interactions detection estimation and characterization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning")
  Member "hoaxy a platform for tracking online misinformation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "topology comparison of twitter diffusion networks effectively reveals misleading information")
  Member "botornot a system to evaluate social bots":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning")
  Member "the darpa twitter bot challenge":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning")
  Member "the rise of social bots":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a feature driven approach for identifying pathogenic social media accounts")
  Member "measuring online social bubbles":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "positive algorithmic bias cannot stop fragmentation in homophilic social networks")

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.SI(Social and Information Networks)