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 "don t feed the troll detecting troll behavior via inverse reinforcement learning"):
  Abstract: Since the 2016 US Presidential election, social media abuse has been eliciting massive concern in the academic community and beyond. Preventing and limiting the malicious activity of users, such as trolls and bots, in their manipulation campaigns is of paramount importance for the integrity of democracy, public health, and more. However, the automated detection of troll accounts is an open challenge. In this work, we propose an approach based on Inverse Reinforcement Learning (IRL) to capture troll behavior and identify troll accounts. We employ IRL to infer a set of online incentives that may steer user behavior, which in turn highlights behavioral differences between troll and non-troll accounts, enabling their accurate classification. We report promising results: the IRL-based approach is able to accurately detect troll accounts (AUC=89.1%). The differences in the predictive features between the two classes of accounts enables a principled understanding of the distinctive behaviors reflecting the incentives trolls and non-trolls respond to.

Includes members:
  Member "analysing user identity via time sensitive semantic edit distance t sed a case study of russian trolls on twitter":
    also connected through other hyperedges:
      (none)
  Member "still out there modeling and identifying russian troll accounts on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "red bots do it better comparative analysis of social bot partisan behavior")
  Member "red bots do it better comparative analysis of social bot partisan behavior":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bots elections and social media a brief overview")
  Member "arming the public with artificial intelligence to counter social bots":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how many bots are you following")
  Member "senator we sell ads analysis of the 2016 russian facebook ads campaign":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "perils and challenges of social media and election manipulation analysis the 2018 us midterms")
  Member "characterizing the 2016 russian ira influence campaign":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "debiasing community detection the importance of lowly connected nodes")
  Member "who let the trolls out towards understanding state sponsored trolls":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the pushshift reddit dataset")
  Member "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "topology comparison of twitter diffusion networks effectively reveals misleading information")

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)