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 "textrolls identifying russian trolls on twitter from a textual perspective"):
  Abstract: The online new emerging suspicious users, that usually are called trolls, are one of the main sources of hate, fake, and deceptive online messages. Some agendas are utilizing these harmful users to spread incitement tweets, and as a consequence, the audience get deceived. The challenge in detecting such accounts is that they conceal their identities which make them disguised in social media, adding more difficulty to identify them using just their social network information. Therefore, in this paper, we propose a text-based approach to detect the online trolls such as those that were discovered during the US 2016 presidential elections. Our approach is mainly based on textual features which utilize thematic information, and profiling features to identify the accounts from their way of writing tweets. We deduced the thematic information in a unsupervised way and we show that coupling them with the textual features enhanced the performance of the proposed model. In addition, we find that the proposed profiling features perform the best comparing to the textual features.

Includes members:
  Member "partisanship propaganda and post truth politics quantifying impact in online debate":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "race and religion in online abuse towards uk politicians working paper")
  Member "still out there modeling and identifying russian troll accounts on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning")
  Member "disinformation warfare understanding state sponsored trolls on twitter and their influence on the web":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities")
  Member "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning")
  Member "who falls for online political manipulation":
    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 "tweet2vec character based distributed representations for social media":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "maskdga a black box evasion technique against dga classifiers and adversarial defenses")
  Member "sifting robotic from organic text a natural language approach for detecting automation on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the art of social bots a review and a refined taxonomy")

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.CL(Computation and Language)