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 "opinion conflicts an effective route to detect incivility in twitter"):
  Abstract: In Twitter, there is a rising trend in abusive behavior which often leads to incivility. This trend is affecting users mentally and as a result they tend to leave Twitter and other such social networking sites thus depleting the active user base. In this paper, we study factors associated with incivility. We observe that the act of incivility is highly correlated with the opinion differences between the account holder (i.e., the user writing the incivil tweet) and the target (i.e., the user for whom the incivil tweet is meant for or targeted), toward a named entity. We introduce a character level CNN model and incorporate the entity-specific sentiment information for efficient incivility detection which significantly outperforms multiple baseline methods achieving an impressive accuracy of 93.3% (4.9% improvement over the best baseline). In a post-hoc analysis, we also study the behavioral aspects of the targets and account holders and try to understand the reasons behind the incivility incidents. Interestingly, we observe that there are strong signals of repetitions in incivil behavior. In particular, we find that there are a significant fraction of account holders who act as repeat offenders - attacking the targets even more than 10 times. Similarly, there are also targets who get targeted multiple times. In general, the targets are found to have higher reputation scores than the account holders.

Includes members:
  Member "peer to peer hate hate speech instigators and their targets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a benchmark dataset for learning to intervene in online hate speech")
  Member "hate lingo a target based linguistic analysis of hate speech in social media":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a framework for the computational linguistic analysis of dehumanization")
  Member "mean birds detecting aggression and bullying on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "angry birds flock together aggression propagation on social media")
  Member "measuring gamergate a tale of hate sexism and bullying":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "and we will fight for our race a measurement study of genetic testing conversations on reddit and 4chan")
  Member "deceiving google s perspective api built for detecting toxic comments":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "wac a corpus of wikipedia conversations for online abuse detection")
  Member "anyone can become a troll causes of trolling behavior in online discussions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "ten social dimensions of conversations and relationships")
  Member "hate is not binary studying abusive behavior of gamergate on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities")
  Member "analyzing the targets of hate in online social media":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a framework for the computational linguistic analysis of dehumanization")

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)