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 "detecting cyberbullying and cyberaggression in social media"):
  Abstract: Cyberbullying and cyberaggression are increasingly worrisome phenomena affecting people across all demographics. More than half of young social media users worldwide have been exposed to such prolonged and/or coordinated digital harassment. Victims can experience a wide range of emotions, with negative consequences such as embarrassment, depression, isolation from other community members, which embed the risk to lead to even more critical consequences, such as suicide attempts. #R##N#In this work, we take the first concrete steps to understand the characteristics of abusive behavior in Twitter, one of today's largest social media platforms. We analyze 1.2 million users and 2.1 million tweets, comparing users participating in discussions around seemingly normal topics like the NBA, to those more likely to be hate-related, such as the Gamergate controversy, or the gender pay inequality at the BBC station. We also explore specific manifestations of abusive behavior, i.e., cyberbullying and cyberaggression, in one of the hate-related communities (Gamergate). We present a robust methodology to distinguish bullies and aggressors from normal Twitter users by considering text, user, and network-based attributes. Using various state-of-the-art machine learning algorithms, we classify these accounts with over 90% accuracy and AUC. Finally, we discuss the current status of Twitter user accounts marked as abusive by our methodology, and study the performance of potential mechanisms that can be used by Twitter to suspend users in the future.

Includes members:
  Member "mean birds detecting aggression and bullying on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-1 (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-2 (induced by source paper "and we will fight for our race a measurement study of genetic testing conversations on reddit and 4chan")
  Member "poised spotting twitter spam off the beaten paths":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ties temporal interaction embeddings for enhancing social media integrity at facebook")
  Member "hate is not binary studying abusive behavior of gamergate on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities")
  Member "kek cucks and god emperor trump a measurement study of 4chan s politically incorrect forum and its effects on the web":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "from pick up artists to incels a data driven sketch of the manosphere")
  Member "a longitudinal measurement study of 4chan s politically incorrect forum and its effect on the web":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "understanding abuse a typology of abusive language detection subtasks")
  Member "deep residual learning for image recognition":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "discrimination aware network pruning for deep model compression")
  Member "exploring cyberbullying and other toxic behavior in team competition online games":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "political discussions in homogeneous and cross cutting communication spaces")

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)