human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "measuring gamergate a tale of hate sexism and bullying"
  Abstract: Over the past few years, online aggression and abusive behaviors have occurred in many different forms and on a variety of platforms. In extreme cases, these incidents have evolved into hate, discrimination, and bullying, and even materialized into real-world threats and attacks against individuals or groups. In this paper, we study the Gamergate controversy. Started in August 2014 in the online gaming world, it quickly spread across various social networking platforms, ultimately leading to many incidents of cyberbullying and cyberaggression. We focus on Twitter, presenting a measurement study of a dataset of 340k unique users and 1.6M tweets to study the properties of these users, the content they post, and how they differ from random Twitter users. We find that users involved in this "Twitter war" tend to have more friends and followers, are generally more engaged and post tweets with negative sentiment, less joy, and more hate than random users. We also perform preliminary measurements on how the Twitter suspension mechanism deals with such abusive behaviors. While we focus on Gamergate, our methodology to collect and analyze tweets related to aggressive and bullying activities is of independent interest.

Connected through hyperedge HE-1 (induced by source paper "and we will fight for our race a measurement study of genetic testing conversations on reddit and 4chan"):
  with members:
    - "what is gab a bastion of free speech or an alt right echo chamber"
    - "a quantitative approach to understanding online antisemitism"
    - "the effect of extremist violence on hateful speech online"
    - "mobilizing the trump train understanding collective action in a political trolling community"
    - "analyzing right wing youtube channels hate violence and discrimination"
    - "23andme confirms i m super white analyzing twitter discourse on genetic testing"
    - "on the origins of memes by means of fringe web communities"
    - "characterizing and detecting hateful users on twitter"

Connected through hyperedge HE-2 (induced by source paper "detecting cyberbullying and cyberaggression in social media"):
  with members:
    - "mean birds detecting aggression and bullying on twitter"
    - "poised spotting twitter spam off the beaten paths"
    - "hate is not binary studying abusive behavior of gamergate on twitter"
    - "kek cucks and god emperor trump a measurement study of 4chan s politically incorrect forum and its effects on the web"
    - "a longitudinal measurement study of 4chan s politically incorrect forum and its effect on the web"
    - "deep residual learning for image recognition"
    - "exploring cyberbullying and other toxic behavior in team competition online games"
    - "deep learning and the information bottleneck principle"

Connected through hyperedge HE-3 (induced by source paper "bot electioneering volume visualizing social bot activity during elections"):
  with members:
    - "arming the public with artificial intelligence to counter social bots"
    - "anatomy of an online misinformation network"
    - "the spread of low credibility content by social bots"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "online human bot interactions detection estimation and characterization"
    - "hoaxy a platform for tracking online misinformation"
    - "botornot a system to evaluate social bots"
    - "the rise of social bots"

Connected through hyperedge HE-4 (induced by source paper "tweeting your destiny profiling users in the twitter landscape around an online game"):
  with members:
    - "gendered conversation in a social game streaming platform"

Connected through hyperedge HE-5 (induced by source paper "conversations gone awry detecting early signs of conversational failure"):
  with members:
    - "automated hate speech detection and the problem of offensive language"
    - "asking too much the rhetorical role of questions in political discourse"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "interpreting neural networks to improve politeness comprehension"
    - "a piece of my mind a sentiment analysis approach for online dispute detection"
    - "ex machina personal attacks seen at scale"
    - "conversational markers of constructive discussions"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"

Connected through hyperedge HE-6 (induced by source paper "opinion conflicts an effective route to detect incivility in twitter"):
  with members:
    - "peer to peer hate hate speech instigators and their targets"
    - "hate lingo a target based linguistic analysis of hate speech in social media"
    - "mean birds detecting aggression and bullying on twitter"
    - "deceiving google s perspective api built for detecting toxic comments"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "hate is not binary studying abusive behavior of gamergate on twitter"
    - "analyzing the targets of hate in online social media"
    - "character level convolutional networks for text classification"

Connected through hyperedge HE-7 (induced by source paper "analyzing the hate and counter speech accounts on twitter"):
  with members:
    - "inside the right leaning echo chambers characterizing gab an unmoderated social system"
    - "thou shalt not hate countering online hate speech"
    - "peer to peer hate hate speech instigators and their targets"
    - "like sheep among wolves characterizing hateful users on twitter"
    - "hate lingo a target based linguistic analysis of hate speech in social media"
    - "characterizing and detecting hateful users on twitter"
    - "automated hate speech detection and the problem of offensive language"
    - "deep learning for hate speech detection in tweets"

Connected through hyperedge HE-8 (induced by source paper "analyzing right wing youtube channels hate violence and discrimination"):
  with members:
    - "trollspot detecting misbehavior in commenting platforms"
    - "like sheep among wolves characterizing hateful users on twitter"
    - "semantics derived automatically from language corpora contain human like biases"
    - "empath understanding topic signals in large scale text"
    - "shirtless and dangerous quantifying linguistic signals of gender bias in an online fiction writing community"
    - "participatory militias an analysis of an armed movement s online audience"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

Question: Please tell me which class the center node 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)