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: "characterizing and detecting hateful users on twitter"
  Abstract: Most current approaches to characterize and detect hate speech focus on \textit{content} posted in Online Social Networks. They face shortcomings to collect and annotate hateful speech due to the incompleteness and noisiness of OSN text and the subjectivity of hate speech. These limitations are often aided with constraints that oversimplify the problem, such as considering only tweets containing hate-related words. In this work we partially address these issues by shifting the focus towards \textit{users}. We develop and employ a robust methodology to collect and annotate hateful users which does not depend directly on lexicon and where the users are annotated given their entire profile. This results in a sample of Twitter's retweet graph containing $100,386$ users, out of which $4,972$ were annotated. We also collect the users who were banned in the three months that followed the data collection. We show that hateful users differ from normal ones in terms of their activity patterns, word usage and as well as network structure. We obtain similar results comparing the neighbors of hateful vs. neighbors of normal users and also suspended users vs. active users, increasing the robustness of our analysis. We observe that hateful users are densely connected, and thus formulate the hate speech detection problem as a task of semi-supervised learning over a graph, exploiting the network of connections on Twitter. We find that a node embedding algorithm, which exploits the graph structure, outperforms content-based approaches for the detection of both hateful ($95\%$ AUC vs $88\%$ AUC) and suspended users ($93\%$ AUC vs $88\%$ AUC). Altogether, we present a user-centric view of hate speech, paving the way for better detection and understanding of this relevant and challenging issue.

Connected through hyperedge HE-1 (induced by source paper "from pick up artists to incels a data driven sketch of the manosphere"):
  with members:
    - "what is gab a bastion of free speech or an alt right echo chamber"
    - "the effect of extremist violence on hateful speech online"
    - "analyzing right wing youtube channels hate violence and discrimination"
    - "on the origins of memes by means of fringe web communities"
    - "automated hate speech detection and the problem of offensive language"
    - "deceiving google s perspective api built for detecting toxic comments"
    - "kek cucks and god emperor trump a measurement study of 4chan s politically incorrect forum and its effects on the web"

Connected through hyperedge HE-2 (induced by source paper "deep unified multimodal embeddings for understanding both content and users in social media networks"):
  with members:
    - "integrating text and image determining multimodal document intent in instagram posts"
    - "align2ground weakly supervised phrase grounding guided by image caption alignment"
    - "universal dependency parsing from scratch"
    - "deep learning based recommender system a survey and new perspectives"
    - "exploring the limits of weakly supervised pretraining"
    - "a comprehensive survey of deep learning for image captioning"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "attributed social network embedding"

Connected through hyperedge HE-3 (induced by source paper "trouble on the horizon forecasting the derailment of online conversations as they develop"):
  with members:
    - "something s brewing early prediction of controversy causing posts from discussion features"
    - "forecasting the presence and intensity of hostility on instagram using linguistic and social features"
    - "the effect of extremist violence on hateful speech online"
    - "deep contextualized word representations"
    - "community interaction and conflict on the web"
    - "neural approaches to conversational ai"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "wikiconv a corpus of the complete conversational history of a large online collaborative community"

Connected through hyperedge HE-4 (induced by source paper "temporal effects of unmoderated hate speech in gab"):
  with members:
    - "auditing radicalization pathways on youtube"
    - "what is gab a bastion of free speech or an alt right echo chamber"
    - "all you need is love evading hate speech detection"
    - "challenges in discriminating profanity from hate speech"
    - "the effect of extremist violence on hateful speech online"
    - "hate speech dataset from a white supremacy forum"
    - "thou shalt not hate countering online hate speech"
    - "spread of hate speech in online social media"

Connected through hyperedge HE-5 (induced by source paper "a just and comprehensive strategy for using nlp to address online abuse"):
  with members:
    - "hybrid approaches to detect comments violating macro norms on reddit"
    - "machine learning suites for online toxicity detection"
    - "forecasting the presence and intensity of hostility on instagram using linguistic and social features"
    - "a survey on natural language processing for fake news detection"
    - "style transfer through back translation"
    - "thou shalt not hate countering online hate speech"
    - "extractive adversarial networks high recall explanations for identifying personal attacks in social media posts"
    - "fighting offensive language on social media with unsupervised text style transfer"

Connected through hyperedge HE-6 (induced by source paper "trajectories of blocked community members redemption recidivism and departure"):
  with members:
    - "mind your pov convergence of articles and editors towards wikipedia s neutrality norm"
    - "forecasting the presence and intensity of hostility on instagram using linguistic and social features"
    - "the effect of extremist violence on hateful speech online"
    - "community interaction and conflict on the web"
    - "wikiconv a corpus of the complete conversational history of a large online collaborative community"
    - "the view from the other side the border between controversial speech and harassment on kotaku in action"
    - "conversations gone awry detecting early signs of conversational failure"
    - "automated hate speech detection and the problem of offensive language"

Connected through hyperedge HE-7 (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"
    - "automated hate speech detection and the problem of offensive language"

Connected through hyperedge HE-8 (induced by source paper "race ethnicity and national origin based discrimination in social media and hate crimes across 100 u s cities"):
  with members:
    - "the effect of extremist violence on hateful speech online"
    - "socio spatial self organizing maps using social media to assess relevant geographies for exposure to social processes"
    - "peer to peer hate hate speech instigators and their targets"
    - "hate lingo a target based linguistic analysis of hate speech in social media"
    - "the paradigm shift of social spambots evidence theories and tools for the arms race"
    - "online human bot interactions detection estimation and characterization"
    - "ex machina personal attacks seen at scale"
    - "empath understanding topic signals in large scale text"

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.CY(Computers and Society)