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: "anyone can become a troll causes of trolling behavior in online discussions"
  Abstract: In online communities, antisocial behavior such as trolling disrupts constructive discussion. While prior work suggests that trolling behavior is confined to a vocal and antisocial minority, we demonstrate that ordinary people can engage in such behavior as well. We propose two primary trigger mechanisms: the individual's mood, and the surrounding context of a discussion (e.g., exposure to prior trolling behavior). Through an experiment simulating an online discussion, we find that both negative mood and seeing troll posts by others significantly increases the probability of a user trolling, and together double this probability. To support and extend these results, we study how these same mechanisms play out in the wild via a data-driven, longitudinal analysis of a large online news discussion community. This analysis exposes temporal mood effects, and explores long range patterns of repeated exposure to trolling. A predictive model of trolling behavior reveals that mood and discussion context together can explain trolling behavior better than an individual's history of trolling. These results combine to suggest that ordinary people can, under the right circumstances, behave like trolls.

Connected through hyperedge HE-1 (induced by source paper "ten social dimensions of conversations and relationships"):
  with members:
    - "firsthand opiates abuse on social media monitoring geospatial patterns of interest through a digital cohort"
    - "the language of dialogue is complex"
    - "coloring in the links capturing social ties as they are perceived"
    - "the anatomy of reddit an overview of academic research"
    - "community interaction and conflict on the web"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "caveat emptor computational social science large scale missing data in a widely published reddit corpus"
    - "automated hate speech detection and the problem of offensive language"

Connected through hyperedge HE-2 (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-3 (induced by source paper "learning from fact checkers analysis and generation of fact checking language"):
  with members:
    - "homogeneity based transmissive process to model true and false news in social networks"
    - "the rise of guardians fact checking url recommendation to combat fake news"
    - "declare debunking fake news and false claims using evidence aware deep learning"
    - "fever a large scale dataset for fact extraction and verification"
    - "variational memory encoder decoder"
    - "fact checking in community forums"
    - "automated hate speech detection and the problem of offensive language"
    - "liar liar pants on fire a new benchmark dataset for fake news detection"

Connected through hyperedge HE-4 (induced by source paper "predicting dynamic embedding trajectory in temporal interaction networks"):
  with members:
    - "hierarchical temporal convolutional networks for dynamic recommender systems"
    - "deep learning based recommender system a survey and new perspectives"
    - "dylink2vec effective feature representation for link prediction in dynamic networks"
    - "network embedding as matrix factorization unifying deepwalk line pte and node2vec"
    - "leveraging friendship networks for dynamic link prediction in social interaction networks"
    - "dyngem deep embedding method for dynamic graphs"
    - "community interaction and conflict on the web"
    - "graph embedding techniques applications and performance a survey"

Connected through hyperedge HE-5 (induced by source paper "consequential ranking algorithms and long term welfare"):
  with members:
    - "policy learning for fairness in ranking"
    - "delayed impact of fair machine learning"
    - "reinforcement learning and control as probabilistic inference tutorial and review"
    - "a short term intervention for long term fairness in the labor market"
    - "equity of attention amortizing individual fairness in rankings"
    - "from fair decision making to social equality"
    - "fairness of exposure in rankings"
    - "deconvolving feedback loops in recommender systems"

Connected through hyperedge HE-6 (induced by source paper "intergroup contact in the wild characterizing language differences between intergroup and single group members in nba related discussion forums"):
  with members:
    - "this is why we play characterizing online fan communities of the nba teams"
    - "community interaction and conflict on the web"
    - "extracting inter community conflicts in reddit"
    - "me my echo chamber and i introspection on social media polarization"
    - "automated hate speech detection and the problem of offensive language"
    - "all who wander on the prevalence and characteristics of multi community engagement"
    - "antisocial behavior in online discussion communities"
    - "stfu noob predicting crowdsourced decisions on toxic behavior in online games"

Connected through hyperedge HE-7 (induced by source paper "build it break it fix it for dialogue safety robustness from adversarial human attack"):
  with members:
    - "the second conversational intelligence challenge convai2"
    - "semeval 2019 task 6 identifying and categorizing offensive language in social media offenseval"
    - "all you need is love evading hate speech detection"
    - "large scale gan training for high fidelity natural image synthesis"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "automated hate speech detection and the problem of offensive language"
    - "deceiving google s perspective api built for detecting toxic comments"
    - "ethical challenges in data driven dialogue systems"

Connected through hyperedge HE-8 (induced by source paper "sentiment dynamics in social media news channels"):
  with members:
    - "automated hate speech detection and the problem of offensive language"
    - "breaking the news first impressions matter on online news"
    - "characterizing the life cycle of online news stories using social media reactions"
    - "how community feedback shapes user behavior"
    - "the pulse of news in social media forecasting popularity"
    - "good friends bad news affect and virality in twitter"
    - "using a model of social dynamics to predict popularity of news"
    - "predicting the popularity of online content"

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)