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: "truthy mapping the spread of astroturf in microblog streams"
  Abstract: Online social media are complementing and in some cases replacing person-to-person social interaction and redefining the diffusion of information. In particular, microblogs have become crucial grounds on which public relations, marketing, and political battles are fought. We demonstrate a web service that tracks political memes in Twitter and helps detect astroturfing, smear campaigns, and other misinformation in the context of U.S. political elections. We also present some cases of abusive behaviors uncovered by our service. Our web service is based on an extensible framework that will enable the real-time analysis of meme diffusion in social media by mining, visualizing, mapping, classifying, and modeling massive streams of public microblogging events.

Connected through hyperedge HE-1 (induced by source paper "topology comparison of twitter diffusion networks effectively reveals misleading information"):
  with members:
    - "false news on social media a data driven survey"
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "fake news detection on social media using geometric deep learning"
    - "an information theoretic all scales approach to comparing networks"
    - "anatomy of an online misinformation network"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "the spread of low credibility content by social bots"
    - "validation of twitter opinion trends with national polling aggregates hillary clinton vs donald trump"

Connected through hyperedge HE-2 (induced by source paper "the mass fake news and cognition security"):
  with members:
    - "the role of user profile for fake news detection"
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "studying fake news via network analysis detection and mitigation"
    - "techniques for interpretable machine learning"
    - "declare debunking fake news and false claims using evidence aware deep learning"
    - "fake news a survey of research detection methods and opportunities"
    - "opinion dynamics with varying susceptibility to persuasion"
    - "deepinf social influence prediction with deep learning"

Connected through hyperedge HE-3 (induced by source paper "bots elections and social media a brief overview"):
  with members:
    - "the history of digital spam"
    - "red bots do it better comparative analysis of social bot partisan behavior"
    - "arming the public with artificial intelligence to counter social bots"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "deep neural networks for bot detection"
    - "measuring bot and human behavioral dynamics"
    - "who falls for online political manipulation"
    - "the spread of low credibility content by social bots"

Connected through hyperedge HE-4 (induced by source paper "hateful people or hateful bots detection and characterization of bots spreading religious hatred in arabic social media"):
  with members:
    - "universal dependency parsing from scratch"
    - "mind your pov convergence of articles and editors towards wikipedia s neutrality norm"
    - "deep learning for hate speech detection in tweets"
    - "online human bot interactions detection estimation and characterization"
    - "botornot a system to evaluate social bots"
    - "dissecting a social botnet growth content and influence in twitter"
    - "analyzing the targets of hate in online social media"
    - "the rise of social bots"

Connected through hyperedge HE-5 (induced by source paper "using deep networks and transfer learning to address disinformation"):
  with members:
    - "automatic detection of fake news"
    - "hoaxy a platform for tracking online misinformation"
    - "exploring the limits of language modeling"
    - "character level convolutional networks for text classification"
    - "computational fact checking from knowledge networks"
    - "collective attention in the age of mis information"

Connected through hyperedge HE-6 (induced by source paper "hunting for troll comments in news community forums"):
  with members:
    - "crowdsourcing a word emotion association lexicon"
    - "scikit learn machine learning in python"
    - "finding deceptive opinion spam by any stretch of the imagination"

Connected through hyperedge HE-7 (induced by source paper "deception strategies and threats for online discussions"):
  with members:
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "anatomy of an online misinformation network"
    - "the spread of low credibility content by social bots"
    - "soc2seq social embedding meets conversation model"
    - "reuters tracer toward automated news production using large scale social media data"
    - "early detection of promoted campaigns on social media"
    - "discovery retrieval and analysis of star wars botnet in twitter"
    - "limited individual attention and online virality of low quality information"

Connected through hyperedge HE-8 (induced by source paper "scholarly twitter metrics"):
  with members:
    - "a systematic identification and analysis of scientists on twitter"
    - "grand challenges in altmetrics heterogeneity data quality and dependencies"
    - "botornot a system to evaluate social bots"
    - "scholarly use of social media and altmetrics a review of the literature"
    - "the rise of social bots"
    - "when is an article actually published an analysis of online availability publication and indexation dates"
    - "differences in personal and professional tweets of scholars"
    - "influence of study type on twitter activity for medical research papers"

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)