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: "catching zika fever application of crowdsourcing and machine learning for tracking health misinformation on twitter"
  Abstract: In February 2016, World Health Organization declared the Zika outbreak a Public Health Emergency of International Concern. With developing evidence it can cause birth defects, and the Summer Olympics coming up in the worst affected country, Brazil, the virus caught fire on social media. In this work, use Zika as a case study in building a tool for tracking the misinformation around health concerns on Twitter. We collect more than 13 million tweets -- spanning the initial reports in February 2016 and the Summer Olympics -- regarding the Zika outbreak and track rumors outlined by the World Health Organization and Snopes fact checking website. The tool pipeline, which incorporates health professionals, crowdsourcing, and machine learning, allows us to capture health-related rumors around the world, as well as clarification campaigns by reputable health organizations. In the case of Zika, we discover an extremely bursty behavior of rumor-related topics, and show that, once the questionable topic is detected, it is possible to identify rumor-bearing tweets using automated techniques. Thus, we illustrate insights the proposed tools provide into potentially harmful information on social media, allowing public health researchers and practitioners to respond with a targeted and timely action.

Connected through hyperedge HE-1 (induced by source paper "advertisers jump on coronavirus bandwagon politics news and business"):
  with members:
    - "social bots for online public health interventions"

Connected through hyperedge HE-2 (induced by source paper "fake cures user centric modeling of health misinformation in social media"):
  with members:
    - "the spread of low credibility content by social bots"
    - "using facebook ads audiences for global lifestyle disease surveillance promises and limitations"
    - "the spread of fake news by social bots"
    - "halal culture on instagram"
    - "fake news detection on social media a data mining perspective"
    - "fetishizing food in digital age foodporn around the world"
    - "a cross platform collection of social network profiles"
    - "hoaxy a platform for tracking online misinformation"

Connected through hyperedge HE-3 (induced by source paper "information sources and needs in the obesity and diabetes twitter discourse"):
  with members:
    - "fetishizing food in digital age foodporn around the world"
    - "computational fact checking from knowledge networks"
    - "foodporn obesity patterns in culinary interactions"
    - "information community and action how nonprofit organizations use social media"

Connected through hyperedge HE-4 (induced by source paper "differences between health related news articles from reliable and unreliable media"):
  with members:
    - "fake cures user centric modeling of health misinformation in social media"
    - "diving deep into clickbaits who use them to what extents in which topics with what effects"
    - "fake news detection on social media a data mining perspective"

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)