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: "can whatsapp counter misinformation by limiting message forwarding"
  Abstract: WhatsApp is the most popular messaging app in the world. The closed nature of the app summed to the ease of transferring multimedia and sharing information to large-scale groups make WhatsApp unique among other platforms, where an anonymous encrypted message can be viral, reaching multiple users in a short period of time. The personal feeling and immediacy of messages directly delivered in the user's phone was extensively abused in WhatsApp to spread unfounded rumors and create misinformation campaigns. WhatsApp has been deploying contention measures to mitigate this problem, such as reducing the limit for forwarding a message to five. Despite the welcomed effort in counter the problem, there is no evidence so far on the real effectiveness of such restrictions. In this work, we propose a methodology to evaluate the effectiveness of such contention measures on the spreading of misinformation circulating on WhatsApp. We use an epidemiological model and real data gathered from WhatsApp in Brazil, India and Indonesia to assess the impact of limiting virality features in this kind of network. Our results suggest that the current efforts deployed by WhatsApp can offer delays on the information spread, but they are ineffective in blocking the propagation of misinformation campaigns in public groups.

Connected through hyperedge HE-1 (induced by source paper "the pushshift telegram dataset"):
  with members:
    - "nela gt 2018 a large multi labelled news dataset for the study of misinformation in news articles"
    - "large scale crowdsourcing and characterization of twitter abusive behavior"
    - "whatsapp doc a first look at whatsapp public group data"

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)