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: "what do the us west coast public libraries post on twitter"
  Abstract: Twitter has provided a great opportunity for public libraries to disseminate information for a variety of purposes. Twitter data have been applied in different domains such as health, politics, and history. There are thousands of public libraries in the US, but no study has yet investigated the content of their social media posts like tweets to find their interests. Moreover, traditional content analysis of Twitter content is not an efficient task for exploring thousands of tweets. Therefore, there is a need for automatic methods to overcome the limitations of manual methods. This paper proposes a computational approach to collecting and analyzing using Twitter Application Programming Interfaces (API) and investigates more than 138,000 tweets from 48 US west coast libraries using topic modeling. We found 20 topics and assigned them to five categories including public relations, book, event, training, and social good. Our results show that the US west coast libraries are more interested in using Twitter for public relations and book-related events. This research has both practical and theoretical applications for libraries as well as other organizations to explore social media actives of their customer and themselves.

Connected through hyperedge HE-1 (induced by source paper "twitter speaks a case of national disaster situational awareness"):
  with members:
    - "characterizing transgender health issues in twitter"
    - "social media analysis for organizations us northeastern public and state libraries case study"
    - "characterizing diseases and disorders in gay users tweets"
    - "mining public opinion about economic issues twitter and the u s presidential election"
    - "life never matters in the democrats mind examining strategies of retweeted social bots during a mass shooting event"
    - "applications of deep learning and reinforcement learning to biological data"
    - "deep learning for iot big data and streaming analytics a survey"
    - "computational content analysis of negative tweets for obesity diet diabetes and exercise"

Connected through hyperedge HE-2 (induced by source paper "hidden in plain sight for too long using text mining techniques to shine a light on workplace sexism and sexual harassment"):
  with members:
    - "twitter speaks a case of national disaster situational awareness"
    - "characterizing transgender health issues in twitter"
    - "computational content analysis of negative tweets for obesity diet diabetes and exercise"

Connected through hyperedge HE-3 (induced by source paper "application of fuzzy clustering for text data dimensionality reduction"):
  with members:
    - "twitter speaks a case of national disaster situational awareness"
    - "characterizing transgender health issues in twitter"
    - "learning in high dimensional multimedia data the state of the art"

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)