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: "u s religious landscape on twitter"
  Abstract: Religiosity is a powerful force shaping human societies, affecting domains as diverse as economic growth or the ability to cope with illness. As more religious leaders and organizations as well as believers start using social networking sites (e.g., Twitter, Facebook), online activities become important extensions to traditional religious rituals and practices. However, there has been lack of research on religiosity in online social networks. This paper takes a step toward the understanding of several important aspects of religiosity on Twitter, based on the analysis of more than 250k U.S. users who self-declared their religions/belief, including Atheism, Buddhism, Christianity, Hinduism, Islam, and Judaism. Specifically, (i) we examine the correlation of geographic distribution of religious people between Twitter and offline surveys. (ii) We analyze users' tweets and networks to identify discriminative features of each religious group, and explore supervised methods to identify believers of different religions. (iii) We study the linkage preference of different religious groups, and observe a strong preference of Twitter users connecting to others sharing the same religion.

Connected through hyperedge HE-1 (induced by source paper "modeling islamist extremist communications on social media using contextual dimensions religion ideology and hate"):
  with members:
    - "predictive analysis on twitter techniques and applications"
    - "the rise of jihadist propaganda on social networks"
    - "domain adapted word embeddings for improved sentiment classification"
    - "what s ur type contextualized classification of user types in marijuana related communications using compositional multiview embedding"
    - "probabilistic fasttext for multi sense word embeddings"
    - "automated hate speech detection and the problem of offensive language"
    - "predicting online extremism content adopters and interaction reciprocity"
    - "enriching word vectors with subword information"

Connected through hyperedge HE-2 (induced by source paper "arabs and atheism religious discussions in the arab twittersphere"):
  with members:
    - "failedrevolutions using twitter to study the antecedents of isis support"

Connected through hyperedge HE-3 (induced by source paper "the road to popularity the dilution of growing audience on twitter"):
  with members:
    - "characterizing information diets of social media users"
    - "distinguishing between topical and non topical information diffusion mechanisms in social media"

Connected through hyperedge HE-4 (induced by source paper "whom should we sense in social sensing analyzing which users work best for social media now casting"):
  with members:
    - "is the sample good enough comparing data from twitter s streaming api with twitter s firehose"

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)