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: "online social media in the syria conflict encompassing the extremes and the in betweens"
  Abstract: The Syria conflict has been described as the most socially mediated in history, with online social media playing a particularly important role. At the same time, the ever-changing landscape of the conflict leads to difficulties in applying analytical approaches taken by other studies of online political activism. Therefore, in this paper, we use an approach that does not require strong prior assumptions or the proposal of an advance hypothesis to analyze Twitter and YouTube activity of a range of protagonists to the conflict, in an attempt to reveal additional insights into the relationships between them. By means of a network representation that combines multiple data views, we uncover communities of accounts falling into four categories that broadly reflect the situation on the ground in Syria. A detailed analysis of selected communities within the anti-regime categories is provided, focusing on their central actors, preferred online platforms, and activity surrounding "real world" events. Our findings indicate that social media activity in Syria is considerably more convoluted than reported in many other studies of online political activism, suggesting that alternative analytical approaches can play an important role in this type of scenario.

Connected through hyperedge HE-1 (induced by source paper "social influence and radicalization a social data analytics study"):
  with members:
    - "adaptive influence maximization in dynamic social networks"
    - "data curation apis"
    - "least cost influence maximization across multiple social networks"
    - "failedrevolutions using twitter to study the antecedents of isis support"
    - "klout score measuring influence across multiple social networks"
    - "big data and cross document coreference resolution current state and future opportunities"
    - "maximizing social influence in nearly optimal time"
    - "on budgeted influence maximization in social networks"

Connected through hyperedge HE-2 (induced by source paper "voice for the voiceless active sampling to detect comments supporting the rohingyas"):
  with members:
    - "kashmir a computational analysis of the voice of peace"
    - "sentiment analysis of comments on rohingya movement with support vector machine"
    - "unsupervised learning of sentence embeddings using compositional n gram features"
    - "automated hate speech detection and the problem of offensive language"
    - "deep learning for hate speech detection in tweets"
    - "inducing domain specific sentiment lexicons from unlabeled corpora"
    - "enriching word vectors with subword information"
    - "bag of tricks for efficient text classification"

Connected through hyperedge HE-3 (induced by source paper "failedrevolutions using twitter to study the antecedents of isis support"):
  with members:
    - "is twitter a public sphere for online conflicts a cross ideological and cross hierarchical look"
    - "content and network dynamics behind egyptian political polarization on twitter"
    - "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)