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: "a survey of prediction using social media"
  Abstract: Social media comprises interactive applications and platforms for creating, sharing and exchange of user-generated contents. The past ten years have brought huge growth in social media, especially online social networking services, and it is changing our ways to organize and communicate. It aggregates opinions and feelings of diverse groups of people at low cost. Mining the attributes and contents of social media gives us an opportunity to discover social structure characteristics, analyze action patterns qualitatively and quantitatively, and sometimes the ability to predict future human related events. In this paper, we firstly discuss the realms which can be predicted with current social media, then overview available predictors and techniques of prediction, and finally discuss challenges and possible future directions.

Connected through hyperedge HE-1 (induced by source paper "using social media to predict the future a systematic literature review"):
  with members:
    - "what the language you tweet says about your occupation"
    - "mining online social data for detecting social network mental disorders"
    - "sentiment aggregate functions for political opinion polling using microblog streams"
    - "using user generated online photos to estimate and monitor air pollution in major cities"
    - "beating the news with embers forecasting civil unrest using open source indicators"
    - "predicting crowd behavior with big public data"
    - "big questions for social media big data representativeness validity and other methodological pitfalls"
    - "geotagging one hundred million twitter accounts with total variation minimization"

Connected through hyperedge HE-2 (induced by source paper "intelligent disaster response via social media analysis a survey"):
  with members:
    - "quotus the structure of political media coverage as revealed by quoting patterns"
    - "finding eyewitness tweets during crises"
    - "processing social media messages in mass emergency a survey"
    - "dynamical classes of collective attention in twitter"
    - "truthy mapping the spread of astroturf in microblog streams"
    - "predicting the popularity of online content"

Connected through hyperedge HE-3 (induced by source paper "twitterpaul extracting and aggregating twitter predictions"):
  with members:
    - "an empirical comparison of algorithms for aggregating expert predictions"
    - "why watching movie tweets won t tell the whole story"
    - "i wanted to predict elections with twitter and all i got was this lousy paper a balanced survey on election prediction using twitter data"
    - "twitter mood predicts the stock market"

Connected through hyperedge HE-4 (induced by source paper "i wanted to predict elections with twitter and all i got was this lousy paper a balanced survey on election prediction using twitter data"):
  with members:
    - "twitter mood predicts the stock market"

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)