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: "twitter sentiment analysis applied to finance a case study in the retail industry"
  Abstract: This paper presents a financial analysis over Twitter sentiment analytics extracted from listed retail brands. We investigate whether there is statistically-significant information between the Twitter sentiment and volume, and stock returns and volatility. Traditional newswires are also considered as a proxy for the market sentiment for comparative purpose. The results suggest that social media is indeed a valuable source in the analysis of the financial dynamics in the retail sector even when compared to mainstream news such as the Wall Street Journal and Dow Jones Newswires.

Connected through hyperedge HE-1 (induced by source paper "twitter sentiment around the earnings announcement events"):
  with members:
    - "multilingual twitter sentiment classification the role of human annotators"
    - "the effects of twitter sentiment on stock price returns"
    - "sentiment of emojis"
    - "crowds on wall street extracting value from social investing platforms"
    - "twitter mood predicts the stock market"

Connected through hyperedge HE-2 (induced by source paper "the effects of twitter sentiment on stock price returns"):
  with members:
    - "emotional dynamics in the age of misinformation"
    - "twitter sentiment analysis lexicon method machine learning method and their combination"
    - "cohesiveness in financial news and its relation to market volatility"
    - "where in the world are you geolocation and language identification in twitter"
    - "the royal birth of 2013 analysing and visualising public sentiment in the uk using twitter"
    - "dynamical classes of collective attention in twitter"
    - "twitter mood predicts the stock market"

Connected through hyperedge HE-3 (induced by source paper "twitter sentiment analysis lexicon method machine learning method and their combination"):
  with members:
    - "tripartite graph clustering for dynamic sentiment analysis on social media"
    - "nrc canada building the state of the art in sentiment analysis of tweets"
    - "a new anew evaluation of a word list for sentiment analysis in microblogs"
    - "twitter mood predicts the stock market"
    - "thumbs up or thumbs down semantic orientation applied to unsupervised classification of reviews"
    - "thumbs up sentiment classification using machine learning techniques"

Connected through hyperedge HE-4 (induced by source paper "in quest of significance identifying types of twitter sentiment events that predict spikes in sales"):
  with members:
    - "using twitter to predict sales a case study"
    - "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.CY(Computers and Society)