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: "sentiment cascades in the 15m movement"
  Abstract: Recent grassroots movements have suggested that online social networks might play a key role in their organization, as adherents have a fast, many-to-many, communication channel to help coordinate their mobilization. The structure and dynamics of the networks constructed from the digital traces of protesters have been analyzed to some extent recently. However, less effort has been devoted to the analysis of the semantic content of messages exchanged during the protest. Using the data obtained from a microblogging service during the brewing and active phases of the 15M movement in Spain, we perform the first large scale test of theories on collective emotions and social interaction in collective actions. Our findings show that activity and information cascades in the movement are larger in the presence of negative collective emotions and when users express themselves in terms related to social content. At the level of individual participants, our results show that their social integration in the movement, as measured through social network metrics, increases with their level of engagement and of expression of negativity. Our findings show that non-rational factors play a role in the formation and activity of social movements through online media, having important consequences for viral spreading.

Connected through hyperedge HE-1 (induced by source paper "integrating sentiment and social structure to determine preference alignments the irish marriage referendum"):
  with members:
    - "in the mood the dynamics of collective sentiments on twitter"
    - "is the sample good enough comparing data from twitter s streaming api with twitter s firehose"
    - "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 reciprocal reply networks exhibit assortativity with respect to happiness"
    - "twitter mood predicts the stock market"
    - "seeing stars exploiting class relationships for sentiment categorization with respect to rating scales"
    - "thumbs up or thumbs down semantic orientation applied to unsupervised classification of reviews"

Connected through hyperedge HE-2 (induced by source paper "the qwerty effect on the web how typing shapes the meaning of words in online human computer interaction"):
  with members:
    - "inferring networks of substitutable and complementary products"
    - "image based recommendations on styles and substitutes"
    - "social signals and algorithmic trading of bitcoin"
    - "who watches and shares what on youtube and when using twitter to understand youtube viewership"
    - "gender asymmetries in reality and fiction the bechdel test of social media"
    - "from amateurs to connoisseurs modeling the evolution of user expertise through online reviews"
    - "positive words carry less information than negative words"
    - "happiness is assortative in online social networks"

Connected through hyperedge HE-3 (induced by source paper "the dynamics of emotions in online interaction"):
  with members:
    - "comparing and combining sentiment analysis methods"

Connected through hyperedge HE-4 (induced by source paper "emotions demographics and sociability in twitter interactions"):
  with members:
    - "measuring urban deprivation from user generated content"
    - "user effort and network structure mediate access to information in networks"
    - "cultures in community question answering"
    - "big questions for social media big data representativeness validity and other methodological pitfalls"
    - "comparing and combining sentiment analysis methods"
    - "the role of social networks in information diffusion"
    - "positive words carry less information than negative words"

Connected through hyperedge HE-5 (induced by source paper "social ties and emotions evidence from social media"):
  with members:
    - "measuring urban deprivation from user generated content"
    - "user effort and network structure mediate access to information in networks"
    - "cultures in community question answering"
    - "big questions for social media big data representativeness validity and other methodological pitfalls"
    - "comparing and combining sentiment analysis methods"
    - "positive words carry less information than negative words"

Connected through hyperedge HE-6 (induced by source paper "geography of emotion where in a city are people happier"):
  with members:
    - "measuring urban deprivation from user generated content"
    - "big questions for social media big data representativeness validity and other methodological pitfalls"
    - "comparing and combining sentiment analysis methods"
    - "positive words carry less information than negative words"

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)