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: "bloggers behavior and emergent communities in blog space"
  Abstract: Interactions between users in cyberspace may lead to phenomena different from those observed in common social networks. Here we analyse large data sets about users and Blogs which they write and comment, mapped onto a bipartite graph. In such enlarged Blog space we trace user activity over time, which results in robust temporal patterns of user-Blog behavior and the emergence of communities. With the spectral methods applied to the projection on weighted user network we detect clusters of users related to their common interests and habits. Our results suggest that different mechanisms may play the role in the case of very popular Blogs. Our analysis makes a suitable basis for theoretical modeling of the evolution of cyber communities and for practical study of the data, in particular for an efficient search of interesting Blog clusters and further retrieval of their contents by text analysis.

Connected through hyperedge HE-1 (induced by source paper "the dynamics of emotional chats with bots experiment and agent based simulations"):
  with members:
    - "the anatomy of the facebook social graph"
    - "negative emotions boost user activity at bbc forum"

Connected through hyperedge HE-2 (induced by source paper "patterns of emotional blogging and emergence of communities agent based model on bipartite networks"):
  with members:
    - "negative emotions boost user activity at bbc forum"
    - "emotional reactions and the pulse of public opinion measuring the impact of political events on the sentiment of online discussions"
    - "measuring the happiness of large scale written expression songs blogs and presidents"

Connected through hyperedge HE-3 (induced by source paper "negative emotions boost user activity at bbc forum"):
  with members:
    - "emotional reactions and the pulse of public opinion measuring the impact of political events on the sentiment of online discussions"
    - "human dynamics revealed through web analytics"

Connected through hyperedge HE-4 (induced by source paper "emotional analysis of blogs and forums data"):
  with members:
    - "negative emotions boost user activity at bbc forum"
    - "machine learning in automated text categorization"

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)