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: "building bridges into the unknown personalizing connections to little known countries"
  Abstract: How are you related to Malawi? Do recent events on the Comoros effect you in any subtle way? Who in your extended social network is in Croatia? We seldom ask ourselves these questions, yet a "long tail" of content beyond our everyday knowledge is waiting to be explored. In this work we propose a recommendation task of creating interest in little-known content by building personalized "bridges" to users. We consider an example task of interesting users in little-known countries, and propose a system which aggregates a user's Twitter profile, network, and tweets to create an interest model, which is then matched to a library of knowledge about the countries. We perform a user study of 69 participants and conduct 11 in-depth interviews in order to evaluate the efficacy of the proposed approach and gather qualitative insight into the effect of multi-faceted use of Twitter on the perception of the bridges. We find the increase in interest concerning little-known content to greatly depend on the pre-existing disposition to it. Additionally, we discover a set of vital properties good bridges must possess, including recency, novelty, emotiveness, and a proper selection of language. Using the proposed approach we aim to harvest the "invisible connections" to make explicit the idea of a "small world" where even a faraway country is more closely connected to you than you might have imagined.

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)