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: "how many political parties should brazil have a data driven method to assess and reduce fragmentation in multi party political systems"
  Abstract: In June 2013, Brazil faced the largest and most significant mass protests in a generation. These were exacerbated by the population’s disenchantment towards its highly fragmented party system, which is composed by a very large number of political parties. Under these circumstances, presidents are constrained by informal coalition governments, bringing very harmful consequences to the country. In this work I propose ARRANGE, a dAta dRiven method foR Assessing and reduciNG party fragmEntation in a country. ARRANGE uses as input the roll call data for congress votes on bills and amendments as a proxy for political preferences and ideology. With that, ARRANGE finds the minimum number of parties required to house all congressmen without decreasing party discipline. When applied to Brazil’s historical roll call data, ARRANGE was able to generate 23 distinct configurations that, compared with the status quo, have (i) a significant smaller number of parties, (ii) a higher discipline of partisans towards their parties and (iii) a more even distribution of partisans into parties. ARRANGE is fast and parsimonious, relying on a single, intuitive parameter.

Connected through hyperedge HE-1 (induced by source paper "analyzing dynamic ideological communities in congressional voting networks"):
  with members:
    - "community discovery in dynamic networks a survey"
    - "signed graph analysis for the interpretation of voting behavior"
    - "trump vs hillary what went viral during the 2016 us presidential election"
    - "how polarized have we become a multimodal classification of trump followers and clinton followers"
    - "cohesion and coalition formation in the european parliament roll call votes and twitter activities"
    - "brazilian congress structural balance analysis"

Connected through hyperedge HE-2 (induced by source paper "when politicians talk about politics identifying political tweets of brazilian congressmen"):
  with members:
    - "portuguese word embeddings evaluating on word analogies and natural language tasks"
    - "recognizing explicit and implicit hate speech using a weakly supervised two path bootstrapping approach"
    - "efficient estimation of word representations in vector space"

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)