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: "societal controversies in wikipedia articles"
  Abstract: Collaborative content creation inevitably reaches situations where different points of view lead to conflict. We focus on Wikipedia, the free encyclopedia anyone may edit, where disputes about content in controversial articles often reflect larger societal debates. While Wikipedia has a public edit history and discussion section for every article, the substance of these sections is difficult to phantom for Wikipedia users interested in the development of an article and in locating which topics were most controversial. In this paper we present Contropedia, a tool that augments Wikipedia articles and gives insight into the development of controversial topics. Contropedia uses an efficient language agnostic measure based on the edit history that focuses on wiki links to easily identify which topics within a Wikipedia article have been most controversial and when.

Connected through hyperedge HE-1 (induced by source paper "wikilinkgraphs a complete longitudinal and multi language dataset of the wikipedia link networks"):
  with members:
    - "benchmarking distributed stream processing engines"
    - "growing wikipedia across languages via recommendation"
    - "mining missing hyperlinks from human navigation traces a case study of wikipedia"
    - "interactions of cultures and top people of wikipedia from ranking of 24 language editions"
    - "biographical social networks on wikipedia a cross cultural study of links that made history"
    - "ranking of wikipedia articles in search engines revisited fair ranking for reasonable quality"
    - "pagerank standing on the shoulders of giants"

Connected through hyperedge HE-2 (induced by source paper "viewpoint discovery and understanding in social networks"):
  with members:
    - "actionable and political text classification using word embeddings and lstm"
    - "quantifying controversy in social media"
    - "controversy and sentiment in online news"

Connected through hyperedge HE-3 (induced by source paper "temporal analysis of entity relatedness and its evolution using wikipedia and dbpedia"):
  with members:
    - "timemachine timeline generation for knowledge base entities"
    - "extraction of historical events from wikipedia"

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.CL(Computation and Language)