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: "constructing urban tourism space digitally a study of airbnb listings in two berlin neighborhoods"
  Abstract: Over the past decade, Airbnb has emerged as the most popular platform for renting out single rooms or whole apartments. The impact of Airbnb listings on local neighborhoods has been controversially discussed in many cities around the world. The platform's widespread adoption led to changes in urban life, and in particular urban tourism. In this paper, we argue that urban tourism space can no longer be understood as a fixed, spatial entity. Instead, we follow a constructionist approach and argue that urban tourism space is (re-)produced digitally and collaboratively on online platforms such as Airbnb. We relate our work to a research direction in the CSCW community that is concerned with the role of digital technologies in the production and appropriation of urban space and use the concept of representations as a theoretical lens for our empirical study. In that study, we qualitatively analyzed how the two Berlin neighborhoods Kreuzkolln and City West are digitally constructed by Airbnb hosts in their listing descriptions. Moreover, we quantitatively investigated to what extend mentioned places differ between Airbnb hosts and visitBerlin, the city's destination management organization (DMO). In our qualitative analysis, we found that hosts primarily focus on facilities and places in close proximity to their apartment. In the traditional urban tourism hotspot City West, hosts referred to many places also mentioned by the DMO. In the neighborhood of Kreuzkolln, in contrast, hosts reframed everyday places such as parks or an immigrant food market as the must sees in the area. We discuss how Airbnb hosts contribute to the discursive production of urban neighborhoods and thus co-produce them as tourist destinations. With the emergence of online platforms such as Airbnb, power relations in the construction of tourism space might shift from DMOs towards local residents who are now producing tourism space collaboratively.

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)