human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "twitter activity timeline as a signature of urban neighborhood"):
  Abstract: Modern cities are complex systems, evolving at a fast pace. Thus, many urban planning, political, and economic decisions require a deep and up-to-date understanding of the local context of urban neighborhoods. This study shows that the structure of openly available social media records, such as Twitter, offers a possibility for building a unique dynamic signature of urban neighborhood function, and, therefore, might be used as an efficient and simple decision support tool. Considering New York City as an example, we investigate how Twitter data can be used to decompose the urban landscape into self-defining zones, aligned with the functional properties of individual neighborhoods and their social and economic characteristics. We further explore the potential of these data for detecting events and evaluating their impact over time and space. This approach paves a way to a methodology for immediate quantification of the impact of urban development programs and the estimation of socioeconomic statistics at a finer spatial-temporal scale, thus allowing urban policy-makers to track neighborhood transformations and foresee undesirable changes in order to take early action before official statistics would be available.

Includes members:
  Member "urban magnetism through the lens of geo tagged photography":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fine grained land use classification at the city scale using ground level images")
  Member "scaling of city attractiveness for foreign visitors through big data of human economical and social media activity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scaling laws in geo located twitter data")
  Member "delineating geographical regions with networks of human interactions in an extensive set of countries":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "assessing the quality of home detection from mobile phone data for official statistics")

Question: Please tell me which class the source paper 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)