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 "the human geography of twitter"):
  Abstract: Given the centrality of regions in social movements, politics and public administration we aim to quantitatively study inter- and intra-regional communication for the first time. This work uses social media posts to first identify contiguous geographical regions with a shared social identity and then investigate patterns of communication within and between them. Our case study uses over 150 days of located Twitter data from England and Wales. In contrast to other approaches, (e.g. phone call data records or online friendship networks) we have the message contents as well as the social connection. This allows us to investigate not only the volume of communication but also the sentiment and vocabulary. We find that the South-East and North-West regions are the most talked about; regions tend to be more positive about themselves than about others; people talk politics much more between regions than within. This methodology gives researchers a powerful tool to study identity and interaction within and between social-geographic regions.

Includes members:
  Member "depicting urban boundaries from a mobility network of spatial interactions a case study of great britain with geo located twitter data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "data4urbanmobility towards holistic data analytics for mobility applications in urban regions")
  Member "dialectometric analysis of language variation in twitter":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "simulating lexical semantic change from sense annotated data")
  Member "scaling laws in geo located twitter data":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "measuring relative opinion from location based social media a case study of the 2016 u s presidential election")
  Member "demographic dialectal variation in social media a case study of african american english":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "theory in theory out how social theory can solve problems that machine learning can t")
  Member "delineating geographical regions with networks of human interactions in an extensive set of countries":
    also connected through other hyperedges:
      - Hyperedge HE-5 (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)