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 "location occupation and semantics based socioeconomic status inference on twitter"):
  Abstract: The socioeconomic status of people depends on a combination of individual characteristics and environmental variables, thus its inference from online behavioral data is a difficult task. Attributes like user semantics in communication, habitat, occupation, or social network are all known to be determinant predictors of this feature. In this paper we propose three different data collection and combination methods to first estimate and, in turn, infer the socioeconomic status of French Twitter users from their online semantics. Our methods are based on open census data, crawled professional profiles, and remotely sensed, expert annotated information on living environment. Our inference models reach similar performance of earlier results with the advantage of relying on broadly available datasets and of providing a generalizable framework to estimate socioeconomic status of large numbers of Twitter users. These results may contribute to the scientific discussion on social stratification and inequalities, and may fuel several applications.

Includes members:
  Member "socioeconomic dependencies of linguistic patterns in twitter a multivariate analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "computational human dynamics")
  Member "correlations and dynamics of consumption patterns in social economic networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "computational human dynamics")
  Member "predicting twitter user socioeconomic attributes with network and language information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "urban2vec incorporating street view imagery and pois for multi modal urban neighborhood embedding")
  Member "what the language you tweet says about your occupation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "social media based user embedding a literature review")
  Member "xgboost a scalable tree boosting system":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "monotonic cardinality estimation of similarity selection a deep learning approach")
  Member "detecting the age of twitter users":
    also connected through other hyperedges:
      (none)
  Member "diffusion of lexical change in social media":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "where new words are born distributional semantic analysis of neologisms and their semantic neighborhoods")
  Member "geotagging one hundred million twitter accounts with total variation minimization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "demographic inference and representative population estimates from multilingual social media data")

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)