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 "nowcasting the stance of social media users in a sudden vote the case of the greek referendum"):
  Abstract: Modelling user voting intention in social media is an important research area, with applications in analysing electorate behaviour, online political campaigning and advertising. Previous approaches mainly focus on predicting national general elections, which are regularly scheduled and where data of past results and opinion polls are available. However, there is no evidence of how such models would perform during a sudden vote under time-constrained circumstances. That poses a more challenging task compared to traditional elections, due to its spontaneous nature. In this paper, we focus on the 2015 Greek bailout referendum, aiming to nowcast on a daily basis the voting intention of 2,197 Twitter users. We propose a semi-supervised multiple convolution kernel learning approach, leveraging temporally sensitive text and network information. Our evaluation under a real-time simulation framework demonstrates the effectiveness and robustness of our approach against competitive baselines, achieving a significant 20% increase in F-score compared to solely text-based models.

Includes members:
  Member "political discourse on social media echo chambers gatekeepers and the price of bipartisanship":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "facebook ads monitor an independent auditing system for political ads on facebook")
  Member "s i o no qu e penses catalonian independence and linguistic identity on social media":
    also connected through other hyperedges:
      (none)
  Member "predicting twitter user socioeconomic attributes with network and language information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "urban2vec incorporating street view imagery and pois for multi modal urban neighborhood embedding")
  Member "stance classification of social media users in independence movements":
    also connected through other hyperedges:
      (none)
  Member "semeval 2017 task 8 rumoureval determining rumour veracity and support for rumours":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stance detection benchmark how robust is your stance detection")
  Member "i have a feeling trump will win forecasting winners and losers from user predictions on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analyzing the perceived severity of cybersecurity threats reported on social media")
  Member "140 characters to victory using twitter to predict the uk 2015 general election":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "measuring the diversity of facebook reactions to research")
  Member "line large scale information network embedding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "adversarial attacks and defenses on graphs a review and empirical study")

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.CY(Computers and Society)