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 "a review of features for the discrimination of twitter users application to the prediction of offline influence"):
  Abstract: Many works related to Twitter aim at characterizing its users in some way: role on the service (spammers, bots, organizations, etc.), nature of the user (socio-professional category, age, etc.), topics of interest, and others. However, for a given user classification problem, it is very difficult to select a set of appropriate features, because the many features described in the literature are very heterogeneous, with name overlaps and collisions, and numerous very close variants. In this article, we review a wide range of such features. In order to present a clear state-of-the-art description, we unify their names, definitions and relationships, and we propose a new, neutral, typology. We then illustrate the interest of our review by applying a selection of these features to the offline influence detection problem. This task consists in identifying users who are influential in real life, based on their Twitter account and related data. We show that most features deemed efficient to predict online influence, such as the numbers of retweets and followers, are not relevant to this problem. However, we propose several content-based approaches to label Twitter users as influencers or not. We also rank them according to a predicted influence level. Our proposals are evaluated over the CLEF RepLab 2014 dataset, and outmatch state-of-the-art methods.

Includes members:
  Member "temporal multinomial mixture for instance oriented evolutionary clustering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "detecting real world influence through twitter")
  Member "klout score measuring influence across multiple social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "midmod osn a microscopic level information diffusion model for online social networks")
  Member "detecting real world influence through twitter":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "measuring user influence on twitter")
  Member "who will retweet this automatically identifying and engaging strangers on twitter to spread information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the art of social bots a review and a refined taxonomy")
  Member "identifying the community roles of social capitalists in the twitter network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "conversational networks for automatic online moderation")
  Member "understanding types of users on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "twawler a lightweight twitter crawler")
  Member "artex is another text summarizer":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "intweetive text summarization")
  Member "i wanted to predict elections with twitter and all i got was this lousy paper a balanced survey on election prediction using twitter data":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a total error framework for digital traces of humans")

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.CL(Computation and Language)