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 "twawler a lightweight twitter crawler"):
  Abstract: This paper presents twAwler, a lightweight twitter crawler that targets language-specific communities of users. twAwler takes advantage of multiple endpoints of the twitter API to explore user relations and quickly recognize users belonging to the targetted set. It performs a complete crawl for all users, discovering many standard user relations, including the retweet graph, mention graph, reply graph, quote graph, follow graph, etc. twAwler respects all twitter policies and rate limits, while able to monitor large communities of active users. #R##N#twAwler was used between August 2016 and March 2018 to generate an extensive dataset of close to all Greek-speaking twitter accounts (about 330 thousand) and their tweets and relations. In total, the crawler has gathered 750 million tweets of which 424 million are in Greek; 750 million follow relations; information about 300 thousand lists, their members (119 million member relations) and subscribers (27 thousand subscription relations); 705 thousand trending topics; information on 52 million users in total of which 292 thousand have been since suspended, 141 thousand have deleted their account, and 3.5 million are protected and cannot be crawled. twAwler mines the collected tweets for the retweet, quote, reply, and mention graphs, which, in addition to the follow relation crawled, offer vast opportunities for analysis and further research.

Includes members:
  Member "the darpa twitter bot challenge":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning")
  Member "aggregate characterization of user behavior in twitter and analysis of the retweet graph":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "vocabulary based method for quantifying controversy in social media")
  Member "understanding types of users on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a review of features for the discrimination of twitter users application to the prediction of offline influence")
  Member "twitter mood predicts the stock market":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mining social media data for biomedical signals and health related behavior")

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)