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 "towards understanding the information ecosystem through the lens of multiple web communities"):
  Abstract: The Web consists of numerous Web communities, news sources, and services, which are often exploited by various entities for the dissemination of false information. Yet, we lack tools and techniques to effectively track the propagation of information across the multiple diverse communities, and to model the interplay and influence between them. Also, we lack an understanding of what the role and impact of emerging communities and services on the Web are, and how such communities are exploited by bad actors that spread false and weaponized information. In this thesis, we study the information ecosystem on the Web by presenting a typology that includes the various types of false information, the involved actors and their possible motives. Then, we follow a data-driven cross-platform quantitative approach to analyze billions of posts from Twitter, Reddit, 4chan's /pol/, and Gab, to shed light on: 1) how news and memes travel from one Web community to another and how we can model and quantify the influence between Web communities; 2) characterizing the role of emerging Web communities and services on the Web, by studying Gab and two Web archiving services, namely the Wayback Machine and archive.is; and 3) how popular Web communities are exploited by state-sponsored actors for the purpose of spreading disinformation. Our analysis reveal that fringe Web communities like 4chan's /pol/ and The_Donald subreddit have a disproportionate influence on mainstream communities like Twitter with regard to the dissemination of news and memes. We find that Gab acts as the new hub for the alt-right community, while for Web archiving services we find that they can be misused to penalize ad revenue from news sources with conflicting ideology. Finally, when studying state-sponsored actors, we find that they were particularly influential in spreading news on popular communities like Twitter and Reddit.

Includes members:
  Member "characterizing the use of images by state sponsored troll accounts on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "disinformation warfare understanding state sponsored trolls on twitter and their influence on the web")
  Member "characterizing the use of images in state sponsored information warfare operations by russian trolls on twitter":
    also connected through other hyperedges:
      (none)
  Member "what is gab a bastion of free speech or an alt right echo chamber":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "from pick up artists to incels a data driven sketch of the manosphere")
  Member "a quantitative approach to understanding online antisemitism":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "semantic search of memes on twitter")
  Member "who let the trolls out towards understanding state sponsored trolls":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning")
  Member "disinformation warfare understanding state sponsored trolls on twitter and their influence on the web":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the web of false information rumors fake news hoaxes clickbait and various other shenanigans")
  Member "mobilizing the trump train understanding collective action in a political trolling community":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "and we will fight for our race a measurement study of genetic testing conversations on reddit and 4chan")
  Member "false information on web and social media a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "discover your social identity from what you tweet a content based approach")

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)