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 "rtbust exploiting temporal patterns for botnet detection on twitter"):
  Abstract: Within OSNs, many of our supposedly online friends may instead be fake accounts called social bots, part of large groups that purposely re-share targeted content. Here, we study retweeting behaviors on Twitter, with the ultimate goal of detecting retweeting social bots. We collect a dataset of 10M retweets. We design a novel visualization that we leverage to highlight benign and malicious patterns of retweeting activity. In this way, we uncover a 'normal' retweeting pattern that is peculiar of human-operated accounts, and 3 suspicious patterns related to bot activities. Then, we propose a bot detection technique that stems from the previous exploration of retweeting behaviors. Our technique, called Retweet-Buster (RTbust), leverages unsupervised feature extraction and clustering. An LSTM autoencoder converts the retweet time series into compact and informative latent feature vectors, which are then clustered with a hierarchical density-based algorithm. Accounts belonging to large clusters characterized by malicious retweeting patterns are labeled as bots. RTbust obtains excellent detection results, with F1 = 0.87, whereas competitors achieve F1 < 0.76. Finally, we apply RTbust to a large dataset of retweets, uncovering 2 previously unknown active botnets with hundreds of accounts.

Includes members:
  Member "influence of fake news in twitter during the 2016 us presidential election":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "topology comparison of twitter diffusion networks effectively reveals misleading information")
  Member "social fingerprinting detection of spambot groups through dna inspired behavioral modeling":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "charting the landscape of online cryptocurrency manipulation")
  Member "relational autoencoder for feature extraction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "financial time series forecasting with deep learning a systematic literature review 2005 2019")
  Member "holoscope topology and spike aware fraud detection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fraud detection in networks state of the art")
  Member "the paradigm shift of social spambots evidence theories and tools for the arms race":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "how many bots are you following")
  Member "botivist calling volunteers to action using online bots":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "how many bots are you following")
  Member "botornot a system to evaluate social bots":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "don t feed the troll detecting troll behavior via inverse reinforcement learning")
  Member "dna inspired online behavioral modeling and its application to spambot detection":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "uncovering coordinated networks on social media")

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)