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 "distilling information reliability and source trustworthiness from digital traces"):
  Abstract: Online knowledge repositories typically rely on their users or dedicated editors to evaluate the reliability of their contents. These explicit feedback mechanisms can be viewed as noisy measurements of both information reliability and information source trustworthiness. Can we leverage these noisy measurements, often biased, to distill a robust, unbiased and interpretable measure of both notions?#R##N##R##N#In this paper, we argue that the large volume of digital traces left by the users within knowledge repositories also reflect information reliability and source trustworthiness. In particular, we propose a temporal point process modeling framework which links the temporal behavior of the users to information reliability and source trustworthiness. Furthermore, we develop an efficient convex optimization procedure to learn the parameters of the model from historical traces of the evaluations provided by these users. Experiments on real-world data gathered from Wikipedia and Stack Overflow show that our modeling framework accurately predicts evaluation events, provides an interpretable measure of information reliability and source trustworthiness, and yields interesting insights about real-world events.

Includes members:
  Member "uncovering the dynamics of crowdlearning and the value of knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the size conundrum why online knowledge markets can fail at scale")
  Member "multistage campaigning in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "meta learning with relational information for short sequences")
  Member "assessing human error against a benchmark of perfection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ask not what ai can do but what ai should do towards a framework of task delegability")
  Member "smart broadcasting do you want to be seen":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "can a user guess what her followers want")
  Member "from data fusion to knowledge fusion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "knowledge federation hierarchy and unification")
  Member "coevolve a joint point process model for information diffusion and network co evolution":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "predicting dynamic embedding trajectory in temporal interaction networks")
  Member "learning and forecasting opinion dynamics in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "consequential ranking algorithms and long term welfare")
  Member "knowledge based trust estimating the trustworthiness of web sources":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "detecting toxicity in news articles application to bulgarian")

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)