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 "visual themes and sentiment on social networks to aid first responders during crisis events"):
  Abstract: Online Social Networks explode with activity whenever a crisis event takes place. Most content generated as part of this activity is a mixture of text and images, and is particularly useful for first responders to identify popular topics of interest and gauge the pulse and sentiment of citizens. While multiple researchers have used text to identify, analyze and measure themes and public sentiment during such events, little work has explored visual themes floating on networks in the form of images, and the sentiment inspired by them. Given the potential of visual content for influencing users' thoughts and emotions, we perform a large scale analysis to compare popular themes and sentiment across images and textual content posted on Facebook during the terror attacks that took place in Paris in 2015. Using state-of-the-art image summarization techniques, we discovered multiple visual themes which were popular in images, but were not identifiable through text. We uncovered instances of misinformation and false flag (conspiracy) theories among popular image themes, which were not prominent in user generated textual content, and can be of particular inter- est to first responders. Our analysis also revealed that while textual content posted after the attacks reflected negative sentiment, images inspired positive sentiment. To the best of our knowledge, this is the first large scale study of images posted on social networks during a crisis event.

Includes members:
  Member "robust image sentiment analysis using progressively trained and domain transferred deep networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi source domain adaptation in the deep learning era a systematic survey")
  Member "rethinking the inception architecture for computer vision":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adversarial ranking attack and defense")
  Member "imagenet large scale visual recognition challenge":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "visual sentiment prediction with deep convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "affective computing for large scale heterogeneous multimedia data a survey")
  Member "decaf a deep convolutional activation feature for generic visual recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "crl class representative learning for image classification")
  Member "twitter mood predicts the stock market":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)