human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "exploring image virality in google plus"
  Abstract: Reactions to posts in an online social network show different dynamics depending on several textual features of the corresponding content. Do similar dynamics exist when images are posted? Exploiting a novel dataset of posts, gathered from the most popular Google+ users, we try to give an answer to such a question. We describe several virality phenomena that emerge when taking into account visual characteristics of images (such as orientation, mean saturation, etc.). We also provide hypotheses and potential explanations for the dynamics behind them, and include cases for which common-sense expectations do not hold true in our experiments.

Connected through hyperedge HE-1 (induced by source paper "who will share my image predicting the content diffusion path in online social networks"):
  with members:
    - "predicting the popularity of github repositories"
    - "node2vec scalable feature learning for networks"
    - "understanding image virality"
    - "densecap fully convolutional localization networks for dense captioning"
    - "improved semantic representations from tree structured long short term memory networks"
    - "top down tree long short term memory networks"
    - "very deep convolutional networks for large scale image recognition"
    - "long term recurrent convolutional networks for visual recognition and description"

Connected through hyperedge HE-2 (induced by source paper "on the statistical properties of viral misinformation in online social media"):
  with members:
    - "early warning of human crowds based on query data from baidu maps analysis based on shanghai stampede"
    - "users polarization on facebook and youtube"
    - "hoaxy a platform for tracking online misinformation"
    - "personality traits and echo chambers on facebook"
    - "trend of narratives in the age of misinformation"
    - "debunking in a world of tribes"
    - "science vs conspiracy collective narratives in the age of misinformation"
    - "emotional dynamics in the age of misinformation"

Connected through hyperedge HE-3 (induced by source paper "online social network analysis a survey of research applications in computer science"):
  with members:
    - "inheritance patterns in citation networks reveal scientific memes"
    - "who will retweet this automatically identifying and engaging strangers on twitter to spread information"
    - "networkit an interactive tool suite for high performance network analysis"
    - "networkit a tool suite for large scale complex network analysis"
    - "can cascades be predicted"
    - "popularity prediction in microblogging network a case study on sina weibo"
    - "a scalable heuristic for viral marketing under the tipping model"
    - "a meta analysis of state of the art electoral prediction from twitter data"

Connected through hyperedge HE-4 (induced by source paper "on the role of conductance geography and topology in predicting hashtag virality"):
  with members:
    - "can cascades be predicted"
    - "a bayesian approach for predicting the popularity of tweets"
    - "predicting successful memes using network and community structure"
    - "virality prediction and community structure in social networks"
    - "exploring text virality in social networks"
    - "topic diffusion and emergence of virality in social networks"
    - "information diffusion and external influence in networks"
    - "good friends bad news affect and virality in twitter"

Connected through hyperedge HE-5 (induced by source paper "deep feelings a massive cross lingual study on the relation between emotions and virality"):
  with members:
    - "depechemood a lexicon for emotion analysis from crowd annotated news"
    - "anger is more influential than joy sentiment correlation in weibo"
    - "the role of emotions in propagating brands in social networks"
    - "how to ask for a favor a case study on the success of altruistic requests"
    - "the effect of wording on message propagation topic and author controlled natural experiments on twitter"
    - "the untold story of the clones content agnostic factors that impact youtube video popularity"
    - "exploring text virality in social networks"
    - "how the scientific community reacts to newly submitted preprints article downloads twitter mentions and citations"

Connected through hyperedge HE-6 (induced by source paper "understanding image virality"):
  with members:
    - "becoming the expert interactive multi class machine teaching"
    - "cloudcv large scale distributed computer vision as a cloud service"
    - "deep feelings a massive cross lingual study on the relation between emotions and virality"
    - "deep fragment embeddings for bidirectional image sentence mapping"
    - "decaf a deep convolutional activation feature for generic visual recognition"
    - "a scalable heuristic for viral marketing under the tipping model"
    - "rich feature hierarchies for accurate object detection and semantic segmentation"

Connected through hyperedge HE-7 (induced by source paper "can cascades be predicted"):
  with members:
    - "characterizing and curating conversation threads expansion focus volume re entry"
    - "virality prediction and community structure in social networks"
    - "information diffusion and external influence in networks"
    - "on the interplay between social and topical structure"
    - "predicting the popularity of online content"

Question: Please tell me which class the center node 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)