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: "inheritance patterns in citation networks reveal scientific memes"
  Abstract: Memes are the cultural equivalent of genes that spread across human culture by means of imitation. What makes a meme and what distinguishes it from other forms of information, however, is still poorly understood. Our analysis of memes in the scientific literature reveals that they are governed by a surprisingly simple relationship between frequency of occurrence and the degree to which they propagate along the citation graph. We propose a simple formalization of this pattern and validate it with data from close to 50 million publication records from the Web of Science, PubMed Central, and the American Physical Society. Evaluations relying on human annotators, citation network randomizations, and comparisons with several alternative approaches confirm that our formula is accurate and effective, without a dependence on linguistic or ontological knowledge and without the application of arbitrary thresholds or filters.

Connected through hyperedge HE-1 (induced by source paper "predicting research trends with semantic and neural networks with an application in quantum physics"):
  with members:
    - "the emergent integrated network structure of scientific research"
    - "a comprehensive survey on graph neural networks"
    - "the landscape of neuroimage ing research"
    - "attention is all you need"
    - "gated graph sequence neural networks"
    - "learning convolutional neural networks for graphs"
    - "quantifying the cognitive extent of science"
    - "coauthorship and citation patterns in the physical review"

Connected through hyperedge HE-2 (induced by source paper "a model for meme popularity growth in social networking systems based on biological principle and human interest dynamics"):
  with members:
    - "limited individual attention and online virality of low quality information"
    - "local variation of hashtag spike trains and popularity in twitter"
    - "seismic a self exciting point process model for predicting tweet popularity"
    - "rising tides or rising stars dynamics of shared attention on twitter during media events"
    - "a bayesian approach for predicting the popularity of tweets"
    - "dynamical classes of collective attention in twitter"
    - "what trends in chinese social media"
    - "agents bookmarks and clicks a topical model of web navigation"

Connected through hyperedge HE-3 (induced by source paper "discontinuities in citation relations among journals self organized criticality as a model of scientific revolutions and change"):
  with members:
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "the dynamics of triads in aggregated journal journal citation relations specialty developments at the above journal level"
    - "aggregated journal journal citation relations in scopus and web of science matched and compared in terms of networks maps and interactive overlays"
    - "a new methodology for constructing a publication level classification system of science"
    - "the production of probabilistic entropy in structure action contingency relations"

Connected through hyperedge HE-4 (induced by source paper "using text analysis to quantify the similarity and evolution of scientific disciplines"):
  with members:
    - "the ground truth about metadata and community detection in networks"
    - "using network science and text analytics to produce surveys in a scientific topic"
    - "science concierge a fast content based recommendation system for scientific publications"
    - "quantifying long term scientific impact"
    - "characterizing interdisciplinarity of researchers and research topics using web search engines"

Connected through hyperedge HE-5 (induced by source paper "online social network analysis a survey of research applications in computer science"):
  with members:
    - "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"
    - "exploring image virality in google plus"
    - "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-6 (induced by source paper "sample nlpde and nlode social media modeling of information transmission for infectious diseases case study ebola"):
  with members:
    - "modeling information diffusion in online social networks with partial differential equations"
    - "analysis of a heterogeneous social network of humans and cultural objects"
    - "a computer virus propagation model using delay differential equations with probabilistic contagion and immunity"
    - "statistically significant detection of linguistic change"
    - "do retweets indicate interest trust agreement extended abstract"
    - "a cooperate defect model for the spread of deviant behavior in social networks"
    - "what they do in shadows twitter underground follower market"
    - "influence spread in social networks a study via a fluid limit of the linear threshold model"

Connected through hyperedge HE-7 (induced by source paper "quantifying the cognitive extent of science"):
  with members:
    - "growth rates of modern science a bibliometric analysis based on the number of publications and cited references"
    - "e prints and journal articles in astronomy a productive co existence"

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)