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: "competition and selection among conventions"
  Abstract: In many domains, a latent competition among different conventions determines which one will come to dominate. One sees such effects in the success of community jargon, of competing frames in political rhetoric, or of terminology in technical contexts. These effects have become widespread in the on-line domain, where the ease of information transmission makes them particularly forceful, and where the available data offers the potential to study competition among conventions at a fine-grained level.#R##N##R##N#In analyzing the dynamics of conventions over time, however, even with detailed on-line data, one encounters two significant challenges. First, as conventions evolve, the underlying substance of their meaning tends to change as well; and such substantive changes confound investigations of social effects. Second, the selection of a convention takes place through the complex interactions of individuals within a community, and contention between the users of competing conventions plays a key role in the convention's evolution. Any analysis of the overall dynamics must take place in the presence of these two issues.#R##N##R##N#In this work we study a setting in which we can cleanly track the competition among conventions while explicitly taking these sources of complexity into account. Our analysis is based on the spread of low-level authoring conventions in the e-print arXiv over 24 years and roughly a million posted papers: by tracking the spread of macros and other author-defined conventions, we are able to study conventions that vary even as the underlying meaning remains constant. We find that the interaction among co-authors over time plays a crucial role in the selection of conventions; the distinction between more and less experienced members of the community, and the distinction between conventions with visible versus invisible effects, are both central to the underlying processes. Through our analysis we make predictions at the population level about the ultimate success of different synonymous conventions over time --- and at the individual level about the outcome of ``fights'' between people over convention choices.

Connected through hyperedge HE-1 (induced by source paper "library adoption dynamics in software teams"):
  with members:
    - "the social dynamics of language change in online networks"

Connected through hyperedge HE-2 (induced by source paper "a wind of change detecting and evaluating lexical semantic change across times and domains"):
  with members:
    - "survey of computational approaches to diachronic conceptual change"
    - "distribution based prediction of the degree of grammaticalization for german prepositions"
    - "a robust self learning method for fully unsupervised cross lingual mappings of word embeddings"
    - "on the linearity of semantic change investigating meaning variation via dynamic graph models"
    - "dialectometric analysis of language variation in twitter"
    - "cultural shift or linguistic drift comparing two computational measures of semantic change"
    - "tracing metaphors in time through self distance in vector spaces"
    - "diachronic word embeddings reveal statistical laws of semantic change"

Connected through hyperedge HE-3 (induced by source paper "competing topic naming conventions in quora predicting appropriate topic merges and winning topics from millions of topic pairs"):
  with members:
    - "universal sentence encoder"
    - "deep dive into anonymity a large scale analysis of quora questions"
    - "language use matters analysis of the linguistic structure of question texts can characterize answerability in quora"
    - "bieber blast bieberblast early prediction of popular hashtag compounds"
    - "analysis of named entity recognition and linking for tweets"
    - "distributed representations of sentences and documents"
    - "efficient estimation of word representations in vector space"
    - "who is authoritative understanding reputation mechanisms in quora"

Connected through hyperedge HE-4 (induced by source paper "short term meaning shift a distributional exploration"):
  with members:
    - "a state of the art of semantic change computation"
    - "the road to success assessing the fate of linguistic innovations in online communities"
    - "diachronic word embeddings and semantic shifts a survey"
    - "tracing metaphors in time through self distance in vector spaces"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "statistically significant detection of linguistic change"
    - "temporal analysis of language through neural language models"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-5 (induced by source paper "the road to success assessing the fate of linguistic innovations in online communities"):
  with members:
    - "tracing the use of practices through networks of collaboration"
    - "loyalty in online communities"
    - "the status gradient of trends in social media"
    - "the social dynamics of language change in online networks"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "diffusion of lexical change in social media"
    - "niche as a determinant of word fate in online groups"
    - "weak ties subtle role of information diffusion in online social networks"

Connected through hyperedge HE-6 (induced by source paper "short term meaning shift an exploratory distributional analysis"):
  with members:
    - "a state of the art of semantic change computation"
    - "the road to success assessing the fate of linguistic innovations in online communities"
    - "diachronic word embeddings and semantic shifts a survey"
    - "words are malleable computing semantic shifts in political and media discourse"
    - "tracing metaphors in time through self distance in vector spaces"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "temporal analysis of language through neural language models"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-7 (induced by source paper "tracing the use of practices through networks of collaboration"):
  with members:
    - "the status gradient of trends in social media"
    - "can cascades be predicted"

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)