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: "statistically significant detection of linguistic change"
  Abstract: We propose a new computational approach for tracking and detecting statistically significant linguistic shifts in the meaning and usage of words. Such linguistic shifts are especially prevalent on the Internet, where the rapid exchange of ideas can quickly change a word's meaning. Our meta-analysis approach constructs property time series of word usage, and then uses statistically sound change point detection algorithms to identify significant linguistic shifts. #R##N#We consider and analyze three approaches of increasing complexity to generate such linguistic property time series, the culmination of which uses distributional characteristics inferred from word co-occurrences. Using recently proposed deep neural language models, we first train vector representations of words for each time period. Second, we warp the vector spaces into one unified coordinate system. Finally, we construct a distance-based distributional time series for each word to track it's linguistic displacement over time. #R##N#We demonstrate that our approach is scalable by tracking linguistic change across years of micro-blogging using Twitter, a decade of product reviews using a corpus of movie reviews from Amazon, and a century of written books using the Google Book-ngrams. Our analysis reveals interesting patterns of language usage change commensurate with each medium.

Connected through hyperedge HE-1 (induced by source paper "a framework for the computational linguistic analysis of dehumanization"):
  with members:
    - "social bias frames reasoning about social and power implications of language"
    - "mitigating gender bias in natural language processing literature review"
    - "talkdown a corpus for condescension detection in context"
    - "automatically neutralizing subjective bias in text"
    - "black is to criminal as caucasian is to police detecting and removing multiclass bias in word embeddings"
    - "contextual affective analysis a case study of people portrayals in online metoo stories"
    - "entity centric contextual affective analysis"
    - "examining gender and race bias in two hundred sentiment analysis systems"

Connected through hyperedge HE-2 (induced by source paper "capturing evolution in word usage just add more clusters"):
  with members:
    - "towards better substitution based word sense induction"
    - "time out temporal referencing for robust modeling of lexical semantic change"
    - "does bert make any sense interpretable word sense disambiguation with contextualized embeddings"
    - "simple dynamic word embeddings for mapping perceptions in the public sphere"
    - "leveraging contextual embeddings for detecting diachronic semantic shift"
    - "survey of computational approaches to diachronic conceptual change"
    - "a state of the art of semantic change computation"
    - "deep contextualized word representations"

Connected through hyperedge HE-3 (induced by source paper "temporal embeddings and transformer models for narrative text understanding"):
  with members:
    - "extraction and analysis of fictional character networks a survey"
    - "contextualized word embeddings enhanced event temporal relation extraction for story understanding"
    - "training temporal word embeddings with a compass"
    - "story ending prediction by transferable bert"
    - "deep contextualized word representations"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "diachronic word embeddings and semantic shifts a survey"
    - "attention is all you need"

Connected through hyperedge HE-4 (induced by source paper "where new words are born distributional semantic analysis of neologisms and their semantic neighborhoods"):
  with members:
    - "survey of computational approaches to diachronic conceptual change"
    - "making fetch happen the influence of social and linguistic context on nonstandard word growth and decline"
    - "the road to success assessing the fate of linguistic innovations in online communities"
    - "word embeddings quantify 100 years of gender and ethnic stereotypes"
    - "diachronic word embeddings and semantic shifts a survey"
    - "problems with evaluation of word embeddings using word similarity tasks"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "improving zero shot learning by mitigating the hubness problem"

Connected through hyperedge HE-5 (induced by source paper "shared task lexical semantic change detection in german"):
  with members:
    - "time out temporal referencing for robust modeling of lexical semantic change"
    - "a wind of change detecting and evaluating lexical semantic change across times and domains"
    - "survey of computational approaches to diachronic conceptual change"
    - "fasttext zip compressing text classification models"
    - "word translation without parallel data"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "sparse overcomplete word vector representations"
    - "temporal analysis of language through neural language models"

Connected through hyperedge HE-6 (induced by source paper "simulating lexical semantic change from sense annotated data"):
  with members:
    - "gasc genre aware semantic change for ancient greek"
    - "a wind of change detecting and evaluating lexical semantic change across times and domains"
    - "challenges in detecting evolutionary forces in language change using diachronic corpora"
    - "dialectometric analysis of language variation in twitter"
    - "german in flux detecting metaphoric change via word entropy"
    - "cultural shift or linguistic drift comparing two computational measures of semantic change"
    - "diachronic word embeddings reveal statistical laws of semantic change"

Connected through hyperedge HE-7 (induced by source paper "language in our time an empirical analysis of hashtags"):
  with members:
    - "network embedding as matrix factorization unifying deepwalk line pte and node2vec"
    - "tagvisor a privacy advisor for sharing hashtags"
    - "hierarchical graph representation learning with differentiable pooling"
    - "you are your metadata identification and obfuscation of social media users using metadata information"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "ml leaks model and data independent membership inference attacks and defenses on machine learning models"
    - "twitter for sparking a movement reddit for sharing the moment metoo through the lens of social media"
    - "is saki delicious the food perception gap on instagram and its relation to health"

Connected through hyperedge HE-8 (induced by source paper "diachronic embedding for temporal knowledge graph completion"):
  with members:
    - "rotate knowledge graph embedding by relational rotation in complex space"
    - "relational representation learning for dynamic knowledge graphs a survey"
    - "hypernetwork knowledge graph embeddings"
    - "tucker tensor factorization for knowledge graph completion"
    - "improved knowledge graph embedding using background taxonomic information"
    - "how powerful are graph neural networks"
    - "learning dynamic embeddings from temporal interactions"
    - "learning sequence encoders for temporal knowledge graph completion"

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.CL(Computation and Language)