With social and technological developments, the contents and means of human communication have undergone tremendous changes, which, in turn, lead to the evolution of word forms and their meanings in human language. In literature, much scholarship has been devoted to the semantic dynamics of words from the perspective of usage frequency, yet this frequency-based method cannot explain clearly the lexical-semantic change due to its failure to cover word senses. In this paper, a large-scale Chinese newspaper text corpus is employed and the distributed representations of some words and their senses are elicited in order to observe the diachronic evolvement of word semantics. The semantic change of the words in the timeline suggests that the distributional method proposed in this paper is effective for the exploration of lexical semantic dynamics. The implication of this study is that the corpus-based distributional method can become a useful tool for studies in other fi elds, such as language evolution, sociolinguistics and language planning.
刘知远 刘 扬 涂存超 孙茂松. 词汇语义变化与社会变迁定量观测与分析[J]. 语言战略研究, 2016, 1(6): 47-54.
Liu Zhiyuan, Liu Yang, Tu Cunchao and Sun Maosong. Lexical Semantic Variation and Social Change: Quantitative Observation and Analysis. , 2016, 1(6): 47-54.
Aiden, Erez Lieberman and Jean-Baptiste Michel. 2013. Uncharted: Big Data as a Lens on Human Culture. New York: Riverhead Books.
Bamman, David and Gregory Crane. 2011. Measuring Historical Word Sense Variation. Proceedings of JCDL, 1-10.
Bengio, Yoshua, Réjean Ducharme, Pascal Vincent, and Christian Jauvin. 2003. A Neural Probabilistic Language Model. The Journal of Machine Learning Research 3, 1137-1155.
Chen, Xinxiong, Zhiyuan Liu, and Maosong Sun. 2014. A Unified Model for Word Sense Representation and Disambiguation. Proceedings of EMNLP.
Eisenstein, Jacob, Brendan O'Connor, Noah A. Smith, and Eric P. Xing. 2010. A Latent Variable Model for Geographic Lexical Variation. Proceedings of EMNLP.
Leskovec, Jure, Lars Backstrom, and Jon Kleinberg. 2009. Meme-Tracking and the Dynamics of the News Cycle. Proceedings of KDD.
Lieberman, Erez, Jean-Baptiste Michel1, Joe Jackson, Tina Tang, and Martin A. Nowak. 2007. Quantifying the Evolutionary Dynamics of Language. Nature 449(7163), 713-716.
Mihalcea, Rada, and Vivi Nastase. 2012. Word Epoch Disambiguation: Finding How Words Change Over Time. Proceedings of ACL, 259-263.
Michel, Jean-Baptiste, Yuan Kui Shen, Aviva Presser Aiden, Adrian Veres, Matthew K. Gray, Joseph P. Pickett, Dale Hoiberg, Dan Clancy, Peter Norvig, Jon Orwant, Steven Pinker, Martin A. Nowak, and Erez Lieberman Aiden. 2011. Quantitative Analysis of Culture Using Millions of Digitized Books. Science 331(6014), 176-182.
Mikolov, Tomas, Ilya Sutskever, Kai Chen, Greg S. Corrado,and Jeff Dean. 2013. Distributed Representations of Words and Phrases and Their Compositionality. Proceedings of NIPS, 3111-3119.
Navigli, Roberto. 2009. Word Sense Disambiguation: A Survey.ACM Computing Surveys (CSUR) 41.2, 10.
Tian, Fei, Hanjun Dai, Jiang Bian, Bin Gao, Rui Zhang, EnhongChen, and Tie-Yan Liu. 2014. A Probabilistic Model for Learning Multi-Prototype Word Embeddings. Proceedings of COLING.
Traugott, Elizabeth Closs, and Richard B. Dasher. 2001. Regularity in Semantic Change. Cambridge: Cambridge University Press.
Reisinger, Joseph, and Raymond J. Mooney. 2010. Multi-Prototype Vector-Space Models of Word Meaning. Proceedings of HLT-NAACL.
Wijaya, Derry Tanti, and Reyyan Yeniterzi. 2011. Understanding Semantic Change of Words Over Centuries. Proceedings of the 2011 International Workshop on Detecting and Exploiting Cultural Diversity on the Social Web, 35-40.
Yang, Jaewon, and Jure Leskovec. 2011. Patterns of Temporal Variation in Online Media. Proceedings of WSDM.
