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http://hdl.handle.net/10397/99851
Title: | Metaphor development in public discourse using an ARIMA time series analysis approach | Authors: | Zeng, WH Tay, D Ahrens, K |
Issue Date: | 2021 | Source: | In K Hu, JB Kim, C Zong & E Chersoni (Eds.), Proceedings of the 35th Pacific Asia Conference on Language, Information and Computation, p. 776-784. Shanghai, China: Association for Computational Lingustics, 2021 | Abstract: | This study introduces a Time Series Analysis approach to metaphor development in a corpus of public discourse as a case study to examine the potential implications for the strategic use of metaphors in discourse over time. The corpus covers 20 years of public speeches by the government leaders in Hong Kong. We conducted an ARIMA time series modeling on the use of the frequently occurring metaphor source domains in the corpus. The ARIMA time series modeling procedures were explicitly presented, and the results were qualitatively discussed with empirical examples. We found that LIVING ORGANISM metaphors demonstrate the clearest usage profile across time, which can be attributable to the progressions of background events in the broad context based on the corpus evidence. In sum, our study emphasizes the Time Series Analysis as a complementary method offering structural insights to the diachronic study of metaphors in discourse. | Description: | The 35th Pacific Asia Conference on Language, Information and Computation, 5–7 November, 2021, Shanghai International Studies University, Shanghai, China | Rights: | ©The PACLIC 35 Organizing Committee and PACLIC Steering Committee Copyright of contributed papers reserved by respective authors. Posted with permission of the author. The following Winnie Huiheng Zeng, Dennis Tay, and Kathleen Ahrens. 2021. Metaphor Development in Public Discourse Using an ARIMA Time Series Analysis Approach. In Proceedings of the 35th Pacific Asia Conference on Language, Information and Computation, pages 776–784, Shanghai, China. Association for Computational Lingustics is available at https://aclanthology.org/2021.paclic-1.82/. |
Appears in Collections: | Conference Paper |
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