Vol. 9:4 (2018) ► pp.626–653
A diachronic analysis of metaphor clusters in political discourse
A comparative study of Chinese and American presidents’ speeches at universities
The complex and abstract character of political discourse makes it difficult to be understood directly by ordinary people. Assuming that use of metaphor could make political language easier to comprehend, more and more scholars began to focus on the study of metaphor in political discourse. However, most of these studies paid only attention to the contrastive study of single metaphor phenomena, while diachronic studies of metaphors still remained few.
The present paper attempts to make a diachronic analysis of metaphor clusters in American and Chinese political discourse. The data employed are American and Chinese leaders’ political speeches, addressed to university students; the Chinese corpus contains 119021 characters, while the American corpus includes 118805 words. The research was implemented over three periods, namely before 1900, from 1900 to 2010, and from 2010 up to now (when the new term “metaphor cluster” was introduced to study the clustering phenomena of metaphor in different periods). In addition, both qualitative analysis and qualitative analysis were employed; the linguistic analysis tool Wmatrix and MIPVU procedures were adopted to identify metaphor clusters, thereby remedying the shortcomings of traditional methods which identify metaphor through researchers’ intuition and perception. Qualitative analysis was used to conduct a contrastive analysis of dominant metaphor clusters and how they tend to be used by the lecturers, both in the American and the Chinese corpuses.
The data analysis shows that metaphor clusters abound in American and Chinese leaders’ political speeches in universities. Generally speaking, Chinese leaders adopt more metaphor clusters than do their American counterparts. Similar metaphor clusters in both data are: journey, family, and building. Circle and art metaphor clusters are unique to the Chinese data, while religion and drama metaphor clusters only occur in the American data. Before 1990, leaders adopted few metaphor clusters both in America and in China; the two decades from 1990 to 2010 witnessed a peak season of employing metaphor clusters in both Chinese and American leaders’ speeches, whereas after 2010, the usage of metaphor clusters in Chinese data ushered in a new stage of development, with a multitude of new metaphorical expressions having cultural connotations. The results reveal that the differences in the usage of metaphor clusters are mainly due to the various ideologies and cultural backgrounds of the two countries. In addition, our analysis also shows that the employment of metaphor clusters in political discourse could lead the audiences’ direction of thinking, reduce the audiences’ comprehensive burden, and arouse the audiences’ emotions.
Article outline
- 1.Introduction
- 2.Metaphor studies of political discourse
- 3.Research objectives
- 4.Methodology and data
- 4.1Data collection
- 4.2Research instruments
- 4.2.1Metaphor identification
- 4.2.2Metaphor cluster identification
- 5.Dominant metaphor clusters in the Chinese data
- 5.1Journey metaphor clusters
- 5.2Architectural construction metaphor clusters
- 5.3Family metaphor clusters
- 5.4War metaphor clusters
- 5.5Human metaphor clusters
- 5.6Nature metaphor clusters
- 5.7Circle metaphor clusters
- 5.8Art metaphor clusters
- 6.Metaphor clusters in the American English data
- 6.1Journey metaphor clusters
- 6.2Building metaphor clusters
- 6.3Family metaphor clusters
- 6.4War metaphor clusters
- 6.5Organism metaphor clusters
- 6.6Drama metaphor clusters
- 6.7Religion metaphor clusters
- 7.Findings and discussions
- 7.1Category comparisons of metaphor clusters in the data
- 7.2Metaphor clusters throughout different periods
- 7.2.1Metaphor clusters before 1990
- 7.2.2Metaphor clusters from 1990 to 2010
- 7.2.3Metaphor clusters from 2010 up to now
- 8.Conclusion
- Acknowledgements
-
References
https://doi.org/10.1075/ps.16055.sun
References
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