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A corpus-based analysis of Singapore's National Day rally speeches
Author
Ng, Qiu Rong
Supervisor
Green, Clarence
Guo, Libo
Abstract
This study is a corpus-based analysis of Singapore’s National Day Rally speeches from 1966 to 2019. Utilising the topicmodels (Grun & Hornik, 2011) package in R (R Core Team, 2017), the top 10 topics in Singapore’s National Day Rally speeches are identified and analysed. Moreover, the changes in prominent topics in line with the transition from Prime Minister Lee Kuan Yew to Prime Minister Goh Chok Tong and finally to the present Prime Minister Lee Hsien Loong are delineated and analysed. In addition, this study also investigates whether the findings obtained from computational linguistic topic modeling relate to the findings of previous largely qualitative discourse analysis studies conducted on the National Day Rally speeches. Specifically, comparisons will be made in relation to the findings of Tan and Wee’s (2002) and Wong and Tupas’ (2018) diachronic qualitative analysis papers. Computational linguistic topic modeling is valuable in confirming and extending the findings of these two qualitative discourse analysis studies conducted on the National Day Rally speeches.
The findings of this study also revealed that the 10 most prominent topics in Singapore’s National Day Rally speeches from 1966 to 2019 were: (1) Nation building, (2) Housing, (3) Family, including family as a metaphor, (4) China’s development, (5) Competitive economy, (6) Changes in society and defence, (7) Worker issues – cost, language and attitude, (8) Older and foreign worker issues, (9) Presidents’ actions, and (10) Building strong communities.
Furthermore, regarding the changes in prominent topics from one Prime Minister to another, the findings highlighted that differing government priorities, changing exogenous events, and evolving social demographics at different time periods resulted in different prominent topics for each Prime Minister’s administration.
In sum, this study has expanded the breadth and depth of the extant qualitative research on Singapore’s National Day Rally speeches by utilising a corpus-based methodology via topic modeling. Moreover, this study has also illuminated the potential of corroborating corpus linguistics with discourse analysis for future studies given that computational linguistic topic modeling confirms and extends the findings of previous discourse analysis studies carried out on the National Day Rally speeches. Most importantly, the value of utilising computational linguistic topic modeling as a methodology is undeniably illustrated as it provides researchers with a broad overview of all the prominent topics in a large corpus at a glance, thereby enabling researchers to know the scope of a corpus and highlight interesting issues that had never occurred to them previously.
The findings of this study also revealed that the 10 most prominent topics in Singapore’s National Day Rally speeches from 1966 to 2019 were: (1) Nation building, (2) Housing, (3) Family, including family as a metaphor, (4) China’s development, (5) Competitive economy, (6) Changes in society and defence, (7) Worker issues – cost, language and attitude, (8) Older and foreign worker issues, (9) Presidents’ actions, and (10) Building strong communities.
Furthermore, regarding the changes in prominent topics from one Prime Minister to another, the findings highlighted that differing government priorities, changing exogenous events, and evolving social demographics at different time periods resulted in different prominent topics for each Prime Minister’s administration.
In sum, this study has expanded the breadth and depth of the extant qualitative research on Singapore’s National Day Rally speeches by utilising a corpus-based methodology via topic modeling. Moreover, this study has also illuminated the potential of corroborating corpus linguistics with discourse analysis for future studies given that computational linguistic topic modeling confirms and extends the findings of previous discourse analysis studies carried out on the National Day Rally speeches. Most importantly, the value of utilising computational linguistic topic modeling as a methodology is undeniably illustrated as it provides researchers with a broad overview of all the prominent topics in a large corpus at a glance, thereby enabling researchers to know the scope of a corpus and highlight interesting issues that had never occurred to them previously.
Date Issued
2020
Call Number
P302.77 Ng
Date Submitted
2020