Applying Advanced Analytics and Natural Language Processing to Assess the Effectiveness of Political Rhetoric: A Case Study of Presidential Messages in Kazakhstan

Political rhetoric plays a crucial role in shaping national strategies and communicating state priorities. This study leverages advanced analytics and Natural Language Processing (NLP) tools to analyze the thematic content and frequency of key phrases in Kazakhstan's presidential messages from 1997 to 2024. Using methods such as topic modeling, lexical density analysis, and frequency distribution, we assess how rhetoric aligns with progress in key indicators. Additionally, we compare elements of political rhetoric with selected healthcare indicators, attempting to identify correlations.However, it is important to emphasize that our goal was not to establish causal links, as we are limited by data availability. Instead, we aim to demonstrate that text analysis tools, including those used in AI-driven research, can be applied to assess political rhetoric. Our findings illustrate the potential of such methods in evaluating discourse trends and their alignment with national development priorities.

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Published
2025-05-14
DOI
https://doi.org/10.1109/sist61657.2025.11139256
Primary Topic
Terrorism, Counterterrorism, and Political Violence
Type
article
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article

Applying Advanced Analytics and Natural Language Processing to Assess the Effectiveness of Political Rhetoric: A Case Study of Presidential Messages in Kazakhstan

Birlik Mendybayev, Tamerlan Mendybayev, Kuralay Tuspekova
Terrorism, Counterterrorism, and Political Violence
article

Applying Advanced Analytics and Natural Language Processing to Assess the Effectiveness of Political Rhetoric: A Case Study of Presidential Messages in Kazakhstan

Birlik Mendybayev, Tamerlan Mendybayev, Kuralay Tuspekova
article en

Abstract

Political rhetoric plays a crucial role in shaping national strategies and communicating state priorities. This study leverages advanced analytics and Natural Language Processing (NLP) tools to analyze the thematic content and frequency of key phrases in Kazakhstan's presidential messages from 1997 to 2024. Using methods such as topic modeling, lexical density analysis, and frequency distribution, we assess how rhetoric aligns with progress in key indicators. Additionally, we compare elements of political rhetoric with selected healthcare indicators, attempting to identify correlations.However, it is important to emphasize that our goal was not to establish causal links, as we are limited by data availability. Instead, we aim to demonstrate that text analysis tools, including those used in AI-driven research, can be applied to assess political rhetoric. Our findings illustrate the potential of such methods in evaluating discourse trends and their alignment with national development priorities.

L. N. Gumilyov Eurasian National University (KZ), Almaty Management University (KZ), Almaty University of Power Engineering and Telecommunications (KZ), Kyrgyz Economic University (KG)
Openalex Percentile: Top 69%
Terrorism, Counterterrorism, and Political Violence
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