The Power of Words from the 2024 United States Presidential Debates: A Natural Language Processing Approach
This study analyzes the linguistic patterns and rhetorical strategies employed in the 2024 U.S. presidential debates from the exchanges between Donald Trump, Joe Biden, and Kamala Harris. This paper examines debate transcripts to find underlying themes and communication styles using Natural Language...
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| Language: | English |
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MDPI AG
2024-12-01
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| Online Access: | https://www.mdpi.com/2078-2489/16/1/2 |
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| author | Ana Lorena Jiménez-Preciado José Álvarez-García Salvador Cruz-Aké Francisco Venegas-Martínez |
| author_facet | Ana Lorena Jiménez-Preciado José Álvarez-García Salvador Cruz-Aké Francisco Venegas-Martínez |
| author_sort | Ana Lorena Jiménez-Preciado |
| collection | DOAJ |
| description | This study analyzes the linguistic patterns and rhetorical strategies employed in the 2024 U.S. presidential debates from the exchanges between Donald Trump, Joe Biden, and Kamala Harris. This paper examines debate transcripts to find underlying themes and communication styles using Natural Language Processing (NLP) advanced techniques, including an n-gram analysis, sentiment analysis, and lexical diversity measurements. The methodology combines a quantitative text analysis with qualitative interpretation through the Jaccard similarity coefficient, the Type–Token Ratio, and the Measure of Textual Lexical Diversity. The empirical results reveal distinct linguistic profiles for each candidate: Trump consistently employed emotionally charged language with high sentiment volatility, while Biden and Harris demonstrated more measured approaches with higher lexical diversity. Finally, this research contributes to the understanding of political discourse in high-stakes debates through NLP and can offer information on the evolution of the communication strategies of the presidential candidates of any country with this regime. |
| format | Article |
| id | doaj-art-342cb9de2b8043dca83a958c6cf2643b |
| institution | Kabale University |
| issn | 2078-2489 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj-art-342cb9de2b8043dca83a958c6cf2643b2025-01-24T13:35:05ZengMDPI AGInformation2078-24892024-12-01161210.3390/info16010002The Power of Words from the 2024 United States Presidential Debates: A Natural Language Processing ApproachAna Lorena Jiménez-Preciado0José Álvarez-García1Salvador Cruz-Aké2Francisco Venegas-Martínez3Escuela Superior de Economía, Instituto Politécnico Nacional, Av. Plan de Agua Prieta 66, Miguel Hidalgo, Mexico City 11350, MexicoDepartamento de Economía Financiera y Contabilidad, Instituto Universitario de Investigación para el Desarrollo Territorial Sostenible (INTERRA), Facultad de Empresa Finanzas y Turismo, Universidad de Extremadura, Avda. de la Universidad, n° 47, 10071 Cáceres, SpainEscuela Superior de Economía, Instituto Politécnico Nacional, Av. Plan de Agua Prieta 66, Miguel Hidalgo, Mexico City 11350, MexicoEscuela Superior de Economía, Instituto Politécnico Nacional, Av. Plan de Agua Prieta 66, Miguel Hidalgo, Mexico City 11350, MexicoThis study analyzes the linguistic patterns and rhetorical strategies employed in the 2024 U.S. presidential debates from the exchanges between Donald Trump, Joe Biden, and Kamala Harris. This paper examines debate transcripts to find underlying themes and communication styles using Natural Language Processing (NLP) advanced techniques, including an n-gram analysis, sentiment analysis, and lexical diversity measurements. The methodology combines a quantitative text analysis with qualitative interpretation through the Jaccard similarity coefficient, the Type–Token Ratio, and the Measure of Textual Lexical Diversity. The empirical results reveal distinct linguistic profiles for each candidate: Trump consistently employed emotionally charged language with high sentiment volatility, while Biden and Harris demonstrated more measured approaches with higher lexical diversity. Finally, this research contributes to the understanding of political discourse in high-stakes debates through NLP and can offer information on the evolution of the communication strategies of the presidential candidates of any country with this regime.https://www.mdpi.com/2078-2489/16/1/2presidential debatesnatural language processingsentiment analysisJaccard similaritytype–token ratiomeasure of textual lexical diversity |
| spellingShingle | Ana Lorena Jiménez-Preciado José Álvarez-García Salvador Cruz-Aké Francisco Venegas-Martínez The Power of Words from the 2024 United States Presidential Debates: A Natural Language Processing Approach Information presidential debates natural language processing sentiment analysis Jaccard similarity type–token ratio measure of textual lexical diversity |
| title | The Power of Words from the 2024 United States Presidential Debates: A Natural Language Processing Approach |
| title_full | The Power of Words from the 2024 United States Presidential Debates: A Natural Language Processing Approach |
| title_fullStr | The Power of Words from the 2024 United States Presidential Debates: A Natural Language Processing Approach |
| title_full_unstemmed | The Power of Words from the 2024 United States Presidential Debates: A Natural Language Processing Approach |
| title_short | The Power of Words from the 2024 United States Presidential Debates: A Natural Language Processing Approach |
| title_sort | power of words from the 2024 united states presidential debates a natural language processing approach |
| topic | presidential debates natural language processing sentiment analysis Jaccard similarity type–token ratio measure of textual lexical diversity |
| url | https://www.mdpi.com/2078-2489/16/1/2 |
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