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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2503.07695 |
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| _version_ | 1866929751780753408 |
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| author | Hagen, Loni Dinh, Ly Alexopoulos, Golfo Li, Lingyao Ford, Diego Chong, Miyoung |
| author_facet | Hagen, Loni Dinh, Ly Alexopoulos, Golfo Li, Lingyao Ford, Diego Chong, Miyoung |
| contents | On February 7, 2024, Russian President Vladimir Putin gave a two-hour interview with conservative political commentator, Tucker Carlson. This study investigated the impact of the Carlson- Putin interview on the US X audience. We proposed a framework of social media impact using machine learning (ML) and natural language processing (NLP) by measuring changes in audience, structure, and content. Triangulation methods were used to validate the process and results. The interview had a considerable impact among segments of the American public: 1) the reach and engagement of far-right influencers increased after the interview, suggesting Kremlin narratives gained traction within these circles, 2) the communication structure became more vulnerable to disinformation spread after the interview, and 3) the public discourse changed from support for Ukraine funding to conversations about Putin, Russia, and the issue of "truth" or the veracity of Putin's claims. This research contributes to methods development for social media studies and aids scholars in analyzing how public opinion shapes policy debates. The Carlson-Putin interview sparked a broader discussion about truth-telling. Far from being muted, the broad impact of the interview appears considerable and poses challenges for foreign affairs leaders who depend on public support and buy-in when formulating national policy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_07695 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Instilling Doubts About Truth: Measuring the Impact of Tucker Carlson's Interview with Vladimir Putin Using Machine Learning and Natural Language Processing Hagen, Loni Dinh, Ly Alexopoulos, Golfo Li, Lingyao Ford, Diego Chong, Miyoung Social and Information Networks On February 7, 2024, Russian President Vladimir Putin gave a two-hour interview with conservative political commentator, Tucker Carlson. This study investigated the impact of the Carlson- Putin interview on the US X audience. We proposed a framework of social media impact using machine learning (ML) and natural language processing (NLP) by measuring changes in audience, structure, and content. Triangulation methods were used to validate the process and results. The interview had a considerable impact among segments of the American public: 1) the reach and engagement of far-right influencers increased after the interview, suggesting Kremlin narratives gained traction within these circles, 2) the communication structure became more vulnerable to disinformation spread after the interview, and 3) the public discourse changed from support for Ukraine funding to conversations about Putin, Russia, and the issue of "truth" or the veracity of Putin's claims. This research contributes to methods development for social media studies and aids scholars in analyzing how public opinion shapes policy debates. The Carlson-Putin interview sparked a broader discussion about truth-telling. Far from being muted, the broad impact of the interview appears considerable and poses challenges for foreign affairs leaders who depend on public support and buy-in when formulating national policy. |
| title | Instilling Doubts About Truth: Measuring the Impact of Tucker Carlson's Interview with Vladimir Putin Using Machine Learning and Natural Language Processing |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2503.07695 |