Story and essential meaning dynamics in Bangladesh's July 2024 Student-People's Uprising
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866912686520926208 |
|---|---|
| author | Prama, Tabia Tanzin Danforth, Christopher M. Dodds, Peter Sheridan |
| author_facet | Prama, Tabia Tanzin Danforth, Christopher M. Dodds, Peter Sheridan |
| contents | News media serves a crucial role in disseminating information and shaping public perception, especially during periods of political unrest. Using over 50,0000 YouTube comments on news coverage from July 16 to August 6, 2024, we investigate the emotional dynamics and evolving discourse of public perception during the July 2024 Student-People's Uprising in Bangladesh. Through integrated analyses of sentiment, emotion, topic, lexical discourse, timeline progression, sentiment shifts, and allotaxonometry, we show how negative sentiment dominated during the movement. We find a negative correlation between comment happiness and number of protest deaths $(r = -0.45,\p = 0.00)$. Using an ousiometer to measure essential meaning, we find public responses reflect a landscape of power, aggression, and danger, alongside persistent expressions of hope, moral conviction, and empowerment through goodnesses. Topic discourse progressed during the movement, with peaks in `Political Conflict', `Media Flow', and `Student Violence' during crisis surges, while topics like `Social Resistance' and `Digital Movement' persisted amid repression. Sentiment shifts reveal that after the second internet blackout, average happiness increased, driven by the more frequent use of positive words such as `victory', `peace' and `freedom' and a decrease in negative terms such as `death' and `lies'. Finally, through allotaxonometric analysis, we observe a clear shift from protest to justice. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_01865 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Story and essential meaning dynamics in Bangladesh's July 2024 Student-People's Uprising Prama, Tabia Tanzin Danforth, Christopher M. Dodds, Peter Sheridan Computers and Society Social and Information Networks News media serves a crucial role in disseminating information and shaping public perception, especially during periods of political unrest. Using over 50,0000 YouTube comments on news coverage from July 16 to August 6, 2024, we investigate the emotional dynamics and evolving discourse of public perception during the July 2024 Student-People's Uprising in Bangladesh. Through integrated analyses of sentiment, emotion, topic, lexical discourse, timeline progression, sentiment shifts, and allotaxonometry, we show how negative sentiment dominated during the movement. We find a negative correlation between comment happiness and number of protest deaths $(r = -0.45,\p = 0.00)$. Using an ousiometer to measure essential meaning, we find public responses reflect a landscape of power, aggression, and danger, alongside persistent expressions of hope, moral conviction, and empowerment through goodnesses. Topic discourse progressed during the movement, with peaks in `Political Conflict', `Media Flow', and `Student Violence' during crisis surges, while topics like `Social Resistance' and `Digital Movement' persisted amid repression. Sentiment shifts reveal that after the second internet blackout, average happiness increased, driven by the more frequent use of positive words such as `victory', `peace' and `freedom' and a decrease in negative terms such as `death' and `lies'. Finally, through allotaxonometric analysis, we observe a clear shift from protest to justice. |
| title | Story and essential meaning dynamics in Bangladesh's July 2024 Student-People's Uprising |
| topic | Computers and Society Social and Information Networks |
| url | https://arxiv.org/abs/2511.01865 |