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Background: Media coverage consistently exerts a significant influence on the formation ofthe public's opinion, especially framing the war. Media framing refers to the deliberateselection and presentation of information in a manner that influences people's perception andreaction to specific aspects of an issue. The major objective of this study was to investigatehow Bangladeshi Print media frame the Russa-Ukraine Conflict (RUC) during the conflictperiod. Methods: The study comprised of scrapped data from the online version of twonewspapers the Daily Star (n=1135) and New Age (n=728) news items related to the RussaUkraine conflict from 24 February 2022 to 24 February 2023. The news stories were scrapedutilizing Python’s web scraping package Beautiful Soup. The data is analyzed adopting theLatent Dirichlet Allocation (LDA) topic modeling technique to determine the dominantframings like top keywords, top key phrases, and the most highlighted topic of the RussaUkraine war. Results: The frequency analysis of the Daily Star showed Ukraine (n=7,112)and Russia (n=5,884) being the most frequently used words, similarly New Age depictedUkraine (n=4,901) and Russia (n=3,655) as both newspaper’s top two mentioned words:Ukraine and Russia, were the same. The ‘United States’ was the top and second most usedkey phrase in New Age and The Daily Star, correspondingly. Surprisingly, Daily Starmentioned ‘United States’ (n=487) and ‘Joe Biden’ (n=211) in a notable amount though theUnited States was not a direct part of the conflict. The topic analysis showed that the topic –‘Military confrontations between Russia-Ukraine’ (frequency =513) and the topic- ‘Russiaand Ukraine’s military clashes’ (frequency= 421) had the utmost priority in the coverage ofthe Daily Star and the New Age, respectively. Conclusion: It was evident from our findingsthat Unites States, Joe Biden, western, sanctions, European Union, security council, BlackSea etc. topics were got much attention in compared with the sufferings of the victims, pricehike, energy crisis etc. topics.
Nath et al. (Fri,) studied this question.