Abstract

ABSTRACT Political leaders articulate themselves best via speeches and/or writings across diverse media (print or electronic) for campaigning, pitching their stand, confronting the opponent/s, impressing upon the citizens, penning down their biographies, and the like. While making speeches, politicians evince provocative sentiments themselves that are likely to move the audience-that is the prime objective of any orator. Concomitantly, however, the politicians make speeches charged with emotions to drive home a point. The present study seeks to hinge itself upon the speeches of Volodymyr Oleksandrovych Zelenskyy, the Ukrainian President, who is embroiled in a war with Russia since February 2022. Specifically, sentiment analysis was done to understand the dynamics of emotions that wavered with the progress of war. Computational text analysis of speeches for a specified period (24 February 2022 until 24 July 2022) shows that sentiments appear to increase over a period of time wherein the best predictor, in our Bayesian regression models, for a change in Zelenskyy’s sentiment between today and tomorrow is his “present” sentiment-the sentiment that he evinces “today.” Implicitly, if we detect a high/low positive sentiment “today,” we would expect to see a strong mean regression such that tomorrow’s sentiment should be close to neutral. Findings suggest that in contrast with the general observation that peculiar war events tend to have great power in explaining changes in sentiments, the same was found only to be an ancillary factor in the present study. The study is rounded off with further research pointers with practitioner implications.

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