<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In a complex information environment, Russia’s invasion of Ukraine presents a major challenge to the communication of political leaders throughout the world. The objective of this article is to analyse the frames and sentiments used by German chancellor Olaf Scholz, employing a novel data set of his Twitter communication (N = 612) during the Russian invasion of Ukraine between 24 February 2022 and 24 February 2023. A combination of computational text analysis approaches with natural language processing (NLP) techniques was used, including the Valence Aware Dictionary and the sentiment Reasoner (VADER) model for sentiment analysis and Latent Dirichlet Allocation (LDA) for topic modelling. This research investigates the prevalent frames and emotions in the chancellor’s communication, providing valuable insights into the German government’s stance and strategic communication during this critical geopolitical event. The results of the study revealed that the chancellor used the frames ‘effects of the Ukraine invasion’, ‘climate &amp; environment’, ‘solidarity’ and ‘Russian aggression’ and communicated with positive sentiments. By examining the chancellor’s Twitter communication, this study contributes to the understanding of political communication in the digital era, particularly in the context of international crises, and offers implications for policymakers, scholars and the broader public.</p>
</abstract>

In a complex information environment, Russia’s invasion of Ukraine presents a major challenge to the communication of political leaders throughout the world. The objective of this article is to analyse the frames and sentiments used by German chancellor Olaf Scholz, employing a novel data set of his Twitter communication (N = 612) during the Russian invasion of Ukraine between 24 February 2022 and 24 February 2023. A combination of computational text analysis approaches with natural language processing (NLP) techniques was used, including the Valence Aware Dictionary and the sentiment Reasoner (VADER) model for sentiment analysis and Latent Dirichlet Allocation (LDA) for topic modelling. This research investigates the prevalent frames and emotions in the chancellor’s communication, providing valuable insights into the German government’s stance and strategic communication during this critical geopolitical event. The results of the study revealed that the chancellor used the frames ‘effects of the Ukraine invasion’, ‘climate & environment’, ‘solidarity’ and ‘Russian aggression’ and communicated with positive sentiments. By examining the chancellor’s Twitter communication, this study contributes to the understanding of political communication in the digital era, particularly in the context of international crises, and offers implications for policymakers, scholars and the broader public.

Frames and sentiments of the Twitter communication by German Chancellor Scholz during the Russian invasion of Ukraine

Politics in Central Europe

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

In a complex information environment, Russia’s invasion of Ukraine presents a major challenge to the communication of political leaders throughout the world....

Frames and sentiments of the Twitter communication by German Chancellor Scholz during the Russian invasion of Ukraine

Online veröffentlicht: 28. Sept. 2023

Seitenbereich: 593 - 620

DOI: https://doi.org/10.2478/pce-2023-0028

Schlüsselwörter
Olaf Scholz, Russian invasion, sentiment analysis, social media

© 2023 Stefan Nisch, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Frames and sentiments of the Twitter communication by German Chancellor Scholz during the Russian invasion of Ukraine

Online veröffentlicht: 28. Sept. 2023

Seitenbereich: 593 - 620

DOI: https://doi.org/10.2478/pce-2023-0028

SchlüsselwörterOlaf Scholz, Russian invasion, sentiment analysis, social media

© 2023 Stefan Nisch, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Olaf Scholz, Russian invasion, sentiment analysis, social media