Gen Z Protests and the Ethics of AI-Generated Political Images: A Sentiment Analysis of Kenyan Twitter Discourse

The rapid, unprecedented advancement of artificial intelligence (AI) has transformed political discourse in Kenya, especially in digital activism. The current study examines the recent Gen Z protests and the role of AI-generated political images in shaping public sentiment on Kenyan X, specifically focusing on how these images have been used to criticize the head of state. The study adopts a quantitative research design, with sentiment analysis conducted on 680 tweets comprising between 80 and 100 responses to original AI-generated political images. The researcher harvested the raw data from X using TwReplyExport and developed a Python-based sentiment analysis model. The framework classified the responses as positive, negative, or neutral. The findings reveal that AI-generated political imagery is highly engaged on X, with posts receiving thousands of likes and retweets. Besides, there is a strong prevalence of positive sentiment. Indeed, while these AI-generated images effectively amplify digital activism and political narratives, they raise serious ethical concerns about digital manipulation, misinformation, and the issue of ideological polarization. The neutral sentiments in these tweets could imply that some users are skeptical about this kind of digital activism, which shows a growing need for media literacy and transparency. Moreover, the use of AI-generated political imagery raises concerns about the potential for echo chambers and the increasingly deepening political divides. All these problems underline the necessity for ethical guidelines and regulatory changes to address risks connected with AI-generated misinformation as part of political communication.

Authors

Publication Details

Journal
International Journal of Research and Innovation in Applied Science
Published
2025-04-29
DOI
https://doi.org/10.51584/ijrias.2025.10040012
Citations
1
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
2.48
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article

Gen Z Protests and the Ethics of AI-Generated Political Images: A Sentiment Analysis of Kenyan Twitter Discourse

Boniface Kimwere
1 citations
International Journal of Research and Innovation in Applied Science
Hate Speech and Cyberbullying Detection
2.48
article

Gen Z Protests and the Ethics of AI-Generated Political Images: A Sentiment Analysis of Kenyan Twitter Discourse

Boniface Kimwere
article en
1 citations

Abstract

The rapid, unprecedented advancement of artificial intelligence (AI) has transformed political discourse in Kenya, especially in digital activism. The current study examines the recent Gen Z protests and the role of AI-generated political images in shaping public sentiment on Kenyan X, specifically focusing on how these images have been used to criticize the head of state. The study adopts a quantitative research design, with sentiment analysis conducted on 680 tweets comprising between 80 and 100 responses to original AI-generated political images. The researcher harvested the raw data from X using TwReplyExport and developed a Python-based sentiment analysis model. The framework classified the responses as positive, negative, or neutral. The findings reveal that AI-generated political imagery is highly engaged on X, with posts receiving thousands of likes and retweets. Besides, there is a strong prevalence of positive sentiment. Indeed, while these AI-generated images effectively amplify digital activism and political narratives, they raise serious ethical concerns about digital manipulation, misinformation, and the issue of ideological polarization. The neutral sentiments in these tweets could imply that some users are skeptical about this kind of digital activism, which shows a growing need for media literacy and transparency. Moreover, the use of AI-generated political imagery raises concerns about the potential for echo chambers and the increasingly deepening political divides. All these problems underline the necessity for ethical guidelines and regulatory changes to address risks connected with AI-generated misinformation as part of political communication.

International Journal of Research and Innovation in Applied ScienceVol. X(IV)
Openalex Percentile: Top 11%
Hate Speech and Cyberbullying Detection
2.48
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