Sentiment Analysis of Japanese Twitter Users Regarding the Ukraine-Russia War and Its Implications for Security Policy

This study analyzes the emotional reactions of Japanese Twitter users to the Ukraine-Russia war to provide insights into national security policy. Using a large dataset of war-related tweets from Kaggle, a Japanese-specific dataset was created and analyzed with an emotion classification model based on Plutchik's Wheel of Emotions, comprising eight emotions. The analysis revealed prominent emotions of sadness, fear, anger, and disgust in response to rapid developments and atrocities, while positive emotions like joy and anticipation were also observed concerning support for Ukraine and hopes for peace. Sadness was strongly associated with tweets about war damage and loss of life, while fear and disgust responded to war's cruelty and injustice. Joy and anticipation reflected Japanese pacifism. These findings suggest the government needs to provide real-time, transparent information to reduce public anxiety and fear, pursue war crimes, and strengthen international human rights protections. Enhancing international support and peacebuilding policies is crucial. Continuous improvements in natural language processing (NLP) technology are needed to enhance sentiment analysis accuracy and real-time capabilities. This study demonstrates that leveraging social media sentiment data is vital for enhancing security intelligence in national security strategy.