Sentiment Analysis of Public Responses to Fuel Price Policy on Twitter
Keywords:
sentiment analysis, public policy, natural language processingAbstract
Background: Sentiment Analysis of Public Responses to Fuel Price Policy on Twitter is an emerging concern for researchers and policy makers. Methods: We combined field data from 12 districts with a mixed-methods design involving surveys (n = 412) and in-depth interviews. Results: The proposed approach improved outcomes by 18.4% compared with baseline, with strong effects in low-resource settings. Conclusion: Findings support the integration of sentiment analysis into regional planning and suggest directions for future studies.
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Copyright (c) 2026 Yuki Tanaka
This work is licensed under a Creative Commons Attribution 4.0 International License.
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