Online opinions, sentiments and news framing of the first nuclear referendum in Taiwan: a mix-method approach

Abstract

ABSTRACT This mixed-method study uses a big data approach to examine cross-platform public sentiments towards Taiwan’s first nuclear energy referendum, and further conducts content analysis for nuclear news framing strategies. Sentiment analysis shows polarized affective attitudes towards Go Green with Nuclear (GGWN) referendum, regardless of media types. News coverage and social media contents reveal significant sentiment differences in narrating the referendum, nuclear energy, and political party-related issues. Polarized political party-related nuclear claims tend to show negative sentiments. As for agenda setting, the big data analysis shows that politics dominate nuclear narratives on news, Facebook and forums. In addition, content analysis reveals that the majority of news articles involve politics, but rarely report on energy and environmental subjects. In terms of generic news framing strategies, dramatic framing is used more than substantive framing in nuclear narratives. Conflict is the leading framing, followed by action. As for environmental news framing, most GGWN-related news is not eco-centric. Eco-efficient framing is most used to emphasize economic growth, national development and people’s livelihood. Moreover, mainstream and alternative media show no significant differences in using generic and environmental news framing to report nuclear referendum issues. Implications are discussed.