Decoding hotline’s information with text-mining: A protocol for improving tobacco control in Shanghai

Abstract

Tobacco consumption in China remains the primary cause of preventable mortality, with Shanghai being particularly affected by issues related to secondhand smoke exposure. This study explores the role of the public service hotline 12345, a grassroots initiative in Shanghai, in capturing public sentiment and assessing the effectiveness of anti-smoking regulations. Our research aims to accurately and deeply understand the implementation and feedback of smoking control policies: by identifying high-frequency points and prominent issues in smoking control work based on the smoking control work order data received by the health hotline 12320. The results of this study will assist government enforcement agencies in improving smoking monitoring and clarify the direction for improving smoking control measures. Text-mining techniques were employed to analyze a dataset comprising 78011 call sheets, all related to tobacco control and collected from the hotline between 1 January 2015 and 31 December 2019. This methodological approach aims to uncover prevalent themes and sentiments in the public discourse on smoking and its regulation, as reflected in the hotline interactions. Our study identified hotspots and the issues of greatest concern to citizens. Additionally, it provided recommendations to enforcement agencies to enhance their capabilities, optimize the allocation of human resources for smoking control monitoring, reduce enforcement costs and support for anti-smoking campaigns, thereby contributing to more effective tobacco control policies in the region.

Keywords

• hotline
• text-mining
• smoking ban
• audience-centered policymaking