Abstract
Take-away food (also referred to as “take-out” food in different regions of the world) is a very convenient and popular dining choice for millions of people. In this article, we collect online textual data regarding “take-away food safety” from Sina Weibo between 2015 and 2018 using the Octopus Collector. After the posts from Sina Weibo were preprocessed, users’ emotions and opinions were analyzed using natural language processing. To our knowledge, little work has studied public opinions regarding take-away food safety. This paper fills this gap by using latent Dirichlet allocation (LDA) and k-means to extract and cluster topics from the posts, allowing for the users’ emotions and related opinions to be mined and analyzed. The results of this research are as follows: (1) data analysis showed that the degree of topics have increased over the years, and there are a variety of topics about take-away food safety; (2) emotional analysis showed that 93.8% of the posts were positive; and (3) topic analysis showed that the topic of public discussion is diverse and rich. Our analysis of public opinion on take-away food safety generates insights for government and industry stakeholders to promote the healthy and vigorous development of the food industry.
Highlights
Food safety issues, such as melamine-contaminated milk powder, heavy metal-contaminated foods, additives which can lead to food poisoning, unhealthy preservatives, and fake foods, pose a great threat to public health [1]
A public and opinion analysis can help government express their related opinions and emotions on social platforms, such as and industry stakeholders to better understand the current situation and provide advice for better the best of our in knowledge, food To safety regulation the future.research on the evolution of online public opinions relating to the safety of take-away foods is limited
Term frequency–Inverse Document Frequency (TF-IDF), was used to measure the representativeness of words considering the times that the word appeared in a post, and the times it appeared in the corpus of all combined posts
Summary
Food safety issues, such as melamine-contaminated milk powder, heavy metal-contaminated foods, additives which can lead to food poisoning, unhealthy preservatives, and fake foods, pose a great threat to public health [1]. Responding the frequent of such laws practices For these complicated discussions, traditional data analysis is not enough to study the and regulations for the online food industry (including take-away food) to strengthen the measures public’s emotional opinions. A public and opinion analysis can help government express their related opinions and emotions on social platforms, such as and industry stakeholders to better understand the current situation and provide advice for better the best of our in knowledge, food To safety regulation the future.research on the evolution of online public opinions relating to the safety of take-away foods is limited. The purpose of this paper is to study the microblogging remarks related to the safety of take-away foods, identify topics of concern, and extract the topic information contained in large amounts of textual data. A public opinion analysis can help government and industry stakeholders to better understand the current situation and provide advice for better food safety regulation in the future
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