Enhancing Artificial Intelligence for Twitter-based Public Discourse on Food Security During the COVID-19 Pandemic

Abstract

Objective: Food security during public health emergencies relies on situational awareness of needs and resources. Artificial intelligence (AI) has revolutionized situational awareness during crises, allowing the allocation of resources to needs through machine learning algorithms. Limited research exists monitoring Twitter for changes in the food security-related public discourse during the COVID-19 pandemic. We aim to address that gap with AI by classifying food security topics on Twitter and showing topic frequency per day. Methods: Tweets were scraped from Twitter from January 2020 through December 2021 using food security keywords. Latent Dirichlet Allocation (LDA) topic modeling was performed, followed by time-series analyses on topic frequency per day. Results: 237,107 tweets were scraped and classified into topics, including food needs and resources, emergency preparedness and response, and mental/physical health. After the WHO’s pandemic declaration, there were relative increases in topic density per day regarding food pantries, food banks, economic and food security crises, essential services, and emergency preparedness advice. Threats to food security in Tigray emerged in 2021. Conclusions: AI is a powerful yet underused tool to monitor food insecurity on social media. Machine learning tools to improve emergency response should be prioritized, along with measurement of impact. Further food insecurity word patterns testing, as generated by this research, with supervised machine learning models can accelerate the uptake of these tools by policymakers and aid organizations.

Using Natural Language Processing to Explore Social Media Opinions on Food Security: Sentiment Analysis and Topic Modeling Study

“…Martin et al [76] also found topics similar to those in our study, with food assistance, needs, and resources found to be the most dominant topic category, and these topics similarly discussed free food, donation, government assistance, food systems, and food banks. Martin et al [76] also highlighted the topic of emergency preparedness, which covered individual family crises, COVID-19-related food insecurity, and emergency aid in Tigray, all of which were discussed in tweets in our study. The time-series topic analysis by Benites-Lazaro et al [77] highlighted discussions on ethanol production (the topic of the study) and food security dominated by government bodies in comparison with nongovernment and media and peaking from 2007 to 2009, which aligned with the world food crisis.…”

“…Our study found an increase in the popularity of food security conversations at the beginning of the COVID-19 pandemic, with similar findings related to frequency of discussion to those of Mayasari et al [75], who also found that Australia was among the top countries in search frequency regarding food security. Similarly, Martin et al [76] used topic modeling of tweets related to food security during the COVID-19 pandemic and found an increase in posts on food security, particularly related to food banks and food relief. Martin et al [76] also found topics similar to those in our study, with food assistance, needs, and resources found to be the most dominant topic category, and these topics similarly discussed free food, donation, government assistance, food systems, and food banks.…”

“…Similarly, Martin et al [76] used topic modeling of tweets related to food security during the COVID-19 pandemic and found an increase in posts on food security, particularly related to food banks and food relief. Martin et al [76] also found topics similar to those in our study, with food assistance, needs, and resources found to be the most dominant topic category, and these topics similarly discussed free food, donation, government assistance, food systems, and food banks. Martin et al [76] also highlighted the topic of emergency preparedness, which covered individual family crises, COVID-19-related food insecurity, and emergency aid in Tigray, all of which were discussed in tweets in our study.…”