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

BACKGROUND: Social media has the potential to be of great value in understanding patterns in public health using large-scale analysis approaches (eg, data science and natural language processing [NLP]), 2 of which have been used in public health: sentiment analysis and topic modeling; however, their use in the area of food security and public health nutrition is limited. OBJECTIVE: This study aims to explore the potential use of NLP tools to gather insights from real-world social media data on the public health issue of food security. METHODS: A search strategy for obtaining tweets was developed using food security terms. Tweets were collected using the Twitter application programming interface from January 1, 2019, to December 31, 2021, filtered for Australia-based users only. Sentiment analysis of the tweets was performed using the Valence Aware Dictionary and Sentiment Reasoner. Topic modeling exploring the content of tweets was conducted using latent Dirichlet allocation with BigML (BigML, Inc). Sentiment, topic, and engagement (the sum of likes, retweets, quotations, and replies) were compared across years. RESULTS: In total, 38,070 tweets were collected from 14,880 Twitter users. Overall, the sentiment when discussing food security was positive, although this varied across the 3 years. Positive sentiment remained higher during the COVID-19 lockdown periods in Australia. The topic model contained 10 topics (in order from highest to lowest probability in the data set): "Global production," "Food insecurity and health," "Use of food banks," "Giving to food banks," "Family poverty," "Food relief provision," "Global food insecurity," "Climate change," "Australian food insecurity," and "Human rights." The topic "Giving to food banks," which focused on support and donation, had the highest proportion of positive sentiment, and "Global food insecurity," which covered food insecurity prevalence worldwide, had the highest proportion of negative sentiment. When compared with news, there were some events, such as COVID-19 support payment introduction and bushfires across Australia, that were associated with high periods of positive or negative sentiment. Topics related to food insecurity prevalence, poverty, and food relief in Australia were not consistently more prominent during the COVID-19 pandemic than before the pandemic. Negative tweets received substantially higher engagement across 2019 and 2020. There was no clear relationship between topics that were more likely to be positive or negative and have higher or lower engagement, indicating that the identified topics are discrete issues. CONCLUSIONS: In this study, we demonstrated the potential use of sentiment analysis and topic modeling to explore evolution in conversations on food security using social media data. Future use of NLP in food security requires the context of and interpretation by public health experts and the use of broader data sets, with the potential to track dimensions or events related to food security to inform evidence-based decision-making in this area.

The use of sentiment and emotion analysis and data science to assess the language of nutrition-, food- and cooking-related content on social media: a systematic scoping review.

Social media data are rapidly evolving and accessible, which presents opportunities for research. Data science techniques, such as sentiment or emotion analysis which analyse textual emotion, provide an opportunity to gather insight from social media. This paper describes a systematic scoping review of interdisciplinary evidence to explore how sentiment or emotion analysis methods alongside other data science methods have been used to examine nutrition, food and cooking social media content. A PRISMA search strategy was used to search nine electronic databases in November 2020 and January 2022. Of 7325 studies identified, thirty-six studies were selected from seventeen countries, and content was analysed thematically and summarised in an evidence table. Studies were published between 2014 and 2022 and used data from seven different social media platforms (Twitter, YouTube, Instagram, Reddit, Pinterest, Sina Weibo and mixed platforms). Five themes of research were identified: dietary patterns, cooking and recipes, diet and health, public health and nutrition and food in general. Papers developed a sentiment or emotion analysis tool or used available open-source tools. Accuracy to predict sentiment ranged from 33·33% (open-source engine) to 98·53% (engine developed for the study). The average proportion of sentiment was 38·8% positive, 46·6% neutral and 28·0% negative. Additional data science techniques used included topic modelling and network analysis. Future research requires optimising data extraction processes from social media platforms, the use of interdisciplinary teams to develop suitable and accurate methods for the subject and the use of complementary methods to gather deeper insights into these complex data.

Assessing the Credibility and Authenticity of Social Media Content for Applications in Health Communication: Scoping Review.

BACKGROUND: Nutrition science is currently facing issues regarding the public's perception of its credibility, with social media (SM) influencers increasingly becoming a key source for nutrition-related information with high engagement rates. Source credibility and, to an extent, authenticity have been widely studied in marketing and communications but have not yet been considered in the context of nutrition or health communication. Thus, an investigation into the factors that impact perceived source and message credibility and authenticity is of interest to inform health communication on SM. OBJECTIVE: This study aims to explore the factors that impact message and source credibility (which includes trustworthiness and expertise) or authenticity judgments on SM platforms to better inform nutrition science SM communication best practices. METHODS: A total of 6 databases across a variety of disciplines were searched in March 2019. The inclusion criteria were experimental studies, studies focusing on microblogs, studies focusing on healthy adult populations, and studies focusing on either source credibility or authenticity. Exclusion criteria were studies involving participants aged under 18 years and clinical populations, gray literature, blogs, WeChat conversations, web-based reviews, non-English papers, and studies not involving participants' perceptions. RESULTS: Overall, 22 eligible papers were included, giving a total of 25 research studies. Among these studies, Facebook and Twitter were the most common SM platforms investigated. The most effective communication style differed depending on the SM platform. Factors reported to impact credibility included language used online, expertise heuristics, and bandwagon heuristics. No papers were found that assessed authenticity. CONCLUSIONS: Credibility and authenticity are important concepts studied extensively in the marketing and communications disciplines; however, further research is required in a health context. Instagram is a less-researched platform in comparison with Facebook and Twitter.

Re-Licious: Co-Design with Adolescents to Turn Leftovers into Delicious and Healthy Meals-A School-Based Pilot Intervention.

One-third of the food produced globally is lost or wasted, and one cause is consumer leftovers. Re-licious was an eight-week pilot intervention aiming to increase awareness of food waste and healthy eating by building adolescents' ability to prepare and cook leftovers. Re-licious used a co-design approach and was piloted in a secondary school, half of which was during a COVID-19 lockdown period. Students watched videos on food waste and healthy eating during class. They identified leftover ingredients at home and repurposed ingredients to create recipes. Students co-created recipe criteria to ensure the personal relevance of the recipes. They completed pre- and post-intervention questionnaires (n = 40) about food waste and motivation and interest in healthy eating. Four group interviews were conducted. The factors identified as important in the co-creation sessions were preparation time, cost, healthiness, and sustainability. Participants with low motivation and interest in healthy eating decreased, and participants with high interest increased (p < 0.001). The intention to reduce food waste increased (p = 0.007), as did resourcefulness (p < 0.001) and personal norms (p = 0.048). Interviews highlighted the students' increased awareness of food waste and enjoyment of the intervention. With improvements based on this pilot, Re-licious could be adapted and re-trialled in a face-to-face format to educate young people about food waste.

Psycho-Behavioural Segmentation in Food and Nutrition: A Systematic Scoping Review of the Literature.

Inadequate dietary intakes are a key modifiable risk factor to reduce the risk of developing non-communicable diseases. To encourage healthy eating and behaviour change, innovative public health interventions are required. Social marketing, in particular segmentation, can be used to understand and target specific population groups. However, segmentation often uses demographic factors, ignoring the reasons behind why people behave the way they do. This review aims to explore the food and nutrition related research that has utilised psycho-behavioural segmentation. Six databases from were searched in June 2020. Inclusion criteria were: published 2010 onwards, segmentation by psycho-behavioural variables, outcome related to food or nutrition, and healthy adult population over 18 years. 30 studies were included; most were quantitative (n = 28) and all studies used post-hoc segmentation methods, with the tools used to segment the population varying. None of the segments generated were targeted in future research. Psycho-behavioural factors are key in understanding people's behaviour. However, when used in post-hoc segmentation, do not allow for effective targeting as there is no prior understanding of behaviours that need to change within each segment. In future, we should move towards hybrid segmentation to assist with the design of interventions that target behaviours such as healthy eating.

Strategies to Improve Health Communication: Can Health Professionals be Heroes?

Communicating evidence-based nutrition messages to the public is challenging and is often in conflict with popular opinions, particularly from social media influencers (SMIs). In order to increase engagement with nutrition professionals (NPs) on social media, we aimed to explore young adults' perceptions of the authenticity and trustworthiness of SMIs and NPs Instagram posts. A cross-sectional questionnaire was administered to students (n = 149) from an Australian University. Participants viewed a real-life Instagram profile and one post from both a NP and a SMI. Main outcomes were post authenticity and trustworthiness, and emotional message appeals measured on five-point Likert scales. Regression models were developed to assess whose post (the NP or SMI) was perceived to be more authentic and trustworthy. Participants were young adults (median age (25th, 75th percentiles): 20 (19,21)), with approximately half identifying as female. A high heroic message appeal (+1SD above mean) significantly increased the perceived authenticity of the NPs post only (p = 0.01). Post authenticity enhanced post trustworthiness, but only when a heroic message appeal was used by the NP. When appropriate, NPs should convey positive emotions such as bravery and success to enhance the authenticity and trustworthiness of their posts.

Beyond Body Weight: Design and Validation of Psycho-Behavioural Living and Eating for Health Segments (LEHS) Profiles for Social Marketing.

Obesity, sedentary behaviour, and poor dietary habits amongst young adults are growing concerns, with this age group being in a worse state of health and nutrition than adolescents and adults. This paper presents the procedures for establishing a new instrument for defining behaviours in relation to healthy lifestyle and food choices amongst young adults (Living and Eating for Health Segments: LEHS). The aim of this paper is to outline the instrument design protocol for external validation and to permit replication in other studies. The instrument design process used a multi-step social marketing instrument design method. This approach has previously been used in designing valid and reliable measures in marketing and consumer research, including social marketing. The protocol established six psycho-behavioural LEHS profiles for young adults. These profiles are: Lifestyle Mavens (15.4%), Aspirational Healthy Eaters (27.5%), Balanced-all Rounders (21.4%), Health Conscious (21.1%), Contemplating Another Day (11.2%), and Blissfully Unconcerned (3.4%). Each of these profiles provided insights into psycho-behavioural characteristics that can be used in designing apposite social media social marketing campaigns.