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

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

This includes degree modifiers that affect the intensity of the sentiment of a sentence. That is, “the service is very good” has a higher positive sentiment than “the service is good” because of the addition of “very” [59]. VADER also uses a lexicon with words assigned to a polarity on a scale of –1 (very negative) to +1 (very positive) based on the average polarity score of the words within the lexicon assigned by 10 independent human raters [59].

Annika Molenaar, Dickson Lukose, Linda Brennan, Eva L Jenkins, Tracy A McCaffrey

J Med Internet Res 2024;26:e47826

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Article has an altmetric score of 4

Prevalence and Correlates of Dietary and Nutrition Information Seeking Through Various Web-Based and Offline Media Sources Among Japanese Adults: Web-Based Cross-Sectional Study

Prevalence and Correlates of Dietary and Nutrition Information Seeking Through Various Web-Based and Offline Media Sources Among Japanese Adults: Web-Based Cross-Sectional Study

On a global scale, poor diet quality is a major risk factor for premature mortality and morbidity, accounting for 22% of total deaths and 15% of disability-adjusted life years annually; these estimates are even higher in East Asian countries, including Japan (30% and 21%, respectively) [1].

Kentaro Murakami, Nana Shinozaki, Tsuyoshi Okuhara, Tracy A McCaffrey, M Barbara E Livingstone

JMIR Public Health Surveill 2024;10:e54805

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Article has an altmetric score of 22

Web-Based Content on Diet and Nutrition Written in Japanese: Infodemiology Study Based on Google Trends and Google Search

Web-Based Content on Diet and Nutrition Written in Japanese: Infodemiology Study Based on Google Trends and Google Search

A value of 100 indicates the peak of popularity (100% popularity in a given period and location), whereas 0 indicates complete disinterest (0%) [19]. The engine enables the analysis of a chosen phrase in a selected region and period (since January 2004). Google Trends allows comparison of up to 5 terms at the same time. In such cases, RSV is adjusted, with RSV=100 representing the highest popularity of one of the chosen phrases. Google Trends may qualify the analyzed phrases as search term or topic.

Kentaro Murakami, Nana Shinozaki, Nana Kimoto, Hiroko Onodera, Fumi Oono, Tracy A McCaffrey, M Barbara E Livingstone, Tsuyoshi Okuhara, Mai Matsumoto, Ryoko Katagiri, Erika Ota, Tsuyoshi Chiba, Yuki Nishida, Satoshi Sasaki

JMIR Form Res 2023;7:e47101

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Article has an altmetric score of 6

Accuracy and Cost-effectiveness of Technology-Assisted Dietary Assessment Comparing the Automated Self-administered Dietary Assessment Tool, Intake24, and an Image-Assisted Mobile Food Record 24-Hour Recall Relative to Observed Intake: Protocol for a Randomized Crossover Feeding Study

Accuracy and Cost-effectiveness of Technology-Assisted Dietary Assessment Comparing the Automated Self-administered Dietary Assessment Tool, Intake24, and an Image-Assisted Mobile Food Record 24-Hour Recall Relative to Observed Intake: Protocol for a Randomized Crossover Feeding Study

AMPM is a web-based interface designed for surveillance, typically implemented in-person by a trained interviewer, which adds to the cost of undertaking large-scale surveys. The AMPM provides a structured interview format with specific probes in 5 structured sets or passes: a quick list, forgotten foods pass, time and occasion pass, detail pass, and final review [10]. Portion size estimation is addressed using a food model booklet.

Clare Whitton, Janelle D Healy, Clare E Collins, Barbara Mullan, Megan E Rollo, Satvinder S Dhaliwal, Richard Norman, Carol J Boushey, Edward J Delp, Fengqing Zhu, Tracy A McCaffrey, Sharon I Kirkpatrick, Paul Atyeo, Syed Aqif Mukhtar, Janine L Wright, César Ramos-García, Christina M Pollard, Deborah A Kerr

JMIR Res Protoc 2021;10(12):e32891

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Article has an altmetric score of 8

What People “Like”: Analysis of Social Media Strategies Used by Food Industry Brands, Lifestyle Brands, and Health Promotion Organizations on Facebook and Instagram

What People “Like”: Analysis of Social Media Strategies Used by Food Industry Brands, Lifestyle Brands, and Health Promotion Organizations on Facebook and Instagram

In identifying the most successful strategies regarding engagement of users with a post, it will be possible to make recommendations for the improvement of nutrition-related health promotion using social media. A glossary of terms has been provided in Multimedia Appendix 1.

Karen Michelle Michell Klassen, Emily S Borleis, Linda Brennan, Mike Reid, Tracy A McCaffrey, Megan SC Lim

J Med Internet Res 2018;20(6):e10227

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Article has an altmetric score of 9