@inproceedings{8eb61449d6044dbb8cf75c6d3340411d,
title = "Healthy food depiction on social media: The case of kale on twitter",
abstract = "This food computing study analyzes Twitter microblog entries related to food. A particular attention here is paid to one specific healthy food - kale. Such an approach is chosen due to kale's popularity as a healthy food. By applying sentiment measurement, authors contribute to the understanding of text-based stories behind healthy food, and conclude that kale offers clear benefits for consumers via its specific health-related aspects (anti-inflammatory, immune system boosting, etc.) while taste is being left outside the discourse. The lack of any references to taste in kale-related social media stories leads to the conclusion that healthy food descriptions in general are short of hedonistic manifestations. Subsequently, this can be seen as one of the drawbacks of healthy food presentation textually vis-a-vis comfort foods. With this study authors add to the knowledge of the most efficient methods in shaping healthier consumer behaviors and inspire for further research of text-based information related to food.",
keywords = "Food blog, Food computing, Health, Kale, NLP, Sentiment-token bigram, Social media, Taste, Word association",
author = "Maija Kāle and Ebenezer Agbozo",
note = "Publisher Copyright: {\textcopyright} 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).",
year = "2020",
language = "English",
volume = "2865",
series = "CEUR Workshop Proceedings",
publisher = "CEUR",
pages = "51--62",
booktitle = "Ceur Workshop Proceedings",
}