Abstract
With the increasing use of data generated through social media for behavioral studies, it is considerable to study food consumption behavior of people using social media analysis. This study focused on concepts of eating behavior and to describe and analyze the content of food-related posts viewed on social media sites, particularly Twitter. Collection and analysis of data were provided through examining the content of tweets about four eating situations, namely breakfast, lunch, dinner, and snack/snacking. Using Twitter’s API, a total of 59,177 unique tweets were retrieved and analyzed by applying text mining techniques and manual analysis. Reflecting the results from previous food-related research, knowledge about what foods were consumed, when, where, and why was contained within the tweets, and was captured through content analysis. The findings of this study revealed that people in their tweets tended to describe eating situations, and refer to foods and beverages consumed, as well as to express emotions towards food. This study also provides suggestion towards the diet and health-related behavior change for preventing the obesity as well as improving the health condition. The results of this study can be used as a recommendation towards the measurement of public policy dealing with health of the people.
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Acknowledgements
This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2017R1D1A3B04032905) and by the Ministry of Trade, Industry and Energy (MOTIE), KOREA through the Education program for Creative and Industrial Convergence (Grant number N0000717).
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Dondokova, A., Aich, S., Kim, HC., Huh, G.H. (2019). A Text Mining Approach to Study Individuals’ Food Choices and Eating Behavior Using Twitter Feeds. In: Hung, J., Yen, N., Hui, L. (eds) Frontier Computing. FC 2018. Lecture Notes in Electrical Engineering, vol 542. Springer, Singapore. https://doi.org/10.1007/978-981-13-3648-5_60
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DOI: https://doi.org/10.1007/978-981-13-3648-5_60
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