Analysis of Food Delivery Using Big Data: Comparative Study before and after COVID-19
This study examined consumers’ change in perception related to food delivery using big data before and after the COVID-19 crisis. This study identified words closely associated with the keyword “food delivery” based on big data from social media and investigated consumers’ perceptions of and needs f...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-09-01
|
| Series: | Foods |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2304-8158/11/19/3029 |
| _version_ | 1797479336634220544 |
|---|---|
| author | Jina Jang Eunjung Lee Hyosun Jung |
| author_facet | Jina Jang Eunjung Lee Hyosun Jung |
| author_sort | Jina Jang |
| collection | DOAJ |
| description | This study examined consumers’ change in perception related to food delivery using big data before and after the COVID-19 crisis. This study identified words closely associated with the keyword “food delivery” based on big data from social media and investigated consumers’ perceptions of and needs for food delivery and related issues before and after COVID-19. Results were derived through analysis methods such as text mining analysis, Concor analysis, and sentiment analysis. The research findings can be summarized as follows: In 2019, frequently appearing dining-related words were “dining-out,” “delivery,” “famous restaurant,” “delivery food,” “foundation,” “dish,” “family order,” and “delicious.” In 2021, these words were “delivery,” “delivery food,” “famous restaurant,” “foundation,” “COVID-19,” “dish,” “order,” “application,” and “family.” The analysis results for the food delivery sentimental network based on 2019 data revealed discourses revolving around delicious, delivery food, lunch box, and Korean food. For the 2021 data, discourses revolved around delivery food, recommend, and delicious. The emotional analysis, which extracted positive and negative words from the “food delivery” search word data, demonstrated that the number of positive keywords decreased by 2.85%, while negative keywords increased at the same rate. In addition, compared to the pre-COVID-19 pandemic era, a weakening trend in positive emotions and an increasing trend in negative emotions were detected after the outbreak of the COVID-19 pandemic; sub-emotions under the positive category (e.g., good feelings, joy, interest) decreased in 2021 compared to 2019, whereas sub-emotions under the negative category (e.g., sadness, fear, pain) increased. |
| first_indexed | 2024-03-09T21:44:24Z |
| format | Article |
| id | doaj.art-cae8577de87d4739a99bed34232f0571 |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-09T21:44:24Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-cae8577de87d4739a99bed34232f05712023-11-23T20:20:59ZengMDPI AGFoods2304-81582022-09-011119302910.3390/foods11193029Analysis of Food Delivery Using Big Data: Comparative Study before and after COVID-19Jina Jang0Eunjung Lee1Hyosun Jung2Nutritional Science and Food Management Department, Ewha Womans University, Seoul 03760, KoreaFood and Nutrition Major, School of Wellness Industry Convergence, Hankyong National University, Jungang-no, Anseong-si 17579, Gyeonggi-do, KoreaCenter for Converging Humanities, KyungHee University, Seoul 02447, KoreaThis study examined consumers’ change in perception related to food delivery using big data before and after the COVID-19 crisis. This study identified words closely associated with the keyword “food delivery” based on big data from social media and investigated consumers’ perceptions of and needs for food delivery and related issues before and after COVID-19. Results were derived through analysis methods such as text mining analysis, Concor analysis, and sentiment analysis. The research findings can be summarized as follows: In 2019, frequently appearing dining-related words were “dining-out,” “delivery,” “famous restaurant,” “delivery food,” “foundation,” “dish,” “family order,” and “delicious.” In 2021, these words were “delivery,” “delivery food,” “famous restaurant,” “foundation,” “COVID-19,” “dish,” “order,” “application,” and “family.” The analysis results for the food delivery sentimental network based on 2019 data revealed discourses revolving around delicious, delivery food, lunch box, and Korean food. For the 2021 data, discourses revolved around delivery food, recommend, and delicious. The emotional analysis, which extracted positive and negative words from the “food delivery” search word data, demonstrated that the number of positive keywords decreased by 2.85%, while negative keywords increased at the same rate. In addition, compared to the pre-COVID-19 pandemic era, a weakening trend in positive emotions and an increasing trend in negative emotions were detected after the outbreak of the COVID-19 pandemic; sub-emotions under the positive category (e.g., good feelings, joy, interest) decreased in 2021 compared to 2019, whereas sub-emotions under the negative category (e.g., sadness, fear, pain) increased.https://www.mdpi.com/2304-8158/11/19/3029food deliverydining out trendsocial mediabig dataCOVID-19 pandemic |
| spellingShingle | Jina Jang Eunjung Lee Hyosun Jung Analysis of Food Delivery Using Big Data: Comparative Study before and after COVID-19 Foods food delivery dining out trend social media big data COVID-19 pandemic |
| title | Analysis of Food Delivery Using Big Data: Comparative Study before and after COVID-19 |
| title_full | Analysis of Food Delivery Using Big Data: Comparative Study before and after COVID-19 |
| title_fullStr | Analysis of Food Delivery Using Big Data: Comparative Study before and after COVID-19 |
| title_full_unstemmed | Analysis of Food Delivery Using Big Data: Comparative Study before and after COVID-19 |
| title_short | Analysis of Food Delivery Using Big Data: Comparative Study before and after COVID-19 |
| title_sort | analysis of food delivery using big data comparative study before and after covid 19 |
| topic | food delivery dining out trend social media big data COVID-19 pandemic |
| url | https://www.mdpi.com/2304-8158/11/19/3029 |
| work_keys_str_mv | AT jinajang analysisoffooddeliveryusingbigdatacomparativestudybeforeandaftercovid19 AT eunjunglee analysisoffooddeliveryusingbigdatacomparativestudybeforeandaftercovid19 AT hyosunjung analysisoffooddeliveryusingbigdatacomparativestudybeforeandaftercovid19 |