• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.119-133
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• 2022

One of the most important current features of food related industry is the growth of food delivery service. Another notable food related culture is, with the advent of Youtube, the popularity of Mukbang, which refers to content that records eating. Based on these background, this study intended to focus on two things. First, we tried to see the impact of Youtube Mukbang and the sentiments of Mukbang comments on the number of related food deliveries. Next, we tried to set up the predictive modeling of chicken delivery order with machine learning method. We used Youtube Mukbang comments data as well as weather related data as main independent variables. The dependent variable used in this study is the number of delivery order of fried chicken. The period of data used in this study is from June 3, 2015 to September 30, 2019, and a total of 1,580 data were used. For the predictive modeling, we used machine learning methods such as linear regression, ridge, lasso, random forest, and gradient boost. We found that the sentiment of Youtube Mukbang and comments have impacts on the number of delivery orders. The prediction model with Mukban data we set up in this study had better performances than the existing models without Mukbang data. We also tried to suggest managerial implications to the food delivery service industry.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.273-281
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• 2021

In this paper, we propose a ways how YouTube Mukbang content attributes affect favorability, satisfaction, and brand selection, and suggest to use YouTube Mukbang contents, and to propose a strategic marketing plan using YouTube at the food franchise. This study conducted survey on 218 people who had watched chicken Mukbang among YouTube Mukbang contents. Through previous studies, YouTube content attributes were classified into informativity, entertainment, reliability, and attractiveness. To verify the hypothesis of the study, single regression and multiple regression analysis were conducted for verifying the relationship between variables. Key results of the study are as follows. First, it was found that YouTube Mukbang content attributes had a positive relationship with favorability. Second, it was found that YouTube Mukbang content attributes had a positive relationship with satisfaction. Third, it was found that favorability had an effect on satisfaction. Fourth, it was found that favorability influenced brand selection. Fifth, it was found that satisfaction did not affect brand selection. Based on these findings, a strategic approach will be needed to increase users' favorability by providing attractive and accurate information through YouTube Mukbang contents and to continuously improve brand choices through continuous favorability to revitalizing YouTube marketing at the food franchise.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.413-425
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• 2021

This study examines the motivation for using YouTube 'mukbang' content by integrating the use and satisfaction approach and the technology acceptance model, and identified the determinants that affect the continuous use intention. A survey was conducted on 358 YouTube 'mukbang' content users, and major results were derived through exploratory/confirmatory factor analysis and path analysis using the SPSS 21.0 program and the AMOS 21.0 program. The main results are presented as follows. First, information seeking motive, stress relief motive, and time spending motive had a positive effect on perceived usefulness, and information seeking motive and time spending motive had a positive effect on perceived ease of use. Second, information seeking motivation, stress relief motivation, and time spending motivate had a positive effect on perceived enjoyment and perceived novelty. Third, perceived enjoyment did not have a significant effect on perceived usefulness. Fourth, both perceived enjoyment and perceived novelty had a positive effect on continuous use intention. Fifth, perceived ease of use had a positive effect on perceived usefulness, and perceived ease of use and perceived usefulness had a positive effect on continuous use intention. This study will have academic significance in that it elaborates a model that can identify the continuous use of YouTube 'mukbang' content by integrating the uses and gratifications approach, and technology acceptance model. Future follow-up studies should contribute to the refinement of models related to the determinants of the intention to continue using YouTube's 'mukbang' content through an attempt to integrate various models.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.49-55
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• 2023

In this study, models for predicting the popularity of mukbang content on YouTube were proposed, and factors influencing the popularity of mukbang content were identified through post-analysis. To accomplish this, information on 22,223 pieces of content was collected from top mukbang channels in terms of subscribers using APIs and Pretty Scale. Machine learning algorithms such as Random Forest, XGBoost, and LGBM were used to build models for predicting views and likes. The results of SHAP analysis showed that subscriber count had the most significant impact on view prediction models, while the attractiveness of a creator emerged as the most important variable in the likes prediction model. This confirmed that the precursor factors for content views and likes reactions differ. This study holds academic significance in analyzing a large amount of online content and conducting empirical analysis. It also has practical significance as it informs mukbang creators about viewer content consumption trends and provides guidance for producing high-quality, marketable content.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.359-372
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• 2022

This study aimed to derive a YouTube content strategy that can be exposed to Trending for a long time by comparing the features of 20 channels in the short/long term using 'YouTube Trending' data in 2021. First, through Pearson's correlation analysis, we found that various factors such as 'the number of title or tag letters' related to long-term exposure, and set this as an index to compare features. As a result, 1)'video title' of about 40-45 letters without excessive special characters, 2)'video length' within 10 minutes, 3)'Video description' is effective when writing 2-3 sentences and adding SNS information or including 3 key tags. Also, it would be more effective if you set key tag pairs such as (먹방, mukbang), (역대급, 레전드) derived through text mining. Through this, the channel will spread globally, bringing various advantages, and will be used as an indicator to evaluate the globality of the channel.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.400-407
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• 2021

Recently, mukbang and cookbang or cooking shows on TV and YouTube channels have increased, and the influences of these broadcasts on food consumption have been gradually increasing. There were several news articles on 'Baek Jong-won effect', in which the consumption of the agri-food Mr. Jong-won Baek mentioned on his broadcast soared, and even foods named after him are on the market. In this study, Mr. Jong-won Baek, who produces influential cooking contents through various media, was taken as a representative example. We evaluated if 'Baek Jong-won effect' exists on potato consumption, which Mr. Jong-won Baek broadcasted potato cooking recipes on TV and YouTube. After the potato recipe was broadcasted for the first time on the TV show called HomeFoodRescue, the differences in the amount of money to purchase potatoes before and after the broadcast were estimated by using the money amount to purchase data of Agri-food consumers panel and the difference-in-differences method at 6 time points (3, 6, 9, 12, 24, and 36 months). Among the time points analyzed, the potato purchases at post-broadcast were less than those at pre-broadcast. No results were observed suggesting the existence of 'Baek Jong-won effect' on potato consumption through HomeFoodRescue show in the study.

• Journal of Nutrition and Health
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• v.56 no.2
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• pp.203-216
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• 2023

Purpose: This study examines the weight control behavior depending on university students' motives of using social media. Methods: The participants were 447 university students in the Jeonbuk area. Collected data were analyzed using factor analysis, cluster analysis, analysis of variance, and χ² tests with SPSS v. 26.0. Considering the motives of using social media, we investigated the usage of social media, dietary behavior related to social media, and weight control behavior. Results: Using the K-clustering method, the motives to use social media were categorized into three clusters: cluster 1 was the interest-centered group, cluster 2 was the multipurpose information-seeking group, and cluster 3 was the relationship-centered group. Among the various social media sites, YouTube (86.8%), Instagram (76.1%), and Facebook (61.1%) were the most visited by the subjects. The dietary behavior related to social media in cluster 2 was significantly higher than clusters 1 and 3 (p < 0.001). Clusters 1 and 2 showed a significantly higher dissatisfaction with one's weight (p < 0.05) and consequent interest in weight control than cluster 3 (p < 0.001). Cluster 2 used weight control-related information from social media significantly more than other clusters (p < 0.05). Weight control experiences in cluster 1 and 2 were significantly higher than in cluster 3 (p < 0.001). Conclusion: Differences in dietary behavior related to social media and weight control behavior were observed between cluster types of motivation to use social media. Based on the usage motives of university students and their behaviors, we propose that educational programs should be conducted for weight control using social media.