Exploring the Power of Multimodal Features for Predicting the Popularity of Social Media Image in a Tourist Destination
Social media platforms are widely used nowadays by various businesses to promote their products and services through multimedia content. Instagram is one of those platforms, which is used not only by companies to promote their products but also by local governments to promote tourist destinations. P...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Multimodal Technologies and Interaction |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2414-4088/4/3/64 |
| _version_ | 1797554510395080704 |
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| author | Vibhuti Gupta Kwanghee Jung Seung-Chul Yoo |
| author_facet | Vibhuti Gupta Kwanghee Jung Seung-Chul Yoo |
| author_sort | Vibhuti Gupta |
| collection | DOAJ |
| description | Social media platforms are widely used nowadays by various businesses to promote their products and services through multimedia content. Instagram is one of those platforms, which is used not only by companies to promote their products but also by local governments to promote tourist destinations. Predicting the popularity of the promotional tourist destination images helps marketers to plan strategically. However, given the abundance of images posted on Instagram daily, identifying the factors that determine the popularity of an image is a big challenge, due to informal and noisy visual content, frequent content evolution, a lack of explicit visual elements, and people’s informal behavior in liking, commenting on, and viewing the images. We present an approach to identify the factors most responsible for the popularity of tourist destinations-related images on Instagram. Our approach provides a proof of concept for an artificial intelligence (AI)-based real-time content management system, which will help to promote a tourist destination. The experiments on a collection of posts crawled from the official Instagram account of Jeju Island, which is one of the most popular tourist destinations in Korea, show that the recency of the post is the most important predictor of the number of likes and comments it will receive. Moreover, the combination of visual content and context features is an excellent predictor of popularity. The number of likes and comments are found to be complementary to each other for predicting image popularity. |
| first_indexed | 2024-03-10T16:33:11Z |
| format | Article |
| id | doaj.art-b89915616e1f424aa1d07613a7d78fc0 |
| institution | Directory Open Access Journal |
| issn | 2414-4088 |
| language | English |
| last_indexed | 2024-03-10T16:33:11Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Multimodal Technologies and Interaction |
| spelling | doaj.art-b89915616e1f424aa1d07613a7d78fc02023-11-20T12:44:02ZengMDPI AGMultimodal Technologies and Interaction2414-40882020-09-01436410.3390/mti4030064Exploring the Power of Multimodal Features for Predicting the Popularity of Social Media Image in a Tourist DestinationVibhuti Gupta0Kwanghee Jung1Seung-Chul Yoo2Department of Pediatrics, University of Michigan; Ann Arbor, MI 48105, USADepartment of Educational Psychology and Leadership, Texas Tech University; Lubbock, TX 79409, USADivision of Communication & Media, Ewha Womans University; Seoul 03760, KoreaSocial media platforms are widely used nowadays by various businesses to promote their products and services through multimedia content. Instagram is one of those platforms, which is used not only by companies to promote their products but also by local governments to promote tourist destinations. Predicting the popularity of the promotional tourist destination images helps marketers to plan strategically. However, given the abundance of images posted on Instagram daily, identifying the factors that determine the popularity of an image is a big challenge, due to informal and noisy visual content, frequent content evolution, a lack of explicit visual elements, and people’s informal behavior in liking, commenting on, and viewing the images. We present an approach to identify the factors most responsible for the popularity of tourist destinations-related images on Instagram. Our approach provides a proof of concept for an artificial intelligence (AI)-based real-time content management system, which will help to promote a tourist destination. The experiments on a collection of posts crawled from the official Instagram account of Jeju Island, which is one of the most popular tourist destinations in Korea, show that the recency of the post is the most important predictor of the number of likes and comments it will receive. Moreover, the combination of visual content and context features is an excellent predictor of popularity. The number of likes and comments are found to be complementary to each other for predicting image popularity.https://www.mdpi.com/2414-4088/4/3/64artificial intelligencecontent management systemstrategic communication |
| spellingShingle | Vibhuti Gupta Kwanghee Jung Seung-Chul Yoo Exploring the Power of Multimodal Features for Predicting the Popularity of Social Media Image in a Tourist Destination Multimodal Technologies and Interaction artificial intelligence content management system strategic communication |
| title | Exploring the Power of Multimodal Features for Predicting the Popularity of Social Media Image in a Tourist Destination |
| title_full | Exploring the Power of Multimodal Features for Predicting the Popularity of Social Media Image in a Tourist Destination |
| title_fullStr | Exploring the Power of Multimodal Features for Predicting the Popularity of Social Media Image in a Tourist Destination |
| title_full_unstemmed | Exploring the Power of Multimodal Features for Predicting the Popularity of Social Media Image in a Tourist Destination |
| title_short | Exploring the Power of Multimodal Features for Predicting the Popularity of Social Media Image in a Tourist Destination |
| title_sort | exploring the power of multimodal features for predicting the popularity of social media image in a tourist destination |
| topic | artificial intelligence content management system strategic communication |
| url | https://www.mdpi.com/2414-4088/4/3/64 |
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