Volume 11, Issue 3 (12-2024)
Human Information Interaction 2024, 11(3): 0-0 |
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Moradi M. Analysis of Users' Interaction with E-Marketers' Posts on Instagram Social Network. Human Information Interaction 2024; 11 (3)
URL: http://hii.khu.ac.ir/article-1-3181-en.html
URL: http://hii.khu.ac.ir/article-1-3181-en.html
Assistant Professor, Department of Computer Engineering, Faculty of Engineering, Bozorgmehr University of Qaenat, Qaenat, Iran
Abstract: (113 Views)
Background and Purpose: Social networks and their increasing influence among different users in all parts of the world have made these networks become suitable tools for advertising and e-commerce. The Instagram social network is known as one of the powerful marketing tools, and increasing views, likes and comments on Instagram plays an important role in the visibility of businesses. The purpose of this research is to analyze the behavior of users when faced with the posts of electronic marketers on the social network Instagram in order to increase the interactions of users with the posts of electronic marketers.
Method: According to library studies, factors influencing the number of visits, likes and comments of e-marketers' posts on the Instagram social network have been extracted. After extracting the data corresponding to each identified factor, the weight and importance of each has been calculated based on the regression model. Also, by using data mining techniques, a decision tree classification model has been created to predict and manage the status of posts in order to increase the number of visits, likes and comments.
Results: Directly, factors such as "number of posts", "number of followers", "post type", "post content" and "post time" are potential factors that influence the number of views, likes and comments. According to the obtained results, the "post content (survey)" factor with a positive sign and a coefficient of 420,290.616 had the most positive effect on the number of views of a post. The factor "post content with discount" having a positive sign and a coefficient of 5417.751 had the most positive effect on the liking of a post. The factor "post content (discount)" having a positive sign and a coefficient of 2164.016 had the most positive effect on the number of comments of a post.
Conclusion: Based on the extracted effective factors, calculating the weight and importance of each factor and the created decision tree model, posts can be managed to increase the number of visits, likes and comments.
Method: According to library studies, factors influencing the number of visits, likes and comments of e-marketers' posts on the Instagram social network have been extracted. After extracting the data corresponding to each identified factor, the weight and importance of each has been calculated based on the regression model. Also, by using data mining techniques, a decision tree classification model has been created to predict and manage the status of posts in order to increase the number of visits, likes and comments.
Results: Directly, factors such as "number of posts", "number of followers", "post type", "post content" and "post time" are potential factors that influence the number of views, likes and comments. According to the obtained results, the "post content (survey)" factor with a positive sign and a coefficient of 420,290.616 had the most positive effect on the number of views of a post. The factor "post content with discount" having a positive sign and a coefficient of 5417.751 had the most positive effect on the liking of a post. The factor "post content (discount)" having a positive sign and a coefficient of 2164.016 had the most positive effect on the number of comments of a post.
Conclusion: Based on the extracted effective factors, calculating the weight and importance of each factor and the created decision tree model, posts can be managed to increase the number of visits, likes and comments.
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