Human Information Interaction

fa تحلیل تعامل کاربران با پست‌های بازاریابان الکترونیکی در شبکه اجتماعی اینستاگرام Analysis of Users' Interaction with E-Marketers' Posts on Instagram Social Network عمومى General پژوهشي Research <div style="text-align: justify;">زمینه و هدف: شبکه‌های اجتماعی و نفوذ هر چه بیشتر آن‌ها در میان کاربران مختلف در تمام نقاط دنیا باعث شده است که این شبکه‌ها به ابزارهایی مناسب برای تبلیغات و تجارت الکترونیک تبدیل شوند. شبکه اجتماعی اینستاگرام به عنوان یکی از ابزارهای قدرتمند بازاریابی شناخته می‌شود و افزایش بازدید، پسند و نظر در اینستاگرام، نقش مهمی در دیده شدن کسب‌وکارها دارد. هدف این پژوهش تحلیل رفتار کاربران در مواجهه با پست‌های بازاریابان الکترونیکی در شبکه اجتماعی اینستاگرام به‌منظور افزایش تعاملات کاربران با پست‌های بازاریابان الکترونیکی می‌باشد. روش پژوهش: طبق مطالعات کتابخانه‌ای، عوامل تاثیرگذار بر میزان بازدید، پسند و نظر پست‌های بازاریابان الکترونیکی در شبکه اجتماعی اینستاگرام استخراج شده است. پس از استخراج داده‌های متناسب با هر عامل شناسایی شده، به محاسبه وزن و اهمیت هر یک بر اساس مدل رگرسیون پرداخته شده است. همچنین با استفاده از تکنیک‌های داده‌کاوی به ایجاد مدل طبقه‌بند درخت تصمیم برای پیش‌بینی و مدیریت پست‌ها به‌منظور افزایش میزان بازدید، پسند و نظر، ایجاد شده است. یافته‌ها: به طور مستقیم، عواملی مانند «تعداد پست‌ها»، «تعداد دنبال‌کنندگان»، «نوع پست»، «محتوای پست» و «زمان پست» عوامل بالقوه‌ای هستند که بر تعداد بازدید، پسند‌ها و نظر‌ها تأثیرگذار هستند. طبق نتایج بدست آمده عامل «محتوای پست با موضوع نظرسنجی» با دارا بودن علامت مثبت و ضریب 420290.616 بیشترین تاثیر مثبت را بر میزان بازدید یک پست داشته است. عامل «محتوای پست با موضوع تخفیف» با دارا بودن علامت مثبت و ضریب 5417.751 بیشترین تاثیر مثبت را بر میزان پسند یک پست داشته است. عامل «محتوای پست با موضوع تخفیف» با دارا بودن علامت مثبت و ضریب 2164.016 بیشترین تاثیر مثبت را بر میزان نظر یک پست داشته است. نتیجه‌گیری: بر اساس عوامل موثر استخراج‌شده، محاسبه وزن و اهمیت هر عامل و مدل درخت تصمیم ایجادشده می‌توان به مدیریت پست‌ها در جهت افزایش میزان بازدید، پسند و نظر پرداخت.  </div> <div style="text-align: justify;">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. Today, businesses have come to understand that social networks are and will continue to be a means of doing business. Instagram is a popular social network based on video and images. This social network is known as one of the powerful marketing tools. The number of views, likes and comments on social networks, including Instagram, plays a significant role in customer decision-making; Because they pay attention to the opinions and reception of other audiences towards that product or post and are influenced. This research analyzes what factors create posts with different levels of popularity. For this purpose, the factors affecting the number of views, likes and comments in an Instagram social network post are extracted and their weight and importance are calculated based on the regression model. Finally, the decision tree model is presented for forecasting and management in order to increase the number of visits, likes and comments. Methods and Materoal In this research, the type of research is based on the purpose of applied research. At first, library studies have been used in order to extract factors affecting the amount of visits, likes and comments in Instagram social network marketing posts. The statistical population includes all articles related to the factors affecting visits, likes and comments. The probability sampling method of simple random samples has been used and 30 articles in this field have been reviewed. Then, the data related to the factors identified from the previous stage have been extracted from the pages of big marketers on the Instagram social network. Then, using the extracted data and using the regression model, the weight and importance of each factor affecting the number of visits, likes, and comments of Instagram social network marketers' posts has been calculated. Finally, a decision tree model has been created to predict the status (rate of visits, likes and comments) of a marketing post on the Instagram social network based on the characteristics of that post. Resultss and Discussion Directly, factors such as the number of posts, the number of followers, the type of post, the content of the post and the time of the post are potential factors that affect the number of views, likes and comments. According to the obtained results, the "post content with survey" factor with a positive sign and a coefficient of 420,290.616 had the most positive effect on the label, which is the number of visits to a post. The factor "discount post content" with a positive sign and a coefficient of 5417.751 has had the most positive effect on the label, which is the liking of a post. The factor "discount post content" with a positive sign and a coefficient of 2164.016 has had the most positive effect on the label, which is the amount of comments on a post. Also, the type of image post with a regression coefficient of 565.153 and a negative sign in the investigation of factors affecting the number of comments shows that the use of video posts will increase the comments and interaction of customers. Conclusion Most of the researches conducted, such as Gkikas et al (2022), Torbarina, Jelenc & Brkljačić (2020), Wahid & Gunarto (2022), etc., only investigated the influence of a few specific factors on the likes and comments of social media posts, and a comprehensive set of factors has not been investigated. Also, these factors were only for checking likes or opinions and not checking both cases. Most importantly, in the studies conducted, only the positive or negative impact of a factor on the number of likes and opinions has been discussed, and their importance has not been determined. In this research, various factors affecting the number of visits, likes and comments of social network posts were investigated. Also, the importance of each factor was determined. In addition, a decision tree model was presented to manage related pages and posts in order to achieve increased likes and comments. 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</div> شبکه‌های اجتماعی, بازاریابی الکترونیکی, تحلیل رفتار کاربران, داده‌کاوی Social Networks, E-Commerce, User Behavior Analysis, Data Mining. 21 39 http://hii.khu.ac.ir/browse.php?a_code=A-10-1030-1&slc_lang=fa&sid=1 Mohammad Moradi محمد مرادی m_moradi@buqaen.ac.ir 10031947532846006048 10031947532846006048 Yes Assistant Professor, Department of Computer Engineering, Faculty of Engineering, Bozorgmehr University of Qaenat, Qaenat, Iran *گروه مهندسی کامپیوتر، دانشکده مهندسی، دانشگاه بزرگمهر قائنات، قائنات، ایران.