Journals / Journal of Artificial Intelligence and Data Science / 2021 / Cilt: 1 - Sayı: 2

Matching Potential Customers and Influencers for Social Media Marketing

Pages
150–159
Publication Date
2021-12-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The accuracy of the predictions is evaluated for each of the three situations and the success of our approach is observed for influencer/follower matching.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Social media platforms are so important for the advertising industry.
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Key Findings & Data:Companies have a huge amount of budget for advertisement and try to select an influencer as the face of their brand for these advertisements.
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Conclusion & Impact:The accuracy of the predictions is evaluated for each of the three situations and the success of our approach is observed for influencer/follower matching.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Deep learning · fake account detection · image processing

Abstract

Social media platforms are so important for the advertising industry. Companies have a huge amount of budget for advertisement and try to select an influencer as the face of their brand for these advertisements. Each brand is related to a specific segment of customers. When the true influencer is followed by this segment, advertising companies contact him/her. The objective of this work is to facilitate the job of the advertising company by matching the brand and the influencer to use the budget of the advertising company appropriately. Accordingly, our work makes an analysis of real/fake account detection, gender, and age range prediction of the influencer’s followers. In this work, it is focused on the real accounts by eliminating the fake ones and the gender, age- range prediction of these real accounts is considered. The detection of fake accounts is transformed into a binary classification problem by observing the features of real and fake accounts. Another binary classification solution is presented for gender detection by checking the pictures of the account owners and their names together. A pre-trained deep learning model for follower age range prediction is provided based on the pictures of these followers. The accuracy of the predictions is evaluated for each of the three situations and the success of our approach is observed for influencer/follower matching.

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Cite This Article

SOYGAZİ, F., AYDOĞAN, M. E., TAŞKIRAN, H. C., KAYA, Ö. (2021). Matching Potential Customers and Influencers for Social Media Marketing. Journal of Artificial Intelligence and Data Science, Cilt: 1 - Sayı: 2, 150–159. https://ajindex.com/articles/853777

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