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Kamaludin Hanif Farisi
Telkom University
Computer Science & IT

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Retweet Prediction Using ANN Method and Artificial Bee Colony Jondri Jondri; Kamaludin Hanif Farisi; Kemas Muslim Lhaksmana
Computer Science Research and Its Development Journal Vol. 15 No. 2: June 2023
Publisher : LPPM Universitas Potensi Utama

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Abstract

In the ongoing modern era, the rapid dissemination of information takes place, utilizing various channels for data exchange. One such platform is the social media platform Twitter, renowned for its swift and extensive information propagation. A pivotal factor contributing to information distribution on Twitter is the retweet feature, whereby users can redistribute content to their audience. A study has been conducted to forecast this retweet activity by employing the Artificial Neural Network classification method in conjunction with the Artificial Bee Colony optimization approach. This study leverages diverse features, encompassing content-based feature, user-based feature, and time-based feature. The evaluation results from this study reveal that the proposed method achieves an accuracy value of around 83% with the highest accuracy value reaching 84%. These findings indicate that the fusion of the Artificial Neural Network classification method executed with optimization using the Artificial Bee Colony algorithm yields dependable and consistent performance in predicting retweet activities.
Co-Authors Jondri Jondri Kemas Muslim Lhaksmana