Retweet Prediction Using Multi-Layer Perceptron Optimized by The Swarm Intelligence Algorithm

Jondri Jondri; Indwiarti Indwiarti; Dyas Puspandari

doi:10.15575/join.v8i2.1193

Authors

Jondri Jondri Telkom University, Indonesia
Indwiarti Indwiarti Telkom University, Indonesia
Dyas Puspandari Telkom University, Indonesia

DOI:

https://doi.org/10.15575/join.v8i2.1193

Keywords:

twitter, user based, Content-based, time-based, Multi layer perceptron, swarm intelligence

Abstract

Retweets are a way to spread information on Twitter. A tweet is affected by several features which determine whether a tweet will be retweeted or not. In this research, we discuss the features that influence the spread of a tweet. These features are user-based, time-based and content-based. User-based features are related to the user who tweeted, time-based features are related to when the tweet was uploaded, while content-based features are features related to the content of the tweet. The classifier used to predict whether a tweet will be retweeted is Multi Layer Perceptron (MLP) and MLP which is optimized by the swarm intelligence algorithm. In this research, data from Indonesian Twitter users with the hashtag FIFA U-20 was used. The results of this research show that the most influential feature in determining whether a tweet will be retweeted or not is the content-based feature. Furthermore, it was found that the MLP optimized with the swarm intelligence algorithm had better performance compared to the MLP.

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