Vol. 3 No. 2 (2023): Journal of Millimeterwave Communication, Optimization and Modelling
Articles

Bot Account Analysis on Social Media with Artificial Intelligence Support on Twitter Example

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  • Refik Söylemez,
  • Ali Boyacı
Refik Söylemez
İstanbul Ticaret Üniversitesi

Published 31.12.2023

Keywords

  • Twitter,
  • machine learning ,
  • bot tweet

Copyright (c) 2023 Refik Söylemez; Ali Boyacı (Co-Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Abstract

Twitter has undergone significant changes since
its launch in 2006, evolving from a platform that only allowed
140-character messages to one that is used for everything from
communication to marketing. Researchers have conducted
numerous studies on Twitter data, exploring everything from
emotion and influence to political polarization and bot analysis.
However, these studies have primarily focused on analyzing bot
tweets to combat the spread of false information. The accuracy
of these analyses varies depending on the selection of training
data used to create the machine learning models. In this study,
we investigate the impact of different training data on the
accuracy of these models, specifically exploring the effects of
randomly selected training data on model performance. By
examining this important question, we hope to shed new light on
the challenges and opportunities of using machine learning
methods to analyze Twitter data.

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