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The openness feature of Twitter allows programs to generate and controlTwitter accounts automatically via the Twitter API. These accounts, which areknown as bots, can automatically perform actions such as tweeting, re-tweeting,following, unfollowing, or direct messaging other accounts, just like realpeople. They can also conduct malicious tasks such as spreading of fake news,spams, malicious software and other cyber-crimes. In this paper, we introduce anovel bot detection approach using deep learning, with the Multi-layerPerceptron Neural Networks and nine features of a bot account. A web crawler isdeveloped to automatically collect data from public Twitter accounts and buildthe testing and training datasets, with 860 samples of human and bot accounts.After the initial training is done, the Multilayer Perceptron Neural Networksachieved an overall accuracy rate of 92%, which proves the performance of theproposed approach.

BotSpot: Deep Learning Classification of Bot Accounts within Twitter