Detection of Bots Spreading Religious Hatred in Arabic Social Media
Table 4. Evaluation results of various regression models.
['[BOLD] Model/Features', '[BOLD] Spearman’s rho', '[BOLD] Kendall’s tau', '[BOLD] MAE']
Highest scores are shown in bold. We have included the performance of Botometer as well in this table as a baseline. As shown in the table, our regression model trained on only simple content features outperformed Botometer which uses user, friend, network, and temporal features. The most informative content features reported by this regression model were the average numbers of account mentions, URL links, numerics, and punctuation marks, respectively. This shows that linguistic cues conveyed in tweets are highly effective in detecting Arabic bots.