# Bot Datasets on Twitter: Analysis and Challenges
## 6 Conclusions  
In the literature, bot detection on Twitter is a topic that has gained popularity due to the increased risk bots represent to free will and opinion as the popular social network expands. Researchers have agreed on the necessity to characterize bots on the platform at a behavioral level due to their increasing complexity that has overcome the traditional analysis of individual features. In this work, we have analyzed both public and private databases from the literature of bot detection on Twitter. We summarized their advantages, disadvantages, and differences, recommending which is more suitable to work with depending on the necessities of the researcher. This analysis revealed five distinct behaviors in automated accounts exhibited across all the bot datasets analyzed from these databases. We measured their level of presence in each dataset using a radar chart for visual comparison, discussing our results. Lastly, we identified four challenges researchers of bot detection on Twitter have to face when using these databases from the literature. We conclude that our recommendation of a database to work with from the ones we have analyzed depends on the need of follower/following relationships, and not only on the number of attributes extracted from the Twitter API. While our work does not directly improve classification results, the set of behaviors we have identified can characterize bot accounts from different datasets independently of their type, language used, year of creation, and complexity. While we acknowledge that current research has changed its focus to a group-detection effort, we consider our contributions are still applicable. Researchers can treat these behaviors as a series of individual decisions in the platform that they can develop as collective actions. The present work pretends to serve as a starting point for new researchers working with Twitter databases from the literature, and to not repeat the same mistakes from other researchers when extracting their own information. As [PERSON] [12] recently stated, with the constant increase of publications focused on bot detection, the scientific community needs to evaluate the tools currently at their disposal. We soundly agree, and thus it is one of the motivations for which we carry out this work. We hope that the results of this study can inspire researchers to incorporate behavioral analysis in their individual or group detection approaches. Finally, database creators can take into account our suggestions presented and improve the quality of their future collections. We believe that much of what we have learned and discussed here can be applied by researchers to data collections of different natures, with our contributions aiming to help future researchers that are looking to implement new strategies to detect automated accounts effectively. For future work, we intend to create a feature representation that incorporates the five behaviors presented before to improve the state-of-the-art methods. We would also like to study databases of bots on other social networks to identify possible behaviors appearing across all of them, and not only Twitter. Finally, in our graph partitions, we discovered clusters of colored nodes without follower/following relationships connecting them. We want to explore them further as they could contain valuable insights. Methodology, L.D.S.-E.; software, L.D.S.-E.; formal analysis, L.D.S.-E.; investigation, L.D.S.-E.; writing--original draft, L.D.S.-E.; resources, O.L.-G.; supervision, O.L.-G., R.M., and M.A.M.-P.; writing--review and editing, O.L.-G., R.M., and M.A.M.-P.; validation, O.L.-G., R.M., and M.A.M.-P.; conceptualization, R.M. ; visualization, M.A.M.-P. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Council of Science and Technology of Mexico (CONACyT) through the scholarship grant 540975. Not applicable. Two publicly available datasets were analyzed in this study.