Caracterização e Classificação de Bots Utilizando a Rede de Comentários do Reddit
Abstract
Online social networks play an increasingly important role in society, given its influence on the opinion formation of millions of users. However, the presence of bots (users with programmed behavior) emerges as a concern given their potential to dissiminate information and consequently influence opinion formation, evidencing the need for its characterization and identification. This work considers a directed network of users constructed from comments in Reddit to characterize and identify bots. The network characterization highlights the significant structural differences of bots, allowing them to be classified with high accuracy using only network features.
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Baumgartner, J. (2018). Reddit comments dataset. https://files.pushshift.io/reddit/comments/. [Online; accessed 10-march-2019].
Damasceno, R. G. (2019). Classificação de perfis falsos em redes sociais online utilizando a estrutura da rede. Final course assignment, Universidade Federal do Rio de Janeiro, Rio de Janeiro, BR.
Ferrara, E., Varol, O., Davis, C., Menczer, F., and Flammini, A. (2016). The rise of social bots. Communications ofthe ACM, 59(7):96–104.
Gilani, Z., Farahbakhsh, R., Tyson, G., Wang, L., and Crowcroft, J. (2017). Of bots and humans (on twitter). In Proceedings ofthe 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, pages 349–354. ACM.
Kudugunta, S. and Ferrara, E. (2018). Deep neural networks for bot detection. Informa- tion Sciences, 467:312–322.
Newman, M. (2010). Networks: an introduction. Oxford university press.
Rosenberg, M., Confessore, N., and Cadwalladr, C. (2018). How Trump consultants exploited the facebook data of millions. The New York Times.
Varol, O., Ferrara, E., Davis, C., Menczer, F., and Flammini, A. (2017). Online human-bot interactions: Detection, estimation, and characterization.
Wagner, C., Mitter, S., K¨orner, C., and Strohmaier, M. (2012). When social bots attack: Modeling susceptibility of users in online social networks. In # MSM, pages 41–48.
Wang, A. H. (2010). Detecting spam bots in online social networking sites: a machine learning approach. In IFIP Annual Conference on Data and Applications Security and Privacy, pages 335–342. Springer.
Zaki, M. J., Meira Jr, W., and Meira, W. (2014). Data mining and analysis: fundamental concepts and algorithms. Cambridge University Press.
Published
2019-07-08
How to Cite
DAMASCENO, Rafael G.; FIGUEIREDO, Daniel R..
Caracterização e Classificação de Bots Utilizando a Rede de Comentários do Reddit. In: WORKSHOP ON PERFORMANCE OF COMPUTER AND COMMUNICATION SYSTEMS (WPERFORMANCE), 2019. , 2019, Belém.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
ISSN 2595-6167.
DOI: https://doi.org/10.5753/wperformance.2019.6471.
