The identification of automated activitiy in social media, specifically the detection of social bots, has become one of the major tasks within the field of social media computation. Recently published classification algorithms and frameworks focus on the identification of single bot accounts. Within different Twitter experiments, we show that these classifiers can be bypassed by hybrid approaches, which on a first glance may motivate further research for more sophisticated techniques. However, we pose the question, whether the detection of single bot accounts is a necessary condition for identifying malicious, strategic attacks on public opinion. Or is it more productive to concentrate on detecting strategies?.
CITATION STYLE
Grimme, C., Assenmacher, D., & Adam, L. (2018). Changing Perspectives: Is It Sufficient to Detect Social Bots? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10913 LNCS, pp. 445–461). Springer Verlag. https://doi.org/10.1007/978-3-319-91521-0_32
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