Abstract
The deliberate manipulation of public opinion, the spread of disinformation, and polarization are key social media threats that jeopardize national security. The purpose of this study is to analyze the impact of the content published by social bots and the polarization of the public debate on social media (Twitter, Facebook) during the presidential election campaign in Poland in 2020. This investigation takes the form of a quantitative study for which data was collected from the public domains of Facebook and Twitter (the corpus consisted of over three million posts, tweets and comments). The analysis was carried out using a decision algorithm developed in C# that operated on the basis of criteria that identified social bots. The level of polarization was investigated through sentiment analysis. During the analysis, we could not identify automated accounts that would generate traffic. This is a result of an integrated action addressing disinformation and the proliferation of bots that mobilized governments, cybersecurity and strategic communication communities, and media companies. The level of disinformation distributed via social media dropped and an increasing number of automated accounts were removed. Finally, the study shows that public discourse is not characterized by polarization and antagonistic political preferences. Neutral posts, tweets and comments dominate over extreme positive or negative opinions. Moreover, positive posts and tweets are more popular across social networking sites than neutral or negative ones. Finally, the implications of the study for information security are discussed.
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