Computational propaganda

Computational propaganda is the use of computational tools (algorithms and automation) to distribute misleading information using social media networks. The advances in digital technologies and social media resulted in enhancement in methods of propaganda.^[1] It is characterized by automation, scalability, and anonymity.^[2]

Autonomous agents (internet bots) can analyze big data collected from social media and Internet of things in order to ensure manipulating public opinion in a targeted way, and what is more, to mimic real people in the social media.^[3] Coordination is an important component that bots help achieve, giving it an amplified reach.^[4] Digital technology enhance well-established traditional methods of manipulation with public opinion: appeals to people's emotions and biases circumvent rational thinking and promote specific ideas.^[5]

A pioneering work^[6] in identifying and analyzing of the concept has been done by the team of Philip N. Howard at the Oxford Internet Institute who since 2012 have been investigating computational propaganda,^[7] following earlier Howard's research of the effects of social media on general public, published, e.g., in his 2005 book New Media Campaigns and the Managed Citizen and earlier articles. In 2017, they published a series of articles detailing computational propaganda's presence in several countries.^[8]

Regulatory efforts have proposed tackling computational propaganda tactics using multiple approaches.^[9] Detection techniques are another front considered towards mitigation;^[10][4] these can involve machine learning models, with early techniques having issues such as a lack of datasets or failing against the gradual improvement of accounts.^[10] Newer techniques to address these aspects use other machine learning techniques or specialized algorithms, yet other challenges remain such as increasingly believable text and its automation.^[10]