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. It is characterized by automation, scalability, and anonymity.

Autonomous agents (internet bots) can analyze big data collected from social media and the Internet of things in order to manipulate public opinion in a targeted way, and to mimic real people on social media. Bots use coordination to gain a larger reach Digital technology builds upon existing methods of manipulating public opinion. It appeals to people's emotions and biases to circumvent rational thinking and promote specific ideas.

A pioneering work 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, 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.

Regulatory efforts have proposed tackling computational propaganda tactics using multiple approaches. Detection techniques are another front considered towards mitigation; 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. 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.