  The move of propaganda and disinformation to the online environment is
possible thanks to the fact that within the last decade, digital information
channels radically increased in popularity as a news source. The main advantage
of such media lies in the speed of information creation and dissemination.
This, on the other hand, inevitably adds pressure, accelerating editorial work,
fact-checking, and the scrutiny of source credibility. In this chapter, an
overview of computer-supported approaches to detecting disinformation and
manipulative techniques based on several criteria is presented. We concentrate
on the technical aspects of automatic methods which support fact-checking,
topic identification, text style analysis, or message filtering on social media
channels. Most of the techniques employ artificial intelligence and machine
learning with feature extraction combining available information resources. The
following text firstly specifies the tasks related to computer detection of
manipulation and disinformation spreading. The second section presents concrete
methods of solving the tasks of the analysis, and the third sections enlists
current verification and benchmarking datasets published and used in this area
for evaluation and comparison.
