Content rotation is a mode of content publication and viewing typical of the Internet, managed by Artificial Intelligence algorithms. It is a mechanism by which a user who is enjoying a piece of content, at the end of the consultation, receives suggestions and recommendations for him to consult further content.
A typical example of this mode can be experienced on YouTube, where watching a movie is automatically followed by another video that is somehow related to the previous one. Or the movie is even displayed on the same page with others, which YouTube itself recommends or suggests.
Content rotation is produced by algorithms that follow different organization criteria:
- a first criterion is semantic relevance, that is, the correlation of meaning between one content and another. These correlations are created by semantic analysis performed by artificial intelligence.
- a second criterion is personalization, based on the system’s ability to record content that the user has previously viewed and then to propose new content that may be similar and therefore interesting to the user.
- The popularity of a piece of content can also promote its spread, and this, for example, helps promote fake news more than substantiated news.
- Affinity with friends and connections, again managed by algorithms, is a contributing factor to the sharing of materials.
- an additional criterion is the commercial promotion of sponsored content, thus paid for by advertisers, or advertisements.
In general, it should be pointed out that the platform has the utmost interest that the user spends as much time as possible within the system, consulting pages, but also that he/she views and links as much content as possible, in order to then introduce advertising messages, proposed before (pre-roll), during (mid-roll) or after (post-roll) the viewing of a content.
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