What is Boolino Index?
Boolino Index is a relevance index based on an analytical model created by our math team.
This index is the result of a multiple linear regression analysis based on two main areas of information: qualitative and quantitative.
The calculation is performed on an array of values, to which a linear regression is applied, thus enabling us to identify the attributes that are relevant for the mathematical model that we have applied to our database. The resulting function includes a method that does not count the same influence twice and returns the results sorted by decreasing importance. Boolino Index is iterative and there is continuous feedback between all of the variables in it and they all affect the final result.
When the model has been calculated, we apply time blocks to mitigate the effect of time on the market, which may result in recently-published books that are yet to be rated by users not yet being sufficiently relevant.
As remarked above, the two main influencers are divided into qualitative and quantitative information:
- Qualitative information relates to the book, the publisher and the author. The latter two elements are updated continuously whenever a book is added to the database, which then affects all other books to some degree.
- Quantitative information relates to the book and the activities carried out by users in relation to them, with comments, "likes", libraries, itineraries, attempts to buy, etc. All of these factors affect their popularity among users.
Boolino Index is continuously and automatically updated. The only way to influence its results is to create contents about books that generate interest among readers. Such contents will make them more visible to users who will discover them and then select them during their next purchase.
Visit general ranking of Boolino Index.