Know how reliable an individual source of information is without bias and better than a human. Across the internet, there are millions of sources of information, some popular and many lesser-known. However, even if a source has low notoriety, it does not mean it is any less reliable. By modeling numerous factors including recency and propagation, Accrete has developed a dynamic scoring algorithm for scoring the reliability of an individual source, independent of its popularity. Realizing reliable sources are publishing highly accurate information with greater consistency and far in advance of market leaders opens a gateway to an untapped resource of ‘superstars’. Reliability scoring enables you to empirically understand how reliable a source of information is across time, decoupled from biases, and better than a human.
Factors like popularity skew the truth regarding the quality of information a source is sharing. With source reliability, these elements are eliminated which levels the playing field
A source's reliability will vary through time. By building an algorithm that accounts for this variation the accuracy of the score is far superior
By de-coupling bias and empirically measuring a source's reliability, end-users can make decisions based on the value of the content and get ahead of the competition