Our AI process is people-centered
Our Neural Networks process the data, such as text and audio, generating the outputs of the metrics and providing analytics insights.
Behind Erudit there is an exceptional team of psychologists and data scientists trained in the principles of Semantic Personality Analysis. This theory has been created by Erudit and its central hypothesis is that "we are the beliefs that we are constantly repeating, and that we act upon ourselves, others, and the world according to that speech" . That is why we have not try to enclose workers in a global category. We rather offer metrics on different aspects of their hourly mental states considering their historical behavior and cultural context.
Our data scientists and psychologists have previously done an exhausting job by labelling and classifying the data from thousands of forums and social networks. They have done it based on psychological theories such as psychoanalysis and cognitive behavioral. In addition, deep artificial Neural Networks have been designed and they have passed several quality controls.
We determine and measure the metrics based on what people are saying indirectly through their written language. So, how do we do it? Our Neural Networks discern between those words with a high meaning and those with no meaning at all. For example, "sad" brings far more value than a simple "the". Erudit's linguistic model is based on authors such as Chomsky, Maslach, Jung, Gödel, and Vigostky among others.
Erudit’s team of psychologists has previously described each metric and their risk levels, describing each one concisely based on Cantor's set theory. We have used anonymous and unbiased public data from forums, social networks and others to label thousands of words by assigning a risk level of each metric.
