Affective data is a relatively new type of data that is having impact on the commercial market, and is generally defined as;
“Affective data is the feedstock of the algorithms and methods used for the automatic recognition of emotion or sentiment from people.”
As you can see from this Google n-Gram, by the standards of areas of science both Cognitive Biases, and even more so, Affective Data is a very recent concept;
Affective Computing is a very young field of science spending most of the 30 Years in a Saffo Cycle, slowingly working its way to the commercial market. When the amount and methods of accessing data turned scarcity into plentitude the challenge changes to greater selectivity.
Selecting data is done through several methods, classifying, categorizing, clustering and modeling now are more of the value proposition than counts and averages.
It is no surprise that people were looking for a more valuable type of data that explained why humans weren’t logical and consistent in specific situations as that was pointed out by Dieter, Kahneman, Ariey, and others who helped to break down the requisite myths of economics and made Homo Economus extinct, replaced by their modern, but much less predictable ancestor, Homo Affectus;^)
The basic commercial value of Affective Computing are in the opinions, sentiments, and emotions derived from observations over time of people's behaviors that can be captured using their writings, facial expressions, speech, physiological signals and movements, typically expressed in terms of probabilities.
The reason that Homo Affectus evolved is due to society now understanding something they didn’t before, and slowly changing the beliefs and possibilities of individuals, groups and organizations of people.
This is the Affective.health “Overton Window” into the acceptable possibilities and ideas that your customer base holds and believes to be understandable, true, and beneficial to their well being.
To meet the growing need for higher quality data that provides greater levels of predictability and that can be exported to be used in any analytical system Affective.health is announcing the Frugal Model Studio.
The Frugal Model Studio is a combination of technology and prebuilt methods that allows for the creation of these simple mechanical models using their domain knowledge to “tune” the models to their organization’s exact needs, and easily update those needs as they evolve.
With our easy to learn process organization can create custom "Frugal Models" that provide key consumer insights that can be rapidly understood without the need to digest large amounts of data or complex algorithms.
Affective.health has extensive online help, including videos by one of our Founders and Chief Cognitive Scientist, Dr. Joseph Z. Stafura, an engaging lecturer who brings the purpose and the meaning to the model building to collect accurate Affective Data along with conveying the few technical skills needed to operate the studio to the Customer/Creators.
The Models our clients build can become a unique IP asset that provides a differentiation opportunity to our clients through the combination of Affective Data exported into the existing analytics platforms, enhancing and augmenting traditional data sets.
To learn more about the ways that Affective.health can improve your Objective Data through the combination of Affect Data sets - firstname.lastname@example.org