Increase the power of your research data
Unstructured digital records are difficult to use in research. By converting this data into psychological profiles, you can significantly expand the breadth, detail and interpretability of your measurements. Our mission is to equip the research community with computational methods that bring data to life, so we can answer the bigger questions faster.
Avoid asking unnecessary questions
Personality questionnaires can be time-consuming, expensive and tedious to administer. Our API helps you reliably and transparently collect information on psychological characteristics without inconveniencing your participants. (This is especially important for large online studies.) Given that our predictions are based on actual behaviour, many of the biases of self-reports can also be significantly diminished by using Apply Magic Sauce in your study (Kosinski, Matz, Gosling, Popov, Stillwell, 2015).
Accurate prediction published in PNAS
Our model is based on the myPersonality dataset of over 6 million volunteers, the world’s only ground-truth psychological database of comparable scale and detail. We have published our methods in the Proceedings of the National Academy of Sciences (Kosinski, Stillwell & Graepel, 2013) and proven to know you even better than your colleagues, friends, family and romantic partners! (Youyou Wu., Kosinski M. & Stillwell D. 2015). Accuracies are even higher than previously reported, as we update our data and models iteratively.
Global research community
We have collaborated and shared anonymised research data with more than 80 Universities and 150 research teams around the world to promote high-quality research into psychology, education, business, medicine, law and beyond. Visit www.mypersonality.org for more information on this open-source initiative, which resulted in more than 40 peer-reviewed articles between its launch in 2007 and completion in 2018.
Academic use is limited to 1000 profiles per month by default
We make our prediction tools available free-of-charge to academics and educators, for purposes that have no relation whatsoever to any commercial or profit-making activity. We are more likely to consider expanding functionality for those researchers who support our community of students and academics by sharing data, expertise or other resources.