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Personality computing is a research field related to Artificial intelligence and Personality psychology addressing three main problems involving personality with methods of computer science, namely automatic personality recognition, perception and synthesis.

Automatic personality recognition is the inference of personality type of target individuals from their digital footprint), automatic personality perception is the inference of the personality attributed by an observer to a target individual based on her observable behavior, and automatic personality synthesis is the generation of the style or behaviour of artificial personalities in Avatars and Virtual agents.

A set of individuals self-assessed personality test or observer ratings is always exploited as the ground truth for testing and validating the performance of artificial intelligence algoritms for automatic predictions. Despite a wide variety of personality tests have been developed, such as the Myers Briggs Type Indicator (MBTI) or the MMPI, and a number of tests based on the Five Factor Model of personality, such as the Revised NEO Personality Inventory.

History
Personality computing begun around 2005 with few pioneering research works showing that personality traits could be inferred with reasonable accuracy from text, such as blogs and self-presentations , and email addresses.

Few years later begun the research in personality computing from multimodal and social signals, such as recorded meetings and voice calls.

In the 2010s the main research focus of personality computing is the extraction of personality types from social media, in particular from Facebook , Twitter and Instagram

Many works demonstrated the validity of Personality Computing from different human digital footprints, in particular the performance of algorithms recognizing personality types is very high exploiting user preferences such as Facebook page likes. The most recent advancements in Personality Computing showed that machines can recognize personality better than humans.