The IBM Watson Personality Insights service uses linguistic analysis to extract cognitive and social characteristics from input text such as email, text messages, tweets, forum posts, and more. By deriving cognitive and social preferences, the service helps users to understand, connect to, and communicate with other people on a more personalized level.
Personality Characteristics
- 52 personality traits, needs and values that help to better understand and engage people. Consumer Preferences.
- Example traits of Big 5: openness, adventurousness, conscientiousness, facet_achievement_striving, extraversion, facet_activity_level, agreeableness, altruism, neuroticism, facet_anger, need_challenge, value_conservation
- 8 categories and more than 40 consumption preferences for products, services, and activities (e.g. movies or music).
- Install python SDK. I ran pip install --upgrade ibm-watson in bash & the latest Python I installed is 3.7
- Create a IBM Cloud Account
- Create an instance of Personality Insights within your IBM Cloud account, choose the Lite plan.
- Within the PersonalityInsightsProf.py file found in the data folder in this github repo, enter the credentials from Manage-->Credentials of the Personality Insights service you created to authenticate to the service.
- version
- iam_apikey
- url
- Choose the type of file you want to analyze (txt, JSON or CSV)
- You can pass the service a maximum of 20 MB of content to be analyzed via the body of the request, Fewer than 100 words generate an error
- IBM recommends that you provide at least 1200 words, but providing at least 600 words produces acceptable results: 3000 words are sufficient to achieve the service's maximum precision
- In the demo I analyze a txt file for personality traits and save results to a JSON file
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