A message to IBM Watson Personality Insights users from the inventors of the science
IBM recently announced it will begin sunsetting Watson™ Personality Insights. The service is no longer available for new users, and existing users will need to migrate to an alternative by December 2021. Receptiviti is more than just an alternative, we invented the science.
The history of language-based personality insights starts long before IBM launched Personality Insights. The story begins in the 1990s with the seminal work of Receptiviti Co-Founder, Prof. James W. Pennebaker at the University of Texas, who was investigating whether analysis of writing could predict mental and physical health, personalities, social behaviours, and cognitive processes. Since those early days, our science has been the basis for thousands of academic publications in a variety of fields covering topics such as gender differences, authorship identification, power and language, suicidal intervention, deception, and more.
For years, we have worked closely with academics around the world, supporting and contributing to their research, gathering data, and continuously improving the informative and predictive quality of our platform. Today, Receptiviti is the global leader in language psychology, with customers across industries that span technology, financial services, human capital, professional services, and more.
Language-Based Personality Insights is only one of our products, and we invite you to explore how our platform can help you solve your challenges and grow your business. Many of our customers integrate our API directly with their technology, while others rely on our services team to assist with custom analysis and measure development. We welcome you to register for an API account, and let us know how we can help you!
Predictive and Informative Personality Models
Unlike traditional personality assessments, Receptiviti's Language-Based Personality Insights doesn't require subjects to complete a questionnaire. Receptiviti analyzes text-based language from voice, email, messaging systems, transcribed video, engagement surveys, earnings call transcripts, bots, blogs, forum posts, tweets and more.
Personality traits and scores are ideal inputs into machine learning models for predicting behaviours, informing business decisions by comparing and contrasting results of different individuals or groups, gathering customer intelligence, evaluating candidates and employees, optimizing customer interactions, call centre agent matching, and more.
Drives and Motivations
Understand what is motivating a person's behaviour, whether they are driven by the need for achievement and self actualization, domination, reward, avoidance of risk or by engaging in risk-seeking behaviour.
Why should you use Receptiviti Language-Based Personality Insights?
30-years ago we invented the science of language and personality, and we've been perfecting it ever since. Our science is validated, and it has over 17,000 citations on Google Scholar. The new Receptiviti Language-Based Personality API makes it easy to integrate personality insights into your applications.
Our normalization process uses a diverse set of data gathered across multiple contexts of speech and written language with over 10 million data points.
Descriptions, Definitions, and API Documentation
For more information, including measures, descriptions, and definitions, click here.
Check out the API documentation here.
Have questions? We have answers! Contact us.
For Business Users
Understand the personalities of people who matter to predict their behaviours and preferences, and optimize every interaction.
For Data Scientists
Uncover the predictive relationship between personality and human behaviour.
Our easy-to-use API and documentation makes it easy to integrate Language-Based Personality into your technology.
Receptiviti and LIWC Personality Research
Explore some of the personality research conducted by psychologists and linguists using our science.
When Small Words Foretell Academic Success: The Case of College Admissions Essays
This study of over 50,000 college admissions essays from more than 25,000 entering students found higher grades were associated with greater article and prepositions use, and lower grades were associated with greater use of auxiliary verbs, pronouns, adverbs, conjunctions, and negations.
COVID-19 Cognitive, Social and Emotional Impact on the Workforce
This study aggregates the findings of research into how COVID-19 has impacted the cognitive abilities, social and emotional health and productivity of the workforce. Findings highlight critical issues that can help organizations as they prepare for the post- COVID-19 world of work.
Insurance claim lie detection
Twenty percent of policyholders surveyed admitted they would consider submitting an exaggerated or fabricated insurance claim in the future (Association of British Insurers, 2009). This study explores applications of the Verifiability Approach for verbal lie detection.
Public Concerns, and Fears Related to Canada’s COVID Relief Programs
In Fall 2020, the Canadian Ministry of Finance engaged Receptiviti to gain an in-depth understanding of public perception of the CERB program, with the findings to be used to inform future program policy, communication strategy, and risk management.