Our data science team is always learning and experimenting which means they are closely connected to other research in this area around the world.
Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach
- BY Madhura Jayaratne
- DATE: April 14, 2020
Author: H. Andrew Schwartz et al.
Why we love it
These two papers highlight how incredibly one’s personality can be inferred from their language use and how these inferred personality profiles can be used to find the best congruence between one’s personality and personality demand of jobs. These papers in fact provided us inspiration and a benchmark for our own ‘language use to personality’ model.
What I learnt from it
It was in fact scary at first to see how much we give away in our conversations about who we are. After coming into terms with that, it was encouraging for the DS side of me to see how open-vocabulary approaches can outperform the dictionary-based closed-vocabulary approaches used in previous studies in modelling language use. On the other hand, when these models are applied to Tweets from different professionals, it is amazing to see how different professions have different personality signatures. I can personally vouch for high openness and low agreeableness among top open-source developers.
Why it’s a must
These two pieces of research reaffirm the importance of congruence between one’s personality and job/career. As Denissen et al. (2018) put it, “economic success depends not only on having a ‘successful personality’ but also, in part, on finding the best niche for one’s personality”. In evaluating this congruence, one’s language use can reveal a lot about him/her and machine learning models can model complex non-linear relationships between personality and personality demand of jobs.
Who should pay attention
ML/DS practitioners, HR professionals, Personality junkies