A study by a team of Nanyang Technological University, Singapore (NTU Singapore) psychologists has found a link between extraverts and their word choices.
The study found a corelation between extraverts and their tendency to use certain categories of words. The results showed a small strength of relationship between extraversion and the use of "positive emotion words" and "social process words".
Positive emotion words are defined by psychologists (using text analysis tools) as words that describe a pleasant emotional state, such as 'love', 'happy', or 'blessed', or that indicate positivity or optimism, such as 'beautiful' or 'nice'. Social process words include words containing personal pronouns except 'I', and words showing social intentions, such as 'meet', 'share' and 'talk'.
"This is the first time a relationship has been established between extraverts and their tendency to use the two categories of words. As it is a small correlation, we believe that stronger linguistic indicators are needed to improve machine learning approaches, amid rising interest in such tools in consumer marketing," says principal investigator of the study, Associate Professor Lin Qiu from the psychology programme at the NTU School of Social Sciences.
The finding highlights the need for stronger linguistic indicators to be developed for use in online personality prediction tools, which are being rapidly adopted by companies to improve digital marketing strategies.
Today, marketing companies use predictive algorithms to help them forecast what consumers want based on their online behaviours. Companies are also keen to leverage data and machine learning to understand the psychological aspects of consumer behaviour, which cannot be observed directly, but can provide valuable insights about how to improve targeted advertising.
The NTU team said the findings, which was published in the Journal of Research in Personality in December 2020, can provide marketers with well-founded linguistic predictors for the design of machine learning algorithms, improving the performance of software tools for personality prediction.
To establish the effectiveness of such linguistic predictors, the NTU team reviewed 37 studies looking at the same topic to conduct a meta-analysis. Extraversion was determined using internationally recognised personality type questionnaires.