A new research has provided a deeper understanding into how social media can help study personality, potential health risk and cultural differences. Researchers' survey questions to measure thoughts, feelings and personalities of people. The universal use of Twitter and Facebook has afforded new approaches to social science research, and requires new techniques to analyze and interpret data using computer science methods. These techniques allow researchers the ability to generate insights from large-scale data sets.
A study utilizing open-vocabulary analysis found striking variations in language with personality, gender, and age. Certain words and phrases can provide novel and detailed insights. Open-vocabulary analysis can find connections that are unanticipated and often are not captured by other analysis techniques.
Researchers have found that words used on Facebook are surprisingly reliable indicators of personality. The researchers utilized predictive algorithms of the language to create efficient large-scale personality assessments. The automated language-based models of traits were consistent with the participants' self-reported personality measurements.
The study found that certain phrases are predictive of specific personality traits. For example, individuals who score high in neuroticism on self-reported personality assessments are more likely to use words like sadness, loneliness, fear and pain.
Analyzing this data may provide novel connections that may not be apparent in traditional written questionnaires and surveys.
Researchers compared tweets and heart disease at the county level. The study found that language analyses might predict heart disease risk as well or better than traditional epidemiological risk factors.
Twitter users are not necessarily individuals at-risk for heart disease, but rather, they can serve as canaries for communities with higher heart disease risk. Tweets can represent the overall negativity a community is feeling, and indicate the social and environmental stresses that contribute to increased heart-disease risk.
The results of the study illustrated that Twitter serves as an accurate predictor of health and risk factors of a community.
Social media allows researchers to examine similarities and differences across cultures at a new level. Cross-cultural studies typically require time-intensive qualitative analyses with a small number of people. Margaret Kern of the University of Melbourne and Maarten Sap of the University of Pennsylvania are using Twitter to study variations in language use across cultures.
Using differential language analysis the researchers examined Twitter posts from eight countries (United States, Canada, United Kingdom, Australia, India, Singapore, Mexico, and Spain) and two languages (English and Spanish).
The researchers found that there were many similarities across countries, with emoticons and iconic pop artists correlating with positive emotions and curse words, and aggression correlating with negative emotions. There were also differences that point to culture-specific correlations for emotional expression. Results of the study are still preliminary, and have not yet been published.
The study is published in the Journal of Personality and Social Psychology.