Your tweets can tell a lot about you!

By GizBot Bureau

| Published: Monday, November 16, 2015, 12:30 [IST]

What can you tell about people and their situations from just 140 characters they post on Twitter? Quite a lot, according to researchers who analysed more than 20 million tweets to study the psychological characteristics of real-world situations.

Researchers wanted to learn about the kinds of situations people experience across time, and how gender and population density might affect situation experiences. Findings from the study showed large gender differences and significant differences between weekdays and weekends.

However, they also showed that people in urban and rural areas experience situations that are, for the most part, psychologically similar. The researchers found that people experienced on average more positivity on the weekend and more negativity during the work week.

People also experienced higher levels of duty during the "9 to 5" workday and more sociality in the evenings. In terms of gender differences, females experienced higher levels of mating and more emotional situations - both positive and negative - than males.

"Twitter is a digital stream of consciousness of its users and we wondered if we could determine the psychological characteristics of situations people were experiencing based on their tweets," said David Serfass, corresponding author and a PhD psychology student at Florida Atlantic University (FAU).

Researchers were able to develop a method for automatically extracting meaningful information about the situations people experience in their daily lives from tweets. In the study, they gathered 5,000 tweets and rated each of these tweets on eight core dimensions of situations, dimensions which they helped uncover in previous research.

Next, they used a computer programme called the Linguistic Inquiry Word Count (LIWC) to quantify the words used in tweets into distinct psychological and lexical groupings, such as self-references, positive words, negative words, and personal pronouns.

The researchers then used machine learning techniques to determine which word categories tended to co-occur with which psychological characteristics. For example, they found that people who were in situations characterised by "duty" were more likely to use words like "work" and "job."

People who were in situations characterised by adversity were more likely to use swear words. "We applied our scoring algorithms to more than 20 million tweets gathered from Twitter," said Ryne Sherman, study co-author and professor of psychology in FAU's College of Science.

"Thus, we were able to map out the kinds of situations that people experience across time and day, and in urban versus rural areas of the US," said Sherman. The study was published in the journal PLOS ONE.

Source PTI