Post millions των χρηστών του, το Twitter έχει εξελιχθεί σε ένα τεράστιο κανάλι προσωπικής έκφρασης, το οποίο μπορεί να φανεί χρήσιμο σε θέματα δημόσιας healths – especially in matters of depression.
Microsoft Research Redmond, Eric Horvich, is a pioneer of Twitter and depression research, and estimates that at some point smart systems will be able to analyze a user's Twitter feed and warn him if he is at risk of depression, according to a report of Time.
"We wondered if we could create tools that would be able to tell when someone is depressed, just by the publications of. What do people in the world say in public? You can imagine tools that will inform about changes in a user's mood before they even feel it themselves," he says.
Horvich and a team of researchers have helped develop a method that allows depictions to be depicted on Twitter users with 70% accuracy by scraping their tweets. However, the method still has much room for improvement, as some clues can be avoided and people who may be experiencing this problem may not be identified. Also, according to Hornic, there is a mistaking issue, as 10% of cases found that depressed healthy users were at risk.
As part of the research, the Microsoft team found 476 Twitter users, 171 of whom were depressed. Then, the researchers examined their Twitter histories up to a year before diagnosis, looking for various indicators of depression, analyzing 2,2 million tweets with computer models. By comparing the tweets of depressed users with those of healthy users, a method was developed that can predict cases of depression before they occur. This "model" was then tested on another sample of users, with a success rate of 70%.
Some tweets were "obvious": "I want someone to hug me and be there for me when I'm sad," "having a job again makes me happy. Less time to be sad and to see sad movies, "etc. But Microsoft researchers also looked at other factors such as the number of tweets per day, while users made tweets, the degree of interaction with others , the type of language, etc.
They also looked for key words indicating depression ("anxiety", "nausea", "sleeping", "nervousness", etc. were often used, but there were other seemingly more "innocent" words like "love" he "," this "," home "," tolerance "," songs "," movies "etc.). The frequency of tweets and dialogues with other users is also significant, as people who are depressed tend to "tweet" less and interact less with other people, according to Hornic.
One area in which such research might be useful is to evaluate public reactions to major events. Observing and analyzing Twitter feeds after "traumatic" incidents could allow a further understanding of exactly how users are affected by news.
"Our view is that Twitter is the largest observational study of human behavior we have ever seen, and we are working hard to exploit it" Tyler McCormick of the University of Washington's Center for Statistics and Social Sciences tells Time. It is noted that McCormick's team is also working on the subject, as is a team from her University California- San Diego.
