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Every day, 730,000 comments and 420 billion statuses are posted on Facebook, 500 billion 140-character tweets are posted and 430,000 hours of new video is uploaded to YouTube.
The Internet is a goldmine of data just waiting to be analyzed.
Ever since social media crept deeper and deeper into our daily lives, governments and advertisers have been utilizing this data for myriad purposes. Now, a team of researchers at the University of Ottawa, University of Alberta and the Université de Montpellier in France is examining ways to use social media data to detect and monitor people who are potentially at risk of mental health issues.
Finding patterns
Using computer algorithms, the team will apply social web mining and “sentiment analysis methods” to troves of data generated through social media to detect at-risk individuals.
Sentiment analysis is the process of identifying and categorizing opinions expressed in text through ...
