August 19, 2017
Want to diagnose depression more effectively? Use Instagram. That’s the message from two scientists who report that an algorithm they developed can identify depressed people with 70 percent accuracy by analyzing the images that users post on the social media site. That’s a big improvement over doctors’ conventional diagnostic methods, which the researchers say are only 42 percent accurate.
Could this be yet another example of Big Data with big socionomic value? We’ve seen it before. In 2011, researchers at Indiana University discovered that they could use Twitter to forecast the stock market.
If you look closely, you can see patterns in social mood that help you predict social trends. Learn more with the Socionomics Premier Membership.
The Socionomist enables you to see trend-shaping waves of social mood, as reflected by the stock market — and capitalize on them. The June issue looks at phases of social mood and features a “Research Roundup,” which highlights five academic studies that shine a light on important aspects of socionomic theory. Mood Riffs topics include “quiet luxury,” loneliness, the Writers Guild strike and efforts by countries to trade in currencies other than the U.S. dollar. Read the June issue when you become a Socionomics Premier Member.
