“The analysis revealed that increased chatter about cutting back on groceries, increasing use of public transportation and downgrading one’s automobile could, indeed, predict an unemployment spike,” the report says. “After a spike, surges in social media conversations about such topics as canceled vacations, reduced health care spending and foreclosures or evictions shed light on lagging economic effects. Such information could be invaluable for policymakers trying to mitigate negative effects of increased unemployment.”
SAS says its “mood score” is based on tones and emotions displayed by social media users. For instance, the study says an upward spike in “anxious” unemployment chatter with terms such as “car repossessed” or “entering foreclosure” often translates into a higher unemployment rate four months later in the U.S., with the same result five months later in Ireland.
Ironically, information culled from online resources is just an extension of what economists have always used to formulate cultural forecasts – and it could go way beyond the unemployment picture.
“Social media and Internet content is like the letters and phone calls that have always informed organizations,” says I-sah Hsieh, global manager of International Development at SAS. “Only now it’s digital, public and massive in scale. This untapped treasure can provide real-time feedback on policies, improve public safety, enhance citizen relations and support important sociological research.”
So the next time you log on to Facebook or Twitter, and up pops a note from a cousin or a friend on how their household budgets are tightening or how their workload grows even more burdensome at work, take note – conversations such as those could be an early indicator of impending job losses.