#I See the Future
Using Twitter and big data tools to read minds - many, many minds
People who think farther into the future are more likely to invest money and to avoid risks, according to new findings by Emory psychologists.
While that conclusion may not seem revelatory, previous findings on the subject have been inconsistent—possibly due to factors such as observer bias in a lab setting and small sample sizes. What’s notable about this research, published by the Proceedings of the National Academy of Sciences (PNAS), is that it tapped big data tools to conduct text analyses of nearly forty thousand Twitter users and to run online experiments of behavior of people who provided their Twitter handles.
“Twitter is like a microscope for psychologists,” says coauthor Phillip Wolff, associate professor of psychology. “Naturalistic data mined from tweets appears to give insights not just into tweeters’ thoughts at a particular time, but into a relatively stable cognitive process. Using social media and big-data analytical tools opens up a new paradigm in the way we study human behavior.”
Coauthor Robert Thorstad 16G 22PhD, a grad student in the Wolff lab, came up with the idea for the research, worked on the design and analyses, and conducted the experiments.
“I’m fascinated by how peoples’ everyday behavior can give away a lot of information about their psychology,” Thorstad says. “Much of our work was automated, so we were able to analyze millions of tweets from thousands of individuals’ day-to-day lives.”
The future-sightedness found in individuals’ tweets was short—usually just a few days—which differs from prior research suggesting future-sightedness may stretch years.
“One possible interpretation is that the difference is due to a feature of social media,” Wolff says. Another possible reason is that prior studies explicitly asked individuals how far they thought into the future, while the PNAS paper used the implicit measure of previous tweets.
The researchers used a suite of methods to automatically analyze Twitter text trails previously left by individual subjects. Experimental data was gathered using the Amazon crowdsourcing tool Mechanical Turk, a website where individuals can complete psychology experiments and other internet-based tasks.
In one experiment, Mechanical Turk participants answered a classic delay discounting question, such as: Would you prefer $60 today or $100 in six months?
The participants’ tweets were also analyzed. Future orientation was measured by the tendency of participants to tweet about the future compared to the past. Future-sightedness was measured based on how often tweets referred to the future, and how far into the future.
The results showed that future orientation was not associated with investment behavior, but that individuals with far-future-sightedness were more likely to choose to wait for future rewards than those with near-future-sightedness. That indicates that investment behavior depends on how far individuals think into the future, rather than their tendency to think about the future in general.
“Twitter can provide a much broader participant pool than many psychology experiments that primarily use undergraduates as subjects,” Thorstad says. “Big data methods may ultimately improve generalizability for psychology results.”