Social media data from platforms such as Twitter have become increasingly valuable in understanding wider trends across society. A recent effort from Queensland University of Technology (QUT) mines data from the platform to map entrepreneurial activity in the United States.
The work, which was documented in a recently published paper, utilizes artificial intelligence to understand regional personality characteristics from the type of language used in tweets across the US. From this, they believe they can infer entrepreneurial hot and cold spots across the nation.
The researchers analyzed 1.5 billion tweets across 1,772 counties in the United States. Collectively, these states represent 95% of the population. These tweets were analyzed for signs of an entrepreneurial personality, which was defined as high levels of extraversion, conscientiousness, openness and low agreeableness and neuroticism.
This linguistic analysis revealed large areas of entrepreneurial activity, with a major belt on the East Coast, spanning from Massachusetts all the way to Florida, Colorado around Denver / Boulder, San Francisco / Bay Area, and South California, Gulf Coast regions of Louisiana and Mississippi. Large cold spots were found in the Rust Belt, Southern Texas and Central California.
The study is interesting as they didn’t use anything but Twitter activity to create maps that were a pretty accurate reflection of reality in terms of startup rates and other indicators of entrepreneurial activity.
“What we have discovered here is that social media – how language is used in Twitter—is a reliable marker of economic vitality in a region,” the authors say. “We have examined Twitter data from a large project at the University of Pennsylvania. This project analysed 1.5 billion US tweets and other social media data to train a machine learning model that can estimate regional personality characteristics by analysing language patterns typically used on social media in a region.”
Ordinarily, gaining this level of understanding would require laborious and expensive questionnaires that would need a huge sample size to produce meaningful results.
“The US map of the Twitter-based local measure of entrepreneurial personality and the US map of the actual start-up rates show impressive overlap. We found substantial positive correlations between regional Twitter-based entrepreneurial personality and actual start-ups rates, and these correlations were robust when considering local economic conditions such as level of education, unemployment rate, and industry composition,” the authors continue.
The next step for the team is to expand their research into new areas, including Australia and Europe. They’re optimistic that the trends identified in America will be replicable elsewhere, and believe that social media analysis could herald a new age of economic and social research as we shift away from survey based results.
“It seems that we stand at the dawn of a new era where we do not have to wait any longer until millions of people fill out long personality questionnaires to understand the local concentration of entrepreneurially-minded people, and local mechanisms such as entrepreneurship and innovation,” they say. “Instead, by means of artificial intelligence methods we can simply analyse existing, publically-available social media data such as billions of tweets to study local personality differences and their relevance for the well-being and prosperity of whole regions.”