Twitter Behavior Can Predict Users’ Income Level, New Research Shows

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The difference people use on amicable media can exhibit dark definition to those who know where to look.

Linguists have prolonged been preoccupied by this notion, joining a person’s difference to age, gender, even socioeconomic status. Now mechanism scientists from a University of Pennsylvania and elsewhere have left a step further, joining a online duty of some-more than 5,000 Twitter users to their income bracket. They published their formula in a biography PLOS ONE.

Daniel Preotiuc-Pietro a post-doctoral researcher in Penn’s Positive Psychology Center in the School of Arts Sciences led a research, collaborating with Svitlana Volkova of Johns Hopkins University, Vasileios Lampos and Nikolaos Aletras of University College London and Yoram Bachrach of Microsoft Research.

The group took an conflicting proceed to what psychologists and linguists have historically done: Rather than seeking approach questions, a scientists looked during participants’ amicable media posts, mostly full of insinuate sum notwithstanding a miss of remoteness these outlets afford. Researchers from Penn’s World Well-Being Project, of that Preotiuc-Pietro is a part, are extraordinary about amicable media as a examine apparatus that can support, or even replace, expensive, singular and potentially inequitable surveying.

For this experiment, a researchers started by looking during Twitter users’ self-described occupations.

In a United Kingdom, a pursuit formula complement sorts duty into 9 classes. Using that hierarchy, a researchers dynamic normal income for any code, afterwards sought a deputy sampling from each. After manually stealing obscure profiles — for example, listings referencing a film Coal Miner’s Daughter grouped as “coal miner” for contention — a group finished adult with 5,191 Twitter users and some-more than 10 million tweets to analyze.

Income as a duty of a Twitter user's characteristics (objectivity, emotion, contention topics, followers/followees ratio).

Income as a duty of a Twitter user’s characteristics (objectivity, emotion, contention topics, followers/followees ratio).

“It’s a largest dataset of a kind for this form of research,” pronounced Preotiuc-Pietro. “The dataset enabled us to do something no one has unequivocally finished before.”

From there, they combined a statistical healthy denunciation estimate algorithm that pulled in difference that people in any formula category use distinctly. Most people tend to use a same or identical words, so a algorithm’s pursuit was to “understand” that were many predictive for any class. Humans analyzed these groupings and reserved them qualitative signifiers.

Some of a formula certified what’s already known, for instance, that a person’s difference can exhibit age and gender, and that these are tied to income. But Preotiuc-Pietro pronounced there were also some surprises; for example, those who acquire some-more tend to demonstrate some-more fear and annoy on Twitter. Perceived optimists have a reduce meant income. Text from those in reduce income brackets includes some-more swear words, since those in aloft brackets some-more frequently plead politics, companies and a nonprofit world.

Aletras remarkable an altogether design that emerged about Twitter use.

“Lower-income users or those of a reduce socioeconomic standing use Twitter some-more as a communication means among themselves,” he said. “High-income people use it some-more to disseminate news, and they use it some-more professionally than personally.”

Strong correlations like these, between what a researchers report as online countenance and offline demographics — for example, duty organisation or income turn — also valid intriguing, Lampos added. “This work attempts to prominence some of a intensity causal factors in these relationships.”

Such commentary will act as a baseline for destiny work, some of that will examine how perceptions about user income align with reality.

Source: University of Pennsylvania