Title |
Social Media Fingerprints of Unemployment
|
---|---|
Published in |
PLOS ONE, May 2015
|
DOI | 10.1371/journal.pone.0128692 |
Pubmed ID | |
Authors |
Alejandro Llorente, Manuel Garcia-Herranz, Manuel Cebrian, Esteban Moro |
Abstract |
Recent widespread adoption of electronic and pervasive technologies has enabled the study of human behavior at an unprecedented level, uncovering universal patterns underlying human activity, mobility, and interpersonal communication. In the present work, we investigate whether deviations from these universal patterns may reveal information about the socio-economical status of geographical regions. We quantify the extent to which deviations in diurnal rhythm, mobility patterns, and communication styles across regions relate to their unemployment incidence. For this we examine a country-scale publicly articulated social media dataset, where we quantify individual behavioral features from over 19 million geo-located messages distributed among more than 340 different Spanish economic regions, inferred by computing communities of cohesive mobility fluxes. We find that regions exhibiting more diverse mobility fluxes, earlier diurnal rhythms, and more correct grammatical styles display lower unemployment rates. As a result, we provide a simple model able to produce accurate, easily interpretable reconstruction of regional unemployment incidence from their social-media digital fingerprints alone. Our results show that cost-effective economical indicators can be built based on publicly-available social media datasets. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 49 | 18% |
Spain | 30 | 11% |
United Kingdom | 17 | 6% |
France | 10 | 4% |
Germany | 9 | 3% |
Australia | 7 | 3% |
Mexico | 5 | 2% |
Ireland | 4 | 1% |
Indonesia | 3 | 1% |
Other | 33 | 12% |
Unknown | 112 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 216 | 77% |
Scientists | 54 | 19% |
Science communicators (journalists, bloggers, editors) | 6 | 2% |
Practitioners (doctors, other healthcare professionals) | 3 | 1% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 6 | 2% |
United States | 5 | 2% |
Portugal | 2 | <1% |
Brazil | 2 | <1% |
France | 1 | <1% |
United Kingdom | 1 | <1% |
Sri Lanka | 1 | <1% |
Denmark | 1 | <1% |
Italy | 1 | <1% |
Other | 4 | 2% |
Unknown | 218 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 59 | 24% |
Researcher | 45 | 19% |
Student > Master | 28 | 12% |
Student > Bachelor | 24 | 10% |
Lecturer | 12 | 5% |
Other | 50 | 21% |
Unknown | 24 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 45 | 19% |
Social Sciences | 40 | 17% |
Economics, Econometrics and Finance | 26 | 11% |
Engineering | 15 | 6% |
Physics and Astronomy | 14 | 6% |
Other | 65 | 27% |
Unknown | 37 | 15% |