TY - GEN
T1 - Measuring professional skill development in U.S. Cities using internet search queries
AU - Jhaver, Shagun
AU - Cranshaw, Justin
AU - Counts, Scott
N1 - Publisher Copyright:
Copyright © 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2019
Y1 - 2019
N2 - Using a sample of 10 million skill development-related queries from a popular internet search engine, drawn from almost 400 U.S. cities and over a 5 year period (2012 - 2016), we characterize the skills people search for across these cities, and relate them to measures of economic output, including GDP and unemployment. Findings show that differences in the amount, type, and specialization of skill development searches distinguish economically thriving cities from those that are struggling, including explaining variance in future GDP growth after accounting for socioeconomic demographics such as income and poverty levels. Overall, internet-based skill development appears to contribute to rich cities getting richer, with initially well-off cities seeing more and more specialized skill-related searching that in turn aligns with future economic growth.
AB - Using a sample of 10 million skill development-related queries from a popular internet search engine, drawn from almost 400 U.S. cities and over a 5 year period (2012 - 2016), we characterize the skills people search for across these cities, and relate them to measures of economic output, including GDP and unemployment. Findings show that differences in the amount, type, and specialization of skill development searches distinguish economically thriving cities from those that are struggling, including explaining variance in future GDP growth after accounting for socioeconomic demographics such as income and poverty levels. Overall, internet-based skill development appears to contribute to rich cities getting richer, with initially well-off cities seeing more and more specialized skill-related searching that in turn aligns with future economic growth.
UR - https://www.scopus.com/pages/publications/85069967165
UR - https://www.scopus.com/pages/publications/85069967165#tab=citedBy
U2 - 10.1609/icwsm.v13i01.3228
DO - 10.1609/icwsm.v13i01.3228
M3 - Conference contribution
AN - SCOPUS:85069967165
SN - 9781577358060
T3 - Proceedings of the 13th International Conference on Web and Social Media, ICWSM 2019
SP - 267
EP - 277
BT - Proceedings of the 13th International AAAI Conference on Web and Social Media, ICWSM 2019
PB - Association for the Advancement of Artificial Intelligence
T2 - 13th International AAAI Conference on Web and Social Media, ICWSM 2019
Y2 - 11 June 2019 through 14 June 2019
ER -