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Social Media Fingerprints of Unemployment

Overview of attention for article published in PLoS ONE, May 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
5 news outlets
blogs
4 blogs
policy
1 policy source
twitter
330 tweeters
facebook
4 Facebook pages
googleplus
7 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
172 Mendeley
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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.

Twitter Demographics

The data shown below were collected from the profiles of 330 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 5%
Spain 7 4%
Italy 2 1%
Brazil 2 1%
Portugal 2 1%
Netherlands 1 <1%
China 1 <1%
Luxembourg 1 <1%
Denmark 1 <1%
Other 4 2%
Unknown 143 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 30%
Researcher 33 19%
Student > Master 21 12%
Student > Bachelor 15 9%
Other 11 6%
Other 40 23%
Readers by discipline Count As %
Computer Science 47 27%
Social Sciences 30 17%
Economics, Econometrics and Finance 19 11%
Physics and Astronomy 12 7%
Unspecified 11 6%
Other 53 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 324. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 January 2019.
All research outputs
#31,225
of 12,498,674 outputs
Outputs from PLoS ONE
#697
of 136,977 outputs
Outputs of similar age
#574
of 229,472 outputs
Outputs of similar age from PLoS ONE
#30
of 3,059 outputs
Altmetric has tracked 12,498,674 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 136,977 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.7. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 229,472 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 3,059 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.