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Social Media Fingerprints of Unemployment

Author

Listed:
  • 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.

Suggested Citation

  • Alejandro Llorente & Manuel Garcia-Herranz & Manuel Cebrian & Esteban Moro, 2015. "Social Media Fingerprints of Unemployment," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-13, May.
    • Handle: RePEc:plo:pone00:0128692
    DOI: 10.1371/journal.pone.0128692
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    References listed on IDEAS

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    Cited by:

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    2. Ola Hall & Francis Dompae & Ibrahim Wahab & Fred Mawunyo Dzanku, 2023. "A review of machine learning and satellite imagery for poverty prediction: Implications for development research and applications," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(7), pages 1753-1768, October.
    3. Pulkit Sharma & Achut Manandhar & Patrick Thomson & Jacob Katuva & Robert Hope & David A. Clifton, 2019. "Combining Multi-Modal Statistics for Welfare Prediction Using Deep Learning," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    4. Francis Rathinam & Sayak Khatua & Zeba Siddiqui & Manya Malik & Pallavi Duggal & Samantha Watson & Xavier Vollenweider, 2021. "Using big data for evaluating development outcomes: A systematic map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    5. Samara Ahmed & Adil E. Rajput & Akila Sarirete & Asma Aljaberi & Ohoud Alghanem & Abrar Alsheraigi, 2020. "Studying Unemployment Effects on Mental Health: Social Media versus the Traditional Approach," Sustainability, MDPI, vol. 12(19), pages 1-14, October.
    6. David Pastor-Escuredo & Yolanda Torres & María Martínez-Torres & Pedro J. Zufiria, 2020. "Rapid Multi-Dimensional Impact Assessment of Floods," Sustainability, MDPI, vol. 12(10), pages 1-20, May.
    7. Grazia Biorci & Antonella Emina & Michelangelo Puliga & Lisa Sella & Gianna Vivaldo, 2016. "Tweet-tales: moods of socio-economic crisis?," Working Papers 04/2016, IMT School for Advanced Studies Lucca, revised Jul 2016.
    8. Jian Gao & Tao Zhou, 2017. "Quantifying China's Regional Economic Complexity," Papers 1703.01292, arXiv.org, revised Nov 2017.
    9. Abdullah Almaatouq, 2016. "Complex Systems and a Computational Social Science Perspective on the Labor Market," Papers 1606.08562, arXiv.org.
    10. Cem Çağrı Dönmez & Abdulkadir Atalan, 2019. "Developing Statistical Optimization Models for Urban Competitiveness Index: Under the Boundaries of Econophysics Approach," Complexity, Hindawi, vol. 2019, pages 1-11, November.
    11. S. Martin-Gutierrez & J. C. Losada & R. M. Benito, 2018. "Recurrent Patterns of User Behavior in Different Electoral Campaigns: A Twitter Analysis of the Spanish General Elections of 2015 and 2016," Complexity, Hindawi, vol. 2018, pages 1-15, December.
    12. Margarita Torre & Alejandro Llorente, 2019. "Winning the War for Talent: An Experimental Evaluation of Online Recruitment Campaigns Using Twitter," Business and Management Studies, Redfame publishing, vol. 5(1), pages 10-24, March.
    13. Kyriaki Kalimeri & Mariano G. Beiró & Andrea Bonanomi & Alessandro Rosina & Ciro Cattuto, 2020. "Traditional versus Facebook-based surveys: Evaluation of biases in self-reported demographic and psychometric information," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(5), pages 133-148.
    14. Ping Gao & Shenghe Liu & Wei Qi & Honggang Qi, 2020. "The Nexus between Poverty and the Environment: A Case Study of Lijiang, China," Sustainability, MDPI, vol. 12(3), pages 1-17, February.
    15. Talayeh Aledavood & Eduardo López & Sam G B Roberts & Felix Reed-Tsochas & Esteban Moro & Robin I M Dunbar & Jari Saramäki, 2015. "Daily Rhythms in Mobile Telephone Communication," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-14, September.
    16. Indaco, Agustín, 2020. "From twitter to GDP: Estimating economic activity from social media," Regional Science and Urban Economics, Elsevier, vol. 85(C).

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