Journal Article

Augmenting surveys with social media data: a probabilistic framework for LinkedIn data linkage. -conference paper abstract-

By Paulo Serodio, Tarek Al Baghal, Luke Sloan, Shujun Liu and Curtis Jessop

Publication details

Publication date
Published in
International Journal of Population Data Science
Volume
9
Publisher
Swansea University
DOI
https://doi.org/10.23889/ijpds.v9i4.2433
ISSN
23994908

Summary

Introduction & Background:
LinkedIn, with its extensive global network of over 900 million members across more than 200 countries, presents a unique repository for examining labour market dynamics, professional development, and the impact of social networking on employment opportunities. Despite its potential, LinkedIn's wealth of data on professional trajectories, skills, and labour market outcomes remains largely untapped in survey research due to challenges in data collection.

Notes

Conference Proceedings for 2nd Digital Footprints Conference 'Linking Digital Data for Social Impact', 8-9th May 2024, University of Bristol.

Open Access

This work is licensed under a Creative Commons Attribution 4.0 International License.

Topics