Analysis and Visualization of Professional’s LinkedIn Data

Garg, Puneet; Rani, Rinkle; Miglani, Sumit

doi:10.1007/978-81-322-2553-9_1

Cited by 1 publication

(2 citation statements)

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“…Additional limitations concern the homogeneity of data, the design of the application’s user interface, blank or over filled columns, abbreviations, misspelled, etc. (Garg et al 2016 ).…”

Section: Introductionmentioning

confidence: 99%

“…LinkedIn data can be used for collecting information about one’s professional contacts such as the job title, company names or geographic locations. This can be done by applying data mining techniques for retrieving the data and performing cluster analysis for aggregating the variables of interest (Garg et al 2016 ). Alternatively, such data, by constructing and validating appropriate metrics, can be utilised to explore professional skills, industry employment and talent migration (Zhu et al 2018 ).…”

Section: Introductionmentioning

confidence: 99%

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Lessons for science and technology policy? Probing the Linkedin network of an RDI organisation

et al. 2022

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In this paper, we seek to examine the network of the Greek National Documentation Centre (EKT) as formed by its LinkedIn followers. By applying specific data collection and processing techniques, we explore the network of all the individuals that follow EKT’s LinkedIn page. Significant manual and automatic approaches have been implemented with regard to data extraction, data curation and data homogenization. The aim is to identify the network’s advancement over time, the institutions involved and the countries. The timeframe of the study spans from when the relevant LinkedIn page was constructed in 2015 to 2020. Findings indicate that there is a steady increase in the number of new followers, peaking in 2020. On an international scale, the evolution of the network of followers is imprinted and distributed in worldwide maps. In total, 68 countries have followed EKT over the examined time period. Also, in terms of followers’ institutional sector the Business Sector (BES) stands out (46.5%). Higher Education (HES) and Government Sector (GOV) are associated with 26.4 and 22.2% of the followers, respectively. Lastly, this paper provides a first institutional and country-level mapping of who constitutes the organisation’s interlocutors in the national and global RDI ecosystem.

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“…Additional limitations concern the homogeneity of data, the design of the application’s user interface, blank or over filled columns, abbreviations, misspelled, etc. (Garg et al 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%