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Reading: Privacy, Social Network Theory and Patterns of Information Revelation on LinkedIn

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Privacy, Social Network Theory and Patterns of Information Revelation on LinkedIn

Author:

Marta Stelmaszak

Department of Management, London School of Economics and Political Science, GB
About Marta
MSc Management of Information Systems and Innovation (2013/2014)
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Abstract

Online social networks and privacy are often discussed in relation to Facebook or other similar predominantly social platforms (e.g. Friendster). LinkedIn, despite many public concerns about privacy, rarely is the scope of research, though privacy breaches have been identiied coming from other users, the service provider and third-party applications. The scope of this paper is to analyse privacy aspects on LinkedIn in relation to potential risks coming from other users through the application of the social network theory and the analysis of patterns of information revelation on LinkedIn. Following a detailed analysis of LinkedIn proiles and information revealed to diferent degree of connections, a range of indings is presented, including the increase in polarisation of connections, a substantial increase in the number of weak ties, an unprecedented number of connections, as well as potential risks arising from the degree of identiiability, type of information revealed and visibility of information on LinkedIn.

How to Cite: Stelmaszak, M., 2014. Privacy, Social Network Theory and Patterns of Information Revelation on LinkedIn. iSCHANNEL, 9(1), pp.11–17.
Published on 01 Sep 2014.
Peer Reviewed

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