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Social Media Ethics: A Rawlsian Approach to Hypertargeting and Psychometrics in Political and Commercial Campaigns

Published: 21 December 2018 Publication History

Abstract

Targeted social media advertising based on psychometric user profiling has emerged as an effective way of reaching individuals who are predisposed to accept and be persuaded by the advertising message. This article argues that in the case of political advertising, this may present a democratic and ethical challenge. Hypertargeting methods such as psychometrics can “crowd out” political communication with opposing views due to individual attention and time limitations, creating inequities in the access to information essential for voting decisions. The use of psychometrics also appears to have been used to spread both information and misinformation through social media in recent elections in the U.S. and Europe. This article is an applied ethics study of these methods in the context of democratic processes and compared to purely commercial situations. The ethical approach is based on the theoretical, contractarian work of John Rawls, which serves as a lens through which the author examines whether the rights of individuals, as Rawls attributes them, are violated by this practice. The article concludes that within a Rawlsian framework, use of psychometrics in commercial advertising on social media platforms, though not immune to criticism, is not necessarily unethical. In a democracy, however, the individual cannot abandon the consumption of political information, and since using psychometrics in political campaigning makes access to such information unequal, it violates Rawlsian ethics and should be regulated.

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cover image ACM Transactions on Social Computing
ACM Transactions on Social Computing  Volume 1, Issue 4
Special Issue on HICSS 2018
December 2018
106 pages
EISSN:2469-7826
DOI:10.1145/3301392
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 21 December 2018
Accepted: 01 September 2018
Revised: 01 September 2018
Received: 01 April 2018
Published in TSC Volume 1, Issue 4

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  1. Social media
  2. data collection
  3. ethics
  4. psychometrics
  5. targeting

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