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Toward Informed News Media Consumpti...

Strong, Jay.

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Toward Informed News Media Consumption: Avoiding Fake News via Labelling of Online Content.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Toward Informed News Media Consumption: Avoiding Fake News via Labelling of Online Content./
Author:	Strong, Jay.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	13 p.
Notes:	Source: Masters Abstracts International, Volume: 81-11.
Contained By:	Masters Abstracts International81-11.
Subject:	Computer science. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27955960
ISBN:	9798643180517

Toward Informed News Media Consumption: Avoiding Fake News via Labelling of Online Content.
Strong, Jay.

Toward Informed News Media Consumption: Avoiding Fake News via Labelling of Online Content. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 13 p.

Source: Masters Abstracts International, Volume: 81-11.

Thesis (M.S.)--University of Michigan-Flint, 2020.

This item must not be sold to any third party vendors.

Social media has become a primary source of online news content for the vast majority of consumers in recent years. News content on social networking platforms is inexpensive, easily accessible, readily available, and rapidly disseminated, thus making it a natural preference for news content providers and consumers alike. However, these same social media platforms have also provided an opportunity for malicious users to undermine credible news sources and widely propagate misinformation to the public. This contemporary fake news phenomenon has been associated with a number of adverse social implications, including public confusion and manipulation, and election interference, among others. Fake news has been used as a means to incite hysteria and diversion, which continues to be a growing problem in the United States and across the globe. Much of the efforts to abate the spread of fake news on social media have been focused on detecting and removing the sources directly. However, much less has been done to empower individuals so that they may avoid the threat of potential harm caused by widespread misinformation on social media.

ISBN: 9798643180517Subjects--Topical Terms:

523869
Computer science.
Subjects--Index Terms:

Content labeling

Toward Informed News Media Consumption: Avoiding Fake News via Labelling of Online Content.
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245 1 0 $a Toward Informed News Media Consumption: Avoiding Fake News via Labelling of Online Content.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2020
300 $a 13 p.
500 $a Source: Masters Abstracts International, Volume: 81-11.
500 $a Advisor: Spradling, Matthew J.
502 $a Thesis (M.S.)--University of Michigan-Flint, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a Social media has become a primary source of online news content for the vast majority of consumers in recent years. News content on social networking platforms is inexpensive, easily accessible, readily available, and rapidly disseminated, thus making it a natural preference for news content providers and consumers alike. However, these same social media platforms have also provided an opportunity for malicious users to undermine credible news sources and widely propagate misinformation to the public. This contemporary fake news phenomenon has been associated with a number of adverse social implications, including public confusion and manipulation, and election interference, among others. Fake news has been used as a means to incite hysteria and diversion, which continues to be a growing problem in the United States and across the globe. Much of the efforts to abate the spread of fake news on social media have been focused on detecting and removing the sources directly. However, much less has been done to empower individuals so that they may avoid the threat of potential harm caused by widespread misinformation on social media.
590 $a School code: 1873.
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650 4 $a Information science. $3 554358
650 4 $a Mass communications. $3 3422380
653 $a Content labeling
653 $a Fake news
653 $a Misinformation
653 $a News media
653 $a Public relations
653 $a Social networks
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690 $a 0723
690 $a 0708
710 2 $a University of Michigan-Flint. $b Computer Science & Information Systems. $3 3283666
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