Toward Informed News Media Consumption: Avoiding Fake News Via Labelling of Online Content
dc.contributor.author | Strong, Jay | |
dc.contributor.advisor | Spradling, Matthew J. | |
dc.date.accessioned | 2020-05-07T14:14:42Z | |
dc.date.available | NO_RESTRICTION | en_US |
dc.date.available | 2020-05-07T14:14:42Z | |
dc.date.issued | 2020-04-22 | |
dc.date.submitted | 2020 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/155018 | |
dc.description.abstract | 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. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | social media | en_US |
dc.subject | content labeling | en_US |
dc.subject | fake news | en_US |
dc.subject | misinformation | en_US |
dc.subject | news media | en_US |
dc.subject | social networks | en_US |
dc.subject.other | computer science | en_US |
dc.subject.other | information science | en_US |
dc.subject.other | media studies | en_US |
dc.title | Toward Informed News Media Consumption: Avoiding Fake News Via Labelling of Online Content | en_US |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | Master of Science (MS) | en_US |
dc.description.thesisdegreediscipline | Computer Science | en_US |
dc.description.thesisdegreegrantor | University of Michigan-Flint | en_US |
dc.contributor.committeemember | Allison, Mark | |
dc.contributor.committeemember | Alhosban, Amal | |
dc.identifier.uniqname | 35201446 | en_US |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/155018/1/Strong2020.pdf | |
dc.identifier.orcid | https://orcid.org/0000-0002-2520-876X | en_US |
dc.description.filedescription | Description of Strong2020.pdf : Thesis | |
dc.identifier.name-orcid | Strong, Jay; 0000-0002-2520-876X | en_US |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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