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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01ms35tc47w
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dc.contributor.advisorChetty, Marshini-
dc.contributor.authorSwart, Michael-
dc.date.accessioned2019-07-24T19:32:04Z-
dc.date.available2019-07-24T19:32:04Z-
dc.date.created2019-05-06-
dc.date.issued2019-07-24-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01ms35tc47w-
dc.description.abstractSocial Media’s ability to connect people has provided a ripe opportunity for brands to effectively market their products. However, when creating sponsored content, some social media influencers fail to disclose that they are receiving compensation for their endorsement of a product. This lack of disclosure is deceptive and leaves viewers questioning the authenticity of an endorsement. I created a Google Chrome extension called AdIntuition that detects and discloses the presence of affiliate marketing, a type of social media marketing, on YouTube in an effort to provide video viewers insight into deceptive marketing practices. Using a list of known affiliate marketing link patterns and URL query parameters, AdIntuition checks all links in a YouTube video’s description for affiliate marketing content. Additionally, each sentence in a YouTube description is checked against a pre-trained classifier for the existence of coupon codes, which are also used in affiliate marketing campaigns. In order to test the project’s success, I designed and ran a user study that found that participants were able to better determine the existence of affiliate marketing in a YouTube video when using the extension.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.titleAdIntuition: Automatic Sponsorship Disclosure on Social Mediaen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2019en_US
pu.departmentComputer Scienceen_US
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid961140849-
Appears in Collections:Computer Science, 1988-2020

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