Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp01ms35tc47w
Full metadata record
DC Field | Value | Language |
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dc.contributor.advisor | Chetty, Marshini | - |
dc.contributor.author | Swart, Michael | - |
dc.date.accessioned | 2019-07-24T19:32:04Z | - |
dc.date.available | 2019-07-24T19:32:04Z | - |
dc.date.created | 2019-05-06 | - |
dc.date.issued | 2019-07-24 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01ms35tc47w | - |
dc.description.abstract | Social 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.mimetype | application/pdf | - |
dc.language.iso | en | en_US |
dc.title | AdIntuition: Automatic Sponsorship Disclosure on Social Media | en_US |
dc.type | Princeton University Senior Theses | - |
pu.date.classyear | 2019 | en_US |
pu.department | Computer Science | en_US |
pu.pdf.coverpage | SeniorThesisCoverPage | - |
pu.contributor.authorid | 961140849 | - |
Appears in Collections: | Computer Science, 1988-2020 |
Files in This Item:
File | Description | Size | Format | |
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SWART-MICHAEL-THESIS.pdf | 2.17 MB | Adobe PDF | Request a copy |
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