Discerning disinformation through design: Exploring fake news website design patterns

• Main Author: Ruiz, Joaquin Miguel G.
• Format: text
• Language: English
• Published: Animo Repository 2018
• Subjects: Web sites > Design; Web sites > Authoring programs; Fake news; Disinformation
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/5548
• Institution: De La Salle University

As the fake news phenomenon has become a rampant problem worldwide, numerous initiatives have been done to address it. With a steadily increasing amount of people accessing news linked via posts in social media, they are, and will be, exposed to a lot of fake news websites one way or the other. While reading and dissecting the content itself would be the best way to judge if a website is authentic or not, scholars have pointed out that visuals and aesthetics are an important indicator as well. With this in mind, the study proposes to provide an alternative detection via visual means. Using Tandoc et al. as typology of fake news, juxtaposed with visual design cues and elements of website credibility, 23 fake news websites in the Philippines were analyzed to characterize them from a visual standpoint, as well as to glean existing visual design patterns. From a qualitative perspective, the presence and/or absence of certain visual designs cues and elements, as well as the overall aesthetic treatments (low or high) of these were analyzed. Based on the findings, it was shown that not only do most of the fake news websites have common visual design patterns of low aesthetic treatments, but the individual types analyzed (news parodies, news fabrication, and propagandas) had unique visual design patterns that were indicative of their type of fake news based on their facticity and intention to deceive. With the gathered data analyzed from the study, two production projects were rendered to utilize visual design patterns as a means to combat the fake news problem: 1) an infographic series to educate people on an alternative method of gauging if a website is fake or not, and 2) a proposed Google chrome extension that automates the process of assuming through visual means if a news website has the potential to be a purveyor of fake news or not.