dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Nimwegen, Christof van | |
dc.contributor.author | Sluijpers, Matthias | |
dc.date.accessioned | 2022-07-28T01:01:14Z | |
dc.date.available | 2022-07-28T01:01:14Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/41972 | |
dc.description.abstract | Dark patterns are questionable design choices that are made to steer users towards business-preferred outcomes. As there are many different types of dark patterns, this raises the question of what dark patterns are truly unacceptable and what dark patterns are somewhat more tolerable. There are several aspects that could be used to help answer this question. One of these aspects is dark pattern blindness: a phenomenon where users do not recognize a dark pattern that they are exposed to. The first and main research aim of the current study was to investigate to what extent dark pattern blindness occurs for a selection of different dark patterns. In addition, Bergman (2021) developed the System Darkness Scale (SDS) to measure the perceived “darkness” of a system. The second research aim was to investigate whether the scale can differentiate between system versions with dark patterns and system versions without dark patterns (other than the two system versions that were used when developing the scale). To this end, three systems were created, each with a version with and without dark patterns. An online experiment was conducted where participants were assigned to two of these systems - one of which would always be a version with dark patterns and the other would always be a version without dark patterns - and performed two short real-world tasks. Subsequently, the participants evaluated the systems using the SDS and answered a set of questions about whether they had noticed any dark patterns. The results show that several dark pattern instances had a relatively low recognition level, whilst several other dark pattern instances had a relatively high recognition level. However, these results cannot be generalized to a wider population - amongst others, due to the small sample size - nor to other instances of the investigated dark pattern types. In addition, for each of the three systems, the evaluation of the SDS could not establish whether or not the scale is able to differentiate between the version with dark patterns and the corresponding version without dark patterns. Several pointers are provided for future research. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | The “Investigating Dark Pattern Blindness” thesis features the topic of dark patterns. Dark patterns are questionable design choices that are made to steer users towards business-preferred outcomes. In specific, dark pattern blindness is investigated, which is a phenomenon where users do not recognize a certain dark pattern that they are exposed to. In addition, the System Darkness Scale (SDS) is investigated, which was developed by Bergman (2021) to measure the perceived “darkness” of a system. | |
dc.title | Investigating Dark Pattern Blindness | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.courseuu | Human-Computer Interaction | |
dc.thesis.id | 6889 | |