학술논문

Analysis of Dark Pattern-related Tweets from 2010
Document Type
Conference
Source
2023 IEEE 8th International Conference on Big Data Analytics (ICBDA) Big Data Analytics (ICBDA), 2023 IEEE 8th International Conference on. :100-106 Mar, 2023
Subject
Computing and Processing
Sentiment analysis
Privacy
Regulators
Resists
Interference
User interfaces
Position measurement
Dark Patterns
Tweets
Consumer Protection
Topic modeling
Language
Abstract
Dark patterns are defined as user interfaces that make users behave unintendedly, such as buying something or subscribing to some services. The use of dark patterns is considered an infringement of users’ rights and privacy. In this study, we reveal the users’ responses toward dark patterns by analyzing 12 years of tweets. Our findings include 1) users in countries in which dark patterns-related regulations have been implemented have a higher level of discussions about dark patterns; 2) tweets about dark patterns shifted from around 2017 from sharing their diversity to acting to resist them; 3) the commonly discussed dark pattern types of tweets are sneaking, obstruction, and interface interference, which are widely used in e-commerce sites. Our findings may help policymakers and regulators to promote our more secure internet use.