Material and Data for "Visual Indicators to Increase the Detection of Linguistic Media Bias"

Description This repository includes all files relevant to the paper "Visual Indicators to Increase the Detection of Linguistic Media Bias". Abstract The influence of linguistic bias in online news articles is a growing concern, particularly in the context of shaping public opinion and rising political polarization. While there is a growing body of literature on indicators for misinformation, none have been sufficiently tested to counteract the influence of media bias. Hence, we design six indicators (Bias Bar, Bias Gauge, Bias Highlights, Political Scale, Sentiment Scale, and Trust Score) and test their impact on linguistic bias detection and perception in a two-phased experiment (n = 214). First, we expose participants to short, social-media-like statements along with one indicator and query biasperception. Second, we evaluate bias detection by removing the indicator and asking participants to mark biased words. In addition, we examine how trust, sharing discernment, and sentiment relate to bias perception and detection. Our results show that highlighting biased phrases and showing total bias with contextual information in a gauge significantly improve bias detection skills. However, the strongest predictor for reduced bias detection was political congruency between the statement and the participant. We conclude with design recommendations for linguistic media bias indicators in online news environments. Files 1_R_code.zip contains the files for the statistical analysis R_plots contains additional plots from the statistical analysis, such as demographic data visualizations and analysis of single statements. src contains the code for the statistical analysis. data contains the data, both raw and pocessed. 2_Study Material.xlsx contains the material, including the expert annotation process. 3_Study Screenshots.zip includes all steps of the study as screenshots from the live study platform. 4_All Bias Indicators.zip contains the svgs for all indicators and all statements. 5_News Indicator Literature Review Table.csv contains the literature review table for 33 (+5 Websites) indicators