Misleading graphs in context: Less misleading than expected

Autor: Jannetje E. P. Driessen, Daniël A. C. Vos, Ionica Smeets, Casper J. Albers
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: PLoS ONE, Vol 17, Iss 6 (2022)
Druh dokumentu: article
ISSN: 1932-6203
Popis: Misleading graphs are a source of misinformation that worry many experts. Especially people with a low graph literacy are thought to be persuaded by graphs that misrepresent the underlying data. But we know little about how people interpret misleading graphs and how these graphs influence their opinions. In this study we focus on the effect of truncating the y-axis for a line chart which exaggerates an upgoing trend. In a randomized controlled trial, we showed participants either a normal or a misleading chart, and we did so in two different contexts. After they had seen the graphs, we asked participants their opinion on the trend and to give an estimation of the increase. Finally we measured their graph literacy. Our results show that context is the only significant factor in opinion-forming; the misleading graph and graph literacy had no effect. None of these factors had a significant impact on estimations for the increase. These results show that people might be less susceptible to misleading graphs than we thought and that context has more impact than a misleading y-axis.
Databáze: Directory of Open Access Journals
Nepřihlášeným uživatelům se plný text nezobrazuje