Detection of confirmation and distinction biases in visual analytics systems

Nalçacı, Ayşegül and Girgin, Dilara and Balkı, Semih and Talay, Fatih and Boz, Hasan Alp and Balcısoy, Selim (2019) Detection of confirmation and distinction biases in visual analytics systems. In: 1st EuroVis Workshop on Trustworthy Visualization, TrustVis 2019, Porto

Full text not available from this repository. (Request a copy)


Cognitive bias is a systematic error that introduces drifts and distortions in the human judgment in terms of visual decomposition in the direction of the dominant instance. It has a significant role in decision-making process by means of evaluation of data visualizations. This paper elaborates on the experimental depiction of two cognitive bias types, namely Distinction Bias and Confirmation Bias, through the examination of cognate visual experimentations. The main goal of this implementation is to indicate the existence of cognitive bias in visual analytics systems through the adjustment of data visualization and crowdsourcing in terms of confirmation and distinction biases. Two distinct surveys that include biased and unbiased data visualizations which are related to a given data set were established in order to detect and measure the level of existence of introduced bias types. Practice of crowdsourcing which is provided by Amazon Mechanical Turk have been used for experimentation purposes through prepared surveys. Results statistically indicate that both distinction and confirmation biases has substantial effect and prominent significance on decision-making process.
Item Type: Papers in Conference Proceedings
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Selim Balcısoy
Date Deposited: 02 Aug 2023 14:41
Last Modified: 10 May 2024 11:47

Actions (login required)

View Item
View Item