This study focused on four common techniques of distortion of data (truncated axis, area as quantity, aspect ratio, and inverted axis) that lead to two main deception effects (message reversal and message exaggeration/understatement). The line chart/aspect ratio proved to have the biggest distortion effect, which makes sense to me because among the other techniques, a distorted aspect ratio seems the most difficult to mentally adjust for, if that makes any sense. For example, it is easier to imagine/visualize a non-truncated axis, or an accurate bubble case, but harder to mentally see what a corrected aspect ratio graph would look like.

It was interesting to read through the identification and classification of different techniques was because I feel like I often notice and am critical of when these techniques are used in the real world, but I never stop to really crystallize and classify them in my head. On the other hand, while seeing these distortion techniques irks me, I also have been guilty myself of distorting data and I think it is something everyone does because we are always looking for stories out of data and we obviously want to be able to tell the strongest narrative that we can paint. However, there have definitely been times where I have tried to exaggerate my data, but as much as I try, there is a point where the data IS what it is.. Therefore, in response to the question of how deceptive are deceptive visualizations, I think you can definitely stretch the truth a bit but there is a limit to where you cannot completely “lie” or fabricate something that is just blatantly opposite/false.