The research opportunities enabled by social media data are undeniable.
We explored problems that researchers might encounter due to this mismatch between data and methods.
Absurd science
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One brain imaging studyappeared to show the neural activity of a dead salmon tasked with identifying emotions in photos.
Ananalysis of longitudinal statistics from public health recordssuggested that acne, height, and headaches are contagious.
Why would a researcher go out of their way to explore such ridiculous ideas?
The value of these studies is not in presenting a new substantive finding.
Rather, the nonsensical results highlight problems with the methods used to achieve them.
Our research explores whether the same problems can afflict studies that use data from social media.
And we discovered that indeed they do.
The test identifies a misaligned disc in your spine.
This finding might be important and inform a treatment plan.
This part of the finding is as real as any finding.
Past and current studies have tried to identify what factors influence Twitter users decisions to retweet other tweets.
Upon analyzing six datasets containing hundreds of thousands of tweets, the answer we found was yes.
What is a meaningful finding?
Another helpful practice is to check whether results are stable after removing outliers and controlling forcovariates.
These practices are important, but they alone are not sufficient to deal with the problem we identify.
