I want your (anonymized) social media data
In this crossposting from The Conversation Anthony Sanford argues that despite GDPR and the Cambridge Analytica scandal, there are ways for researchers to legitimately and ethically use your social media data.
Social media sites’ responses to the Facebook-Cambridge Analytica scandal and new European privacy regulations have given users much more control over who can access their data, and for what purposes. To me, as a social media user, these are positive developments: It’s scary to think what these platforms could do with the troves of data available about me. But as a researcher, increased restrictions on data sharing worry me.
I am among the many scholars who depend on data from social media to gain insights into people’s actions. In a rush to protect individuals’ privacy, I worry that an unintended casualty could be knowledge about human nature. My most recent work, for example, analyzes feelings people express on Twitter to explain why the stock market fluctuates so much over the course of a single day. There are applications well beyond finance. Other scholars have studied mass transit rider satisfaction, emergency alert systems’ function during natural disasters and how online interactions influence people’s desire to lead healthy lifestyles.
As a researcher myself, I find myself disagreeing with almost everything in this post.
Privacy and permission are fundamental to conducting research, and using social media data to conduct research without explicit permission is overstepping the line. It would lead to further mistrust in the research industry and inevitable privacy breaches. You only need to look at the steps outlined here that would be required to see that there are too many points at which it could break down.
Anything beyond relatively broad collective data is just unacceptable.
I concur.
The article is not founded on research per se, but about data analysis.
I also suspect that the stock market link referred to is probably an example of correlation rather than causation.