Reviewed Paper
Kramer, Adam DI, Jamie E. Guillory, and Jeffrey T. Hancock. “Experimental evidence of massive-scale emotional contagion through social networks.” Proceedings of the National Academy of Sciences 111.24 (2014): 8788-8790.
Summary
The authors an online social platform, Facebook, and manipulated the extent to which people were exposed to emotional expressions in their News Feed. Two parallel experiments were conducted for positive and negative emotion: One in which exposure to friends’ positive emotional content in their News Feed was reduced, and one in which mood posture to negative emotional content in their News Feed nature, reduced. Posts were determined to be positive or negative if they contained at least one positive or negative word, as defined by the Linguistic Inquiry and Word Count. Both experiments had a control condition, in which a pro portion of posts in their News Feed were omitted random (i.e., without respect to emotional
The experiments took place for 1 week (January 11 January 18). In total, over 3 million posts were analyzed. Participants were randomly selected based on their User ID, resulting in a total of ~155,000 participants per condition who posted at least one status update during the research period.
Reflections
I am skeptical on whether “emotional contagion” has a scientific basis. Therefore, I am even more skeptical about it an online framework. I am going to assume for the rest of the paper that it is indeed “well-established”, the words that the authors use.
How about non-verbal posts i.e. images? For instance, people have a tendency to “post” images that do contain texts, that reflect their emotions or thoughts. How about people who post songs that reflect a specific emotional state? For instance, I assume Johnny Cash’s “Hurt” does not invoke the same emotions with “Macarena”.
Two dependent variables pertaining to emotionality expressed in people’s status updates. The authors initially choose Poisson regression. This is sometimes also referred as “log-linear” model. It’s used when the dependent variable is “counts” or frequencies, while there is a linear relationship between with the independent variables. The authors argue that a direct examination of the frequency of positive and negative words is not possible because the frequencies would be confounded with the change in overall words produced. Subsequently, they revert to a different method, a weighted linear regression in which there is a dummy variable that separated control and treated observations. The coefficient of this dummy variable is statistically significant, providing support that emotions do spread through a network.
Questions
- What if the posts had images that have texts? What if they had song tracks?
- The network structure is not taken into account. For instance, when does the emotional effect “die out”?
