Summary – 1
Reflection – 1
Firstly, it is difficult to imagine how large 61 million really is! I was personally quite awed at the scale of experimentation and data collection through online social media and what they can tell us about human behavior.
This paper dealt with multiple issues and could have been a longer paper. An immediately interesting observation is that the effect of online appeals to vote is very small. In more traditional survey-based experiments, this increase would probably not have been noticeable. However, I found it odd that the “social message” group consisted of over 60 million people, however, the “informational message” and control group had only ~600,000. The imbalance seems uncharacteristic for an experiment of this scale and I am curious what the class thought about the distribution of the dataset.
Finally, I found the definition of the close friends arbitrary. The authors define close friends as users who were in the eightieth percentile or higher of frequency of interaction. This definition seems engineered to retrofit the observation that 98% of users had at least one close friend and an average of 10 close friends.
Summary – 2
The 2014 paper on emotional contagion on social networks is mired in controversy. The researchers ask the question – do emotional states spread through social networks? Quoting verbatim from the paper:
The experiment manipulated the extent to which people (N = 689,003) were expose to emotional expressions in their News Feed.
The researchers adapt LIWC to their News Feed algorithm to filter out positive or negative content. They find that when negativity was reduced, users posted more positive content, and consequently when positivity was reduced, the users post less positive content.
Reflection – 2
While the experiment itself is within the realms of Facebook’s acceptable data use policy, there are several signs in the Editorial Expression of Concern and Correction that this experiment may not pass the Institutional Review Board. However, if these two experiments are deemed ethical, they are examples of great experiment design.
Neither paper builds any model. They rely on showing correlation between their dependent and independent variables. As with the previous paper, the effects are small. But applied to large population, even small percentage increases are large enough to take note of.
Questions
- I personally find it quite scary neither study can be done by a university and explicitly needs access from Facebook (or any other social media) for that matter. The consolidation of social media analytics capability in the hands of a few may not bode well for ordinary citizens. How can academic research make this data more available and reachable?
- The first paper lays basis for how societies can be influenced online. Can this be used to target only a small section of users? Can this also be used to identify groups that are under-represented and vocalize their opinions?
