“When you are young, you look at television and think, there’s a conspiracy. The networks have conspired to dumb us down. But when you get a little older, you realize that’s not true. The networks are in business to give people exactly what they want.” – Steve Jobs
The paper is a good precursor to the research project that Shruthi and I are interested in. I would like to analyze the paper in terms of a few keys points that were mentioned trying to capture the things mentioned in the paper and sharing my own insights and possible explanations for them.
Conspiracy theory:
The paper eludes to this concept of people online and websites, in general, are catering to “conspiracy theories” as that is what has been seen to draw people’s attention. But what are conspiracy theories? The paper categorizes them under “alternative narratives” not giving a formal definition of what is being considered as “conspiracy theory”. I will define it as “any propagation of misinformation” which I believe is broadly the same meaning the paper talks about as well. A couple of interesting facts that the paper talks about which I feel is worthy of address are:
- “once someone believes in a conspiracy theory of an event, it is extremely hard to dissuade them from this belief“. Here I would like to further substantiate that some opinions and beliefs are ingrained into a person and unless they are given a logical explanation over a long period of time reinforcing the notion that they might be wrong it will be difficult to get a person to change their stance. This effort is a necessary one and I feel painting the picture of where the information is coming from will help negatively reinforce the idea that they are right. If we do not put an effort to do this then “belief in one conspiracy theory correlates with an increased likelihood that an individual will believe in another” will turn out to be true as well.
- The definition of conspiracy theorists being a part of ‘alternative to “corporate-controlled” media‘ is one I do not agree with. This raises a philosophical debate as to where we draw a line? Should we draw a line or should we look for methods that do not try and draw a line?
Bias:
“first author is a left-leaning individual who receives her news primarily through mainstream sources and who considers that alternative narratives regarding these mass shooting events to be false” was according to me a revelation in the field of human behavioral modeling. Being a part of the Human Factors community and have interacted with many Human Factors professionals this is the first time that I have seen an author explicitly mentioned inherent bias in an effort to eliminate it. Acknowledgment is the first step to elimination. I think the elimination of Bias should follow a similar procedure like the time-tested 12-step model we follow in Addiction recovery. That could be an interesting study as a model like that could shed some light on my hypothesis that “Humans are addicted to being biased”.
Another point is the use of confusion matrix based on signal detection theory. We could use this to build a conservative or liberal model of a human and then use this generalized model to help design tools to foil the propagation of misinformation and “alternative narratives”.
General Reflection:
In general, I found a couple more observations that resonated with the previous readings of this semester.
The overall referral to misinformation propagation coupled with the video lecture where the author presents an example of Deep Fakes for misinformation propagation, sent me back to this question that I have been asking myself off late. All of the research we have analyzed is on text data. What if the same was video data? Especially in this case as we do get some if not all of our information from YouTube and other such video platforms. Will this research translate directly to that case? Is there existing and/or ongoing research on the same? Is there a need for research on it?
Theme convergence was another concept that really interested me as I would be really interested in understanding how diverse domains converge to common themes. These will help build better group behavioral models and overcome the problem of falling into Simpson’s paradox that researchers fall into, especially when dealing with human data.
PAPER:
K. Starbird, “Examining the Alternative Media Ecosystem through the Production of Alternative Narratives of Mass Shooting Events on Twitter,” Icwsm17, no. Icwsm, pp. 230–239, 2017.
