Paper 1: Starbird, Kate. “Examining the Alternative Media Ecosystem Through the Production of Alternative Narratives of Mass Shooting Events on Twitter.” ICWSM. 2017.
Startbird et. al’s paper qualitatively analyzes sources of news related to shooting events on twitter based on the interpretive graph analysis. She analyzes how alternative sources and mainstream sources are referred in different contexts when it comes to conspiracy theories. That is, either in support or to dispute the claims. The paper also dwells on how such citing of alternative news sources can foil politically motivated conspiratorial thinking.
One common theme that is present throughout the paper, is how all of the events are blamed on one central “untouchable” entity such as U.S government or a secret organization. This comes from a very common conspiratorial trait according to which “everything needs to have a reason”. It is found that conspiracists try to relive the event as an aftermath of that event by “rationalizing” it.[1] Further, such theories go on to giving increased importance to certain agents such as FBI, government, Illuminati etc. The paper mentions that 44 out of 80 sources were promoting political agenda. It would be interesting to know which agents such source frequently target and how do they tie such agents to multiple events.
The paper makes another excellent point that “exposure to online media correlates with distrust of mainstream media”. Considering that the mainstream media is correcting conspiratorial claims or presenting the neutral narrative, it will be interesting to do a contrast study in which network of users “bashing” mainstream media can be found. One important thing to note here is that just by text analysis methods, it is difficult to understand the context in which the source of information is cited. This reflects in the three ways mentioned in the paper by which alternative media promotes alternative narratives. 1. They cite alternative sources to support the alternate narrative or 2. They cite mainstream sources in a confrontational way. This is where the quantitative approaches are tricky to use because clearly, just the presence of a link in a post doesn’t tell much about the argument made about it. Similarly, hand-coding techniques are also limiting because analyzing the context, source and narrative takes a long time and results in high quality but smaller dataset. One possible way to automate this process can be to perform “Entity Sentiment Analysis” that combines both entity analysis and sentiment analysis and attempts to determine the sentiment (positive or negative) expressed about entities within the text. Treating the sources cited as “proxy” entities, it can be possible to find out what is being said about them in the positive or negative light.
The paper also mentions that believing in one conspiracy theory makes a person more likely to believe another. This, alongwith the cluster of sources supporting alternative narratives domains in the figure 2 can form a basis for quantitatively analyzing how communities unify. [2]
Lastly, as a further research point, it is also interesting to analyze when a particular alternate narrative gets popular. Why some theories take hold while many more do not? Is it because of the informational pressure or because of the particular event. One starting point for this kind of analysis is [3] which says that when the external event threatens to influence users directly, they explore content outside their filter bubble. This will require retrospective analysis of posting behavior before and after a specific event considering users which are either in geographical, racial any other ideological proximity of the group affected by that event.
[1] Sunstein, C. R., & Vermeule, A. (2009). Conspiracy Theories: Causes and Cures. Journal of Political Philosophy, 17(2), 202–227. https://doi.org/10.1111/j.1467-9760.2008.00325.x
[2]Science vs Conspiracy: Collective Narratives in the Age of Misinformation. PLOS ONE, 10(2), e0118093. https://doi.org/10.1371/journal.pone.0118093
[3] Koutra, D., Bennett, P., & Horvitz, E. (2015). Events and Controversies: Influences of a Shocking News Event on Information Seeking. TAIA Workshop in SIGIR, 0–3. https://doi.org/10.1145/2736277.2741099
