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CTRL + F "shortly before" 0 results. Putting quotes around shortly before makes it seem like you are drawing from the linked story, but you aren't. A quote th

CTRL + F "shortly before" 0 results. Putting quotes around shortly before makes it seem like you are drawing from the linked story, but you aren't. A quote that is actually from the article: >In the 16 months prior to the first major Snowden stories in June 2013, the articles drew a variable but an increasing audience, with a low point of about 2.2 million per month rising to 3.0 million just before disclosures of the NSA's Internet spying programs. Views of the sensitive pages rapidly fell back to 2.2 million a month in the next two months and later dipped under 2.0 million before stabilizing below 2.5 million 14 months later, Penney found. They did not use the day or week of the Boston Bombing as their baseline. Don't misrepresent the research.

slg 10y ago
You are right on the quoting thing. I could have sworn it said "shortly before" but it said "just before". My mistake. Although those are almost semantically identical so I am a little confused on why you are calling it out in such specificity. >They did not use the day or week of the Boston Bombing as their baseline. Don't misrepresent the research. Snowden's leaks came out less than two months after the largest terrorist attack on US soil since 9/11. Since they are measuring monthly stats, they are using either the month of or the month after the Boston bombings as part of their "just before" time frame. If you look at all those number, the 3 million is really the biggest outlier. Isn't it possible that views for these terrorist related pages generally falls between 2 and 2.5 million with 20-50% jumps in page views in the aftermath of large terrorist attacks?
- garrettgrimsley 10y ago
  Because the "just before" is referring to the overall trend, not the single month before the Snowden leaks. The actual highest single month view count is found in November 2012 with around 4 million views. The months around the Boston Bombing are not outliers. November 2012, as well as July 2014, are outliers. Eliminating these outliers from the analysis strengthens the case for the existence of a chilling effect. See pages 28-39 of the paper [0] for their methodology and findings. If I'm being unduly short it is because the sort of low-effort skepticism [1] that you offered is all too common with any article involving a statistical analysis. [0] http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2769645 http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2769645 [1] "Did the researchers account for {{obvious factor}}?" Yes, they did. Check before commenting.

slg 10y ago

You are right on the quoting thing. I could have sworn it said "shortly before" but it said "just before". My mistake. Although those are almost semantically identical so I am a little confused on why you are calling it out in such specificity. >They did not use the day or week of the Boston Bombing as their baseline. Don't misrepresent the research. Snowden's leaks came out less than two months after the largest terrorist attack on US soil since 9/11. Since they are measuring monthly stats, they are using either the month of or the month after the Boston bombings as part of their "just before" time frame. If you look at all those number, the 3 million is really the biggest outlier. Isn't it possible that views for these terrorist related pages generally falls between 2 and 2.5 million with 20-50% jumps in page views in the aftermath of large terrorist attacks?

garrettgrimsley 10y ago
Because the "just before" is referring to the overall trend, not the single month before the Snowden leaks. The actual highest single month view count is found in November 2012 with around 4 million views. The months around the Boston Bombing are not outliers. November 2012, as well as July 2014, are outliers. Eliminating these outliers from the analysis strengthens the case for the existence of a chilling effect. See pages 28-39 of the paper [0] for their methodology and findings. If I'm being unduly short it is because the sort of low-effort skepticism [1] that you offered is all too common with any article involving a statistical analysis. [0] http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2769645 http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2769645 [1] "Did the researchers account for {{obvious factor}}?" Yes, they did. Check before commenting.