Utilizing Big Data to Understand Public Perception In Necessary Policy Changes Before and After a Mass Shooting
School Name
Spring Valley High School
Grade Level
11th Grade
Presentation Topic
Sociology
Presentation Type
Non-Mentored
Written Paper Award
1st Place
Abstract
From May 25, 2015 to May 25, 2018, there were 1,296 mass shootings in the United States. This research attempted to evaluate public support for gun regulation before and after major mass shootings. It was hypothesized that there would be a higher percentage of Tweets opposing gun control 1 week before each mass shooting, and a higher percentage of Tweets supporting gun control 72 hours following each mass shooting. The researcher used “Big Data” to account for outliers and skewing points by analyzing 250 Tweets that occurred one week before each major mass shooting, 72 hours following the mass shooting, and 2 weeks after the shooting, for a total of 750 per shooting. The Tweets were restricted to include at least one of the following hashtags: #secondamendment, #neveragain, #shooting, #NRA, #guncontrol, #gunviolence, and #2A. The Tweets were categorized as pro-gun control, anti-gun control, or neutral, defined by operational definitions. It was found that at ɑ = 0.01, there was a significant decrease in the anti-gun control Tweets and an increase in the pro-gun control Tweets posted 72 hours following a shooting compared to 1 week prior, with p-values < 0.00001. There was a significant increase in anti-gun control Tweets and decrease in pro-gun control Tweets 2 weeks after the shooting compared to 72 hours after the shooting, showing a regression towards the baseline, with p-values < 0.00001. Therefore, people were more vocal about stricter gun control after a mass shooting than before, but regressed back within 2 weeks.
Recommended Citation
Shytle, Elizabeth, "Utilizing Big Data to Understand Public Perception In Necessary Policy Changes Before and After a Mass Shooting" (2019). South Carolina Junior Academy of Science. 299.
https://scholarexchange.furman.edu/scjas/2019/all/299
Location
Founders Hall 251 C
Start Date
3-30-2019 8:45 AM
Presentation Format
Oral and Written
Group Project
No
Utilizing Big Data to Understand Public Perception In Necessary Policy Changes Before and After a Mass Shooting
Founders Hall 251 C
From May 25, 2015 to May 25, 2018, there were 1,296 mass shootings in the United States. This research attempted to evaluate public support for gun regulation before and after major mass shootings. It was hypothesized that there would be a higher percentage of Tweets opposing gun control 1 week before each mass shooting, and a higher percentage of Tweets supporting gun control 72 hours following each mass shooting. The researcher used “Big Data” to account for outliers and skewing points by analyzing 250 Tweets that occurred one week before each major mass shooting, 72 hours following the mass shooting, and 2 weeks after the shooting, for a total of 750 per shooting. The Tweets were restricted to include at least one of the following hashtags: #secondamendment, #neveragain, #shooting, #NRA, #guncontrol, #gunviolence, and #2A. The Tweets were categorized as pro-gun control, anti-gun control, or neutral, defined by operational definitions. It was found that at ɑ = 0.01, there was a significant decrease in the anti-gun control Tweets and an increase in the pro-gun control Tweets posted 72 hours following a shooting compared to 1 week prior, with p-values < 0.00001. There was a significant increase in anti-gun control Tweets and decrease in pro-gun control Tweets 2 weeks after the shooting compared to 72 hours after the shooting, showing a regression towards the baseline, with p-values < 0.00001. Therefore, people were more vocal about stricter gun control after a mass shooting than before, but regressed back within 2 weeks.