Student Scholar Symposium Abstracts and Posters
Document Type
Poster
Publication Date
Spring 5-10-2017
Faculty Advisor(s)
Dr. Oliver Lopez
Abstract
After going on the Warner Brothers Tour in December of 2015, I created a Gilmore Girls Instagram account. This account, which started off as a way for me to create edits of the show and post my photos from the tour turned into something bigger than I ever could have imagined. In just over a year I have over 55,000 followers. I post content including revival news, merchandise, and edits of the show that have been featured in Entertainment Weekly, Bustle, E! News, People Magazine, Yahoo News, & GilmoreNews.
I created a dataset of qualitative and quantitative outcomes from my posts from December 2015 to April 2016, and September 2016 to November 2016. This includes a total of 671 different posts. I am interested in analyzing data for each post including outcomes such as number of likes, number of comments, number of views, caption type, and type of post (video or picture).
My primary research questions are:
- Does the caption type affect the number of comments received?
- Does the type of post affect the overall interaction (the number of likes, comments, and video views) from my followers?
Exploratory analysis:
The overall trend based on likes and comments is that over time (as measured in days of week, month of year, and week of year), the account received more followers, and therefore showed an increase in likes and comments.
I will use statistical methods I learned in my Math 203 Introduction to Statistics course to describe the dataset and to conduct tests of hypotheses for each of my research questions.
Recommended Citation
Simmons, Brittany, "Gilmore Girls and Instagram: A Statistical Look at the Popularity of the Television Show Through the Lens of an Instagram Page" (2017). Student Scholar Symposium Abstracts and Posters. 236.
https://digitalcommons.chapman.edu/cusrd_abstracts/236
Creative Commons License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.
Included in
Applied Statistics Commons, Other Statistics and Probability Commons, Probability Commons, Statistical Methodology Commons, Statistical Models Commons, Statistical Theory Commons
Comments
Presented at the Spring 2017 Student Research Day at Chapman University.