Publications by Caitlyn Pierce
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T-test t.test(cont) ## ## One Sample t-test ## ## data: cont ## t = 42.713, df = 461, p-value < 2.2e-16 ## alternative hypothesis: true mean is not equal to 0 ## 95 percent confidence interval: ## 46.24179 50.70193 ## sample estimates: ## mean of x ## 48.47186 t.test(treat1) ## ## One Sample t-test ## ## data: treat1 ## t = 24.698, df = ...
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Example Data
#package needed library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union data <- read.csv("/Users/caitlyn/Desktop/Ipsos\ Misinformation\ and\ Conspiracy\ Theory\ Poll_\ De...
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Blog Post 2
Over the last two weeks I have thought more about how I want to frame my project. While still heavily interested in Twitter and tweets, I have moved toward creating a more define time frame, but admittedly I am still quite far away from a finalized research design. As of right now, I am thinking about using tweet reactions to major protests surro...
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Blog Post 1
For my project I am interested in individuals in highly policed communities react to social movements that impact them. Specifically, I am interested in how these individuals mobilize the law to advance the cause of the movement even when these individuals would otherwise avoid the law and law enforcement. For my current project, I am interested ...
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Blog Post 3
I continue my path toward hopefully figuring out the best way to study the question I am asking. After some thoughts and conversations with others about the feasibility of this project, I have decided to reign in my goals a little bit. Instead of looking over the entire 7-year period, and gaining all the tweets from that time, I have instead opte...
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Blog Post 4
library(quanteda) ## Package version: 3.2.1 ## Unicode version: 13.0 ## ICU version: 69.1 ## Parallel computing: 8 of 8 threads used. ## See https://quanteda.io for tutorials and examples. library(academictwitteR) I am not going to lie, I have had a very hard time trying to figure out how to pull the tweets. Despite the momentary success of the l...
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Blog Post 7
So for this I am just combining all of the different LDA models so I cann show/have results for each. It Calculating perplexity scores 2020 Data library(quanteda) ## Package version: 3.2.1 ## Unicode version: 13.0 ## ICU version: 69.1 ## Parallel computing: 8 of 8 threads used. ## See https://quanteda.io for tutorials and examples. data.20 <- rea...
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Blog Post 6
I am going to run the LDA model again with different numbers of topics. To start, I will use 5 topics. I will also do two rounds of preprocessing so that way I can remove any of the words that are not useful for analysis. library(quanteda) ## Package version: 3.2.1 ## Unicode version: 13.0 ## ICU version: 69.1 ## Parallel computing: 8 of 8 thread...
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Blog Post 5
Since the last blog post, I have collected all of the data that I will use. I decided to pull tweets (n=1000) from 5pm-6pm EDT each day for the period I specified in the last post. I ran into a few issues with missing data, so the days where that happened, I removed the data from the dataset. I ended up with 10310 tweets for the first period, and...
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