Rationale

Agenda setting des cribe the ability to influence placed on the topics of the public agenda. This theory suggests that the media has the ability to shape public opinion by determining what issues are given the most attention.

In this experiment, 600 frequent Fox News and CNN viewers were pulled for a larger national survey conducted in September of 2023. The survey asks “What is the most important problem facing the U.S. right now?”, and categorized all the answers following which outlet they aligned with most. Within this study, immigration was focused on as the main variable, measuring whether immigration as a topic was mentioned as the most important problem among viewers.

Within the agenda setting theory, it is believed that due to the salience of Fox News to its viewers, it would be expected that the Fox News viewers would say immigration would be one of the top issues in the country, whereas CNN viewers would not find immigration as important.

Hypothesis

The analysis tested the hypothesis the 600 frequent viewers of Fox News and CNN would answer Immigration or different to the question of “What is the most important problem facing the U.S. right now?”

Variables & method

The categorical variable named “1 top issue” measured when the participants gave Immigration as the most important problem in the United States. The categorical variable named “2 Not Top issue” indicated when viewers reported something else as the most important problem the country was facing. The analysis gathered the data of which news outlet the participants were viewing, Fox News or CNN. The analysis treated, “immigration” as the dependent variable and the “preferred network” was treated as the Independent variable, and the Chi Square Test was used to evaluate the hypothesis.

Results

First, the analysis examined whether the participants were frequent viewers of CNN or Fox News. The participants were asked “What is the most important problem facing the US right now?” Viewers of Fox News answered immigration as the biggest issue in the country by 38.3% . Meanwhile, of frequent viewers of CNN only 11.7% answered immigration as the most immportant issue facing the US right not. 88.3% of CNN viewers answered other when asked what the most important issue facing the US right now compared to the 61.7% of the viewers of Fox News that also answered other. The findings suggest that due to the salience of Fox News to its viewers, it would be expected that the Fox News viewers would say immigration would be one of the top issues in the country, whereas CNN viewers would not find immigration as important. These findings suggested a chi-square test would be suitable for the analysis, as planned.

The test found the difference between viewer results to be statistically significant, X2 (1, N=600) = 55.48, p<0.5. The results suggest that more Fox News viewers answered immigration as the biggest issue in the US compared to those who watch CNN.

Analysis code and output

# Read the data from the web
FetchedData <- read.csv("https://drkblake.com/wp-content/uploads/2023/09/TopIssue.csv")
# Save the data on your computer
write.csv(FetchedData, "TopIssue.csv", row.names=FALSE)
# remove the data from the environment
rm (FetchedData)

# Installing required packages
if (!require("tidyverse"))
  install.packages("tidyverse")
if (!require("gmodels"))
  install.packages("gmodels")
library(gmodels)
library(ggplot2)

# Read the data
mydata <- read.csv("TopIssue.csv") #Edit YOURFILENAME.csv

# Specify the DV and IV
mydata$DV <- mydata$Immigration #Edit YOURDVNAME
mydata$IV <- mydata$PreferredNetwork #Edit YOURIVNAME

# Look at the DV and IV
ggplot(mydata, aes(x = IV, fill = DV)) +
  geom_bar(colour = "black") +
  scale_fill_brewer(palette = "Paired")

# Make the crosstab table
CrossTable(
  mydata$DV,
  mydata$IV,
  prop.chisq = FALSE,
  prop.t = FALSE,
  prop.r = FALSE
)
## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## |           N / Col Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  600 
## 
##  
##                 | mydata$IV 
##       mydata$DV |       CNN |       Fox | Row Total | 
## ----------------|-----------|-----------|-----------|
##     1 Top issue |        35 |       115 |       150 | 
##                 |     0.117 |     0.383 |           | 
## ----------------|-----------|-----------|-----------|
## 2 Not top issue |       265 |       185 |       450 | 
##                 |     0.883 |     0.617 |           | 
## ----------------|-----------|-----------|-----------|
##    Column Total |       300 |       300 |       600 | 
##                 |     0.500 |     0.500 |           | 
## ----------------|-----------|-----------|-----------|
## 
## 
# Run the chi-squared test
options(scipen = 999)
chitestresults <- chisq.test(mydata$DV, mydata$IV)
chitestresults
## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  mydata$DV and mydata$IV
## X-squared = 55.476, df = 1, p-value = 0.00000000000009463