SMI205 Preregistration form

1. My replication project

This is a preregistration of an extension project for the following study:

The paper chosen for the replication project aims to understand the impact of social media and its affect towards trust in the Government in 2012 and 2016 (considering the democratic party occupied the White House for both years). The paper uncovers how polarization politically compare for each party whilst controlling for other factors such as news consumption and demographic

Down below is the reference paper and DOI:

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Klein, E., & Robison, J. (2020). Like, post, and distrust? How social media use affects trust in government. Political Communication, 37(1), 46-64.

doi number: https://doi.org/10.1080/10584609.2019.1661891

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In my replication project I am focusing on the following argument made in the study:

• Claim: “We expect a positive realtionship between this variable and our measure of distrust, i.e. increasingly favourable views toward the Republican Party realtive to the Democratic Party should be associated with increasing distrust given that a Democrat occupied the White House in both 2012 and 2016” (page 6)

• Display item:

figure

2. Planned project extention

2.1. Rationale for new hypothesis

Holt et al. find the describe the significance of social media affecting political interest based on age. The understand social media usage will depend widely on age which in turn can shape people’s political interest. Whilst Holt et al does acknowledge motivations of social media vary between age, they can have a heavy impact and influence on societies political views. The data consisted of Swedish elections (similar to the ANES) and through OLS regression models found younger people shared less interest in politics than older people but found statistically significant results showing social media impacts all ages groups political interest.

2.2. Prediction

Hypothesis: Based on Holt et al’s findings, I will therefore look at how age can impact polarization between both political parties. I expect that the results will include somewhat similar conclusions however, including age as a seperate variable will give this paper a further developed understanding. Considering a Democrat occupied the White House in both years I expect that distrust in the gov. will increase as democrats get older but decrease as republicans get younger

3. Data

In this project I will be using the same data from the original paper (American National Election Studies) including data from the 2012 and 2016 studies

• Data can be found on the Open Science Framework website here. As previously mentioned this includes data from covering two years. On the OFS website there was a cleaned version of necessary variables here which can be downloaded.

4. Data analysis plan

4.1. Model specification

I will test the hypothesis using the same regression model applied in the study- OLS regression.

4.2. Variables

Dependent variable(s):

• Trust in Gov. (trust_index )

Independent variables (IVs):

• party attitudes
• social media usage
• news consumption
• financial condition
• presidential approval
• age as a new separate variable
• political perference

As mentioned in the paper, the dependent variable consists of four items regarding trust on gov. which was then scaled from 0-1.

• A higher score means greater distrust
• A lower score means less distrust

variables have been scaled from 0-1

4.3. Interference criteria

will use the standard acceptance of a p-value greater than 0.05 as being unacceptable and discarded

4.4. Data exclusion

Outliers will be included. No checks will be performed to determine eligibility for inclusion besides verification that each respondent answered questions

4.5. Missing data

If three of more of the questions are unanswered from the survey, they will be removed from the analysis

4.6. Exploratory data anlysis

potentially looking for differences in polarization depending on party preference and age

Example: We expect that certain demographic traits may be related to attitudes to migration. Therefore, we will look for relationships between demographic variables (such as age, gender, income) and the attitudinal measures.

5. Session info

This preregistration form was completed in the following R environment:

## R version 4.2.2 (2022-10-31 ucrt)
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##  [1] digest_0.6.31   R6_2.5.1        jsonlite_1.8.4  evaluate_0.20  
##  [5] cachem_1.0.7    rlang_1.0.6     cli_3.6.0       rstudioapi_0.14
##  [9] jquerylib_0.1.4 bslib_0.4.2     rmarkdown_2.20  tools_4.2.2    
## [13] xfun_0.37       yaml_2.3.7      fastmap_1.1.1   compiler_4.2.2 
## [17] htmltools_0.5.4 knitr_1.42      sass_0.4.5

6. References

Holt, K., Shehata, A., Strömbäck, J. and Ljungberg, E., 2013. Age and the effects of news media attention and social media use on political interest and participation: Do social media function as leveller?. European journal of communication, 28(1), pp.19-34.