Data analysis review with R studio preferably with the packages „tidyverse“ and „quanteda“. it to analyze the tweets of Donald Trump with the package „rtweet“ and make word clouds of his frequently used words and visualization in general. It is important to gather only the important data with which one can pose a scientific question. Also it would be important to include a visualization with ggplot and a sentiment analysis. And if possible maybe include a dictionary analysis with quanteda. It is not necessarily to use the twitter data from Donald Trump.
The Trump analysis you’re free to use any other social scientific question.
This is the important information on how the task has to look like. It should be about 6-8 pages long.
1. Introduction (1 page). Briefly introduce your research topic and what you are trying to do. End with a research question that is supported by the (extremely brief) literature review.
2. Data & Methods (2 pages). Describe the data you are using, and the cleaning, preprocessing, and analysis steps you took. This should give the reader enough information to replicate the analysis, but does not necessarily include all technical details like R packages used. For the anlaysis, also discuss the validity here: how do you know you're measuring what you're claiming to measure?
3. Results (2 pages). Show the exploratory and (if applicable) test results. Include relevant figures or tables.
4. Interpretation and discussion (1 page). What do your results mean? What are possible problems for this analysis, and/or ways to improve it? The report should be submitted as an R Markdown document. The layout is not important, but please make sure only to include only relevant figures and details.
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