Problem

Our college project required us to perform sentimental analysis on Twitter accounts using the Twitter API and R Studio. We faced several challenges during the project, including difficulty in accessing the Twitter API due to authentication issues and handling large amounts of data.

We also struggled with visualizing the data in a meaningful way that would accurately represent the sentiment of each tweet. It was important for us to find a solution that would allow us to overcome these obstacles and complete the project successfully.

Solution

To solve our authentication issues with the Twitter API, we used a package called "rtweet" which provided an easy-to-use interface for accessing Twitter data. This allowed us to easily collect large amounts of data from various Twitter accounts without any authentication problems.

To visualize the data, we used R's "ggplot2" package which helped us create visually appealing graphs that accurately represented the sentiment of each tweet. We were able to use this package to create bar charts, histograms, and scatterplots that made it easy for us to analyze and interpret our findings.

Impact

Successfully performed sentimental analysis on multiple Twitter accounts
Visualized data using R's ggplot2 package resulting in clear representation of sentiment analysis results
Increase in overall understanding of R programming language and its capabilities

Team

Team Member -
- Collected data from various Twitter accounts using rtweet package
- Analyzed data and performed sentimental analysis using R Studio
- Used ggplot2 package to create visually appealing graphs that accurately represented the sentiment of each tweet
- Cleaned and formatted data for visualization purposes

Twitter Sentiment Analysis with R Studio