hanna-tes/South-Africa-election-monitoring-analysis-using-X-and-Facebook-data

**South-Africa-election-monitoring-analysis-using-X-and-Facebook-data** **Methodology** This analysis employed a range of tools and techniques: **Data Collection:** **X (formerly Twitter):** Data was collected using Meltwater, a social media monitoring tool. **Facebook:** Data was collected using Crowdtangle, a social media monitoring tool. **Data Processing & Analysis:** **Data Processing:** Python libraries such as Pandas, NumPy, and Scikit-learn were utilized for data cleaning, transformation, and feature engineering. **Sentiment Analysis:** The VADER sentiment analysis model was employed to analyze the sentiment expressed within the tweets. **Text Similarity Analysis:** Cosine Similarity was employed to measure the similarity between texts. **Visualization:** Matplotlib, Seaborn, and Altair were utilized to create informative visualizations, including sentiment distribution charts, and word clouds. This repository aims to conduct an in-depth analysis of the 2024 South African elections, leveraging data to understand election trends, voter behavior, and detect mis/disinformation from the trending narratives.