nihapola/Dynamics-of-Political-Violence-and-Media-Coverage-in-Nigeria-A-Data-Driven-Approach

A data-driven analysis of political violence in Nigeria (2022-2023) using R. Explores event types, actors, hotspots, and news sentiment to reveal conflict dynamics and media influence. # Dynamics-of-Political-Violence-and-Media-Coverage-in-Nigeria-A-Data-Driven-Approach A data-driven analysis of political violence in Nigeria (2022-2023) using R. Explores event types, actors, hotspots, and news sentiment to reveal conflict dynamics and media influence. **Project Overview** This project delves into the intricate landscape of political violence in Nigeria for the years 2022 to 2023, alongside a comprehensive analysis of concurrent news coverage. Utilizing data cleaning, aggregation, sentiment analysis, and correlation techniques, this study aims to decode patterns of violence, identify key actors, geographic hotspots, and contrast these findings with the thematic and sentiment trends in media reporting. **Objective** To provide a holistic view of the political violence landscape in Nigeria and its reflection in the media, highlighting the dynamics of conflict and the media's role in shaping public perception. **Data Sources** 1. Nigeria ACLED Export.csv: Contains detailed records of political violence events. 2. Nigeria News EMM Export.csv: Comprises news articles related to political violence. **Tools and Technologies** 1. Programming Language: R 2. Key Packages: - ggplot2: For creating advanced visualizations. - dplyr, tidyverse: For data manipulation. - lubridate: For handling date and time data. - viridis: For color mapping. - rnaturalearth, rnaturalearthhires: For mapping global data. - sf: For handling spatial data. - leaflet: For interactive maps. - htmlwidgets: For rendering HTML widgets. - readr: For reading CSV data. - syuzhet: For sentiment analysis. - tidytext: For text mining. - wordcloud: For generating word clouds. - RColorBrewer: For color palettes. - grid: For enhancing grid graphics. **Methodology** Data Cleaning and Preparation: Standardizing text columns, filling missing values, and converting date columns for better analysis. Political Violence Profile Analysis: Aggregation of data to identify event types, actors, and geogra …