/police-brutality-data-analysis

In this project, we analyze the events after George Floyd’s death. The protests and riots across the United States and sentiments of news articles of three different news sources that have different political leaning. We will see how these media reacted after Floyd’s death and see the effect of media bias on the sentiments of news for #BlackLivesMatter and #AllLivesMatter movement. We will also see if there is a correlation between the police budget and the number of protests. This analysis will help us to see if there is really a need for defunding police to reduce police brutality and casualties. We will also see the correlation of partisan segregation and number of deaths to see if political preference has an effect on the number of deaths by police.

Primary LanguageJupyter Notebook

Data Analysis and Sentiment Analysis on Police Brutality

Police Brutality is the use of unnecessary force against civilians. It is one of the major issues in America and the number of unarmed deaths by police is increasing annually. Police Brutality has been a hot topic discussion in recent years with the #BlackLivesMatter and #AllLivesMatter movement, and the publication of articles on news websites. Since the death of George Floyd on May 25, 2020, protests, riots and debates have emerged on the public and news media. Police officers and law enforcement have been under public scrutiny for using excessive force and violence when handling suspects and civilians. People are speaking out against such police brutality and systematic racism that caused deaths of George Floyd, Ahmaud Arbery and thousands of violent incidents that happened to black people through movements like Black Lives Matter. However #AllLivesMatter is a movement that has come to be associated with criticism of the #BlackLivesMatter movement. The movement ignores the systematic racism that black people face by arguing that all lives are equal because we all are human beings.

At the end of May, after Floyd’s death there were major protests that were held in cities and towns across the United States. These protests and movements were covered by different news sources. It has been proved that there is a presence of media bias on news sources based on their political leanings. It will be really interesting to analyze the sentiments of articles for #BlackLivesMatter movement and #AllLivesMatter movement which is a counter-movement to #BlackLivesMatter for different news sources. Also, there are debates and discussions on defunding and demilitarizing the police department to reduce police brutality and civilian death in protests.

In this project, we analyze the events after George Floyd’s death. The protests and riots across the United States and sentiments of news articles of three different news sources that have different political leaning. We will see how these media reacted after Floyd’s death and see the effect of media bias on the sentiments of news for #BlackLivesMatter and #AllLivesMatter movement. We will also see if there is a correlation between the police budget and the number of protests. This analysis will help us to see if there is really a need for defunding police to reduce police brutality and casualties. We will also see the correlation of partisan segregation and number of deaths to see if political preference has an effect on the number of deaths by police. The research questions that we will investigate on this report are:

(RQ1) What relation is there between the sentiments of news articles and political leaning of news sources?
(RQ2) What correlation is there between the police budget and number of protests?
(RQ3) What correlation is there between the partisan segregation and the number of deaths by police?

We strongly recommend you to read a complete report on our analysis and findings along with the Methodology section on how to use this repo here.

Some output results

Protest movements across US (May 25-July 31, 2020)

Word cloud obtained from CNN Articles

Word cloud obtained from CNN Reuters

Word cloud obtained from CNN Fox