(Got a mail saying that we don’t have any class today)
Update!
The issue of sexual violence and crowd gatherings seemed unique to me and I have decided to focus my project on analyzing this specific combination. I’ll be looking into how often these events occur, the level of violence involved, and whether factors like crowd size and attacker groups influence the number of deaths.
Continuing from my earlier work with the ACLED dataset on political violence in India. I explored various patterns around protests and regional factors.
I came across a small set of events involving mob violence, sexual violence, and crowd gatherings. These events seem pretty serious to me , becuase they are often under reported. I will have to look more into this
I am working on the ACLED data Political Violence in India.The dataset includes information on regions, time periods, and factors affecting the violence. Right now I’m looking into how protest organizers, ruling parties, and political violence are connected in different regions.
The data is complex, with different regions and time periods. I’m now looking at whether protest organizers and the ruling party in each state are linked. I’m adding the ruling party to the data to see if it helps answer this question.
This week, we learned about the Poisson distribution, which helps us predict how often something happens in a certain time or place. We talked about using it with our datasets on political violence in India and the US.
After spring break, we had our first class. The professor gave us two new datasets: one for India and one for the US, both from ACLED about political violence.
Both datasets are from the Armed Conflict Location and Event Data (ACLED) organization and contain information on political and other forms of violence across these two countries.
This week, classes were on hold. I used the time to continue exploring Mathematica for data analysis. I had another question which I wanted to analyze: Is there a pattern in police shootings based on the time of day or location? Identifying trends in timing or geographic concentration could provide deeper insights into these incidents.
As part of my ongoing efforts to analyze data for my journal, I’ve recently started learning Mathematica, a tool recommended by the Professor. I am still gathering information regarding my previous questions : Which States have made it mandatory for the police to use the body cameras?
I started analysing the data again, this time noting down all the answers, even the most basic ones like: Which state has the highest shootings? Which day has the most shootings?. By answering all the basic questions, I can slowly progress into more detailed analysis which will help me in finding my objective.
I was analyzing the data, using a bunch of filters, and I noticed that more than 82.75 % of the cops had their body cams off. I also had some questions.