Los Angeles Houston Kansas City
The topic of this research lab is the sentiment of guns in various American cities based on their stance on gun policies. The search was conducted 3 times on 3 different cities. The parameters used in this search are search_words, location, and date_since. For the search_words parameter I used "guns", the coordinates for Los Angeles, Houston, and Kansas City and 25.0 miles as the radius for the location parameter, and "2023-1-16" for the date_since parameter. Searching for the term "guns" makes sense to me because it is the weapon that is being debated. Los Angeles in California supposedly has high gun control, Houston in Texas and Kansas City in Missouri supposedly low gun control. The 25 mile radius is because it is generally the length to reach the outskirts of the city from the center. The date "2023-1-16" is because the twitter api limits users to fetch tweets from the last 7 days.
The reason for this comparison is because gun violence is a hotly debated political issue in the United States and the country continues to be affected by gun violence. Just today (1/22/2023) there was a mass shooting in Los Angeles so the topic is more relevant than ever. Each state has different gun control policies and overall sentiments on the right to bear arms. It would be interesting to compare the sentiments of guns in cities with different levels of laxness in gun control. The level of laxness was selected based on criminalattorneycincinnati.com. There are politically left leaning and right leaning states where the cities are located that could be represented in this comparison.
The biggest word for all 3 word clouds is "People". Words like "people", "law", "know", "kill", "don", "ban", "go", "shoot", "more", "use", "out" are all medium to big size in all 3 word clouds. All 3 word clouds have small "right". Los Angeles's cloud contains a large "mass" whereas the Kansas City cloud contains "school". The word clouds for Kansas City and Houston has small "protect" (large in texas but small in Kansas City), large "kid", and small "buy". Kansas seems to be the only one with words like "Ericareport" and "Youtube". There are many other comparisons that could be made but I only listed a notable few. Most words seem to be shared between the 3 word clouds with some minor differences in sizes and words.
The biggest word being "People" in all 3 clouds could possibly be from describing victims, themselves or people from opposing side of gun control. Common words that are medium to large size between all 3 word clouds such as "people", "law", "know", "kill", "don", "ban", "go", "shoot", "more", "use" might be from discussions about the gun control laws. I can see the word "don" being an error from the word "don't" in which case could be people said guns don't kill people and that people kill people. "out" might just be taken from "figure out" wondering what to do or "about" from "how about" pointing out hypocrasy against their stance. The term "Right" found in all clouds might from talking about gun rights, arguing both sides. The "mass" in LA and the "school" in Kansas City could be showing the type of shootings that are taking place in the area recently. The "protect" in Kansas City and Houston could be people explaining how guns are used for self defense since they are gun friendly states, the "kid" could be describing the victims or perpetrators of shootings, and the "buy" could be because of how popular it is to purchse guns in their states. Additionally, "kid" could be a way that people on twitter talk about young people. Kansas City's "Ericareport" and "Youtube" are unique to their word cloud. Ericareport is a prominent democrat on twitter and its presence could be because a lot of Kansas City Twitter users are disagreeing with her ideas on gun control. "youtube" could be where they get their news from or evidence to back up gun friendliness.
A way that my research could be improved in the future is by using a larger dataset of tweets if possible. The twitter api limited my searches to within the last 7 days, if a certain day could be accessed I would select a date that a major mass shooting occurred to get stronger stances on the topic. The research could also account for biases, perhaps people that are pro gun control use twitter more than the anti gun control group. Additionally, people that live in urban areas might have different opinions than people living the suburbs.
Anything you find from the map or data that is different from your expectation before the exercise, or anything that stands out to you
I found that the word cloud does not really accurately depict the sentiment of guns from the dataset. The word clouds does not show a definite stance on the topic between the three cities whereas the csv data could sort of make out a stance. Most words seem to be shared throughout these cities despite their difference in gun control sentiments. The contexts of the tweets were also not what I expected, in the los angeles csv there were a lot of tweets that were not related to gun violence but things like video games.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent