When thinking about my data, I do not think there is a specific place where the tweets will be coming from because this is a topic that affects not only the people in America but people all over the world. People from everywhere are commenting on the issue of Islamophobia but if I had to chose I feel like a lot of the tweets would come from D.C. I feel like the tweets would be coming from the 40 degree latitude 90 degrees longitude. I feel like most of the tweets will be coming out of D.C. because this is a political issue and D.C. is the political capital in the US. I think that the latitude longitude of my home, Atlanta, would be around 30 degrees latitude and 90 degrees longitude. While I do not think there will be a lot, if any, tweets from Atlanta, I would think there would be some because Atlanta is a big metropolitan city with so many people. One would assume there would have to be someone in Atlanta commenting on major issues going on in the world.
I have 10 mappable tweets of my 20,482 tweets which means that only .0488% of my tweets can be mapped. Based on the reading from the Data Points, I feel as though a lot of my data underrepresents the people that are tweeting. I feel this way because I was only able to locate a few number of my tweets. This would make me believe that there are many people being unrepresented in this data. I do think that the data points I will be able to locate will be from many different places in the world which in some ways will give a clue as to where people are tweeting from because it will show the range of location. I think the majority of my tweets will come from the US. I have these thoughts because Islam is such a hot topic now a days with many people talking about the policies that are being put into place especially in the US. The tweets that I can geolocate are in english which does not shock me. Trump has put a Muslim Ban in place so it makes sense that people are tweeting in english which would imply that they are tweeting from America.
I do not really think I have big or small data, maybe just medium data. I think this because yes there are more than 10,000 tweets but I still feel like that does not necessarily make it big. There are people in the class that had so many tweets and so much data. The Boyd and Crawford article states that “the widespread belief that large data sets offer a higher form of intelligence and knowledge that can generate insights that were previously impossible, with the aura of truth, objectivity, and accuracy.” I find this myth to be true. I feel that in looking at my data you could say I have big data and therefore would have lots of information but I feel as though I do not have as much information as I could in terms of how many tweets I have. Within my group, I had the a medium amount of data. I was shocked to find that Katherine only had around 10,000 tweets because I feel like after the Women’s March and all the controversy around Trump’s policies that there would be more people tweeting #whyImarch. I think that my hashtag has more tweets than Katherine’s because the Muslim Ban in America has been fought by some lower level courts this week so I feel that has had an impact on why I had more tweets. Danny had a lot of tweets with #ObamaCare because there are so many questions about how this policy will play out with Trump
Looking at my maps, I do not see any patterns but I feel like that is because I only had 10 tweets to map. There are the majority of tweets that I could map come from the northeast. I think that this map is only telling some of the story and not grasping the full picture. I wish I had more geolocations because I feel that would have given me more of a story.
Kalamazoo Michigan 49001, Population Census in 2016
Kalamazoo, MI: Population of Black People in 1970
The population here in the Census Tract 6 is 3.924%
Kalamazoo, MI: Population of Black People in 1990
The population here has increased to 14.797%
Kalamazoo, MI: Population of Black People in 2010
The population here is 9.64%
The next geolocation I choose was Baltimore, MD the zipcode 21202
This is a map of the population from the 2015 census, I choose to look specifically at the census tract 501
Baltimore, MD in 1970: Population of Black People
The population of Black people in 1970 in census tract 501 was 98.463%
Baltimore, MD in 1990: Population of Black People
The population of Black People in 1990 in the census tract 501 was 98.067%
Baltimore, MD in 2010: Population of Black People
The population of Black People in 2010 in the census tract of 501 was 90.713%
When I went to the Social Explorer and began looking at the maps, I find it all to be very interesting. It was cool to see the census data so easily and also in a readable way. I looked at two locations from my map that I thought would show different populations. I originally wanted to look at the census in terms of religion but truth be told I could not figure out how to do that so I looked at Kalamazoo, Michigan and Baltimore, Maryland in terms of race. I choose to look at the census in race because I feel like Islamophobia is generally a racial issue where people are profiling purely based on looks. In the two places I looked the most accessible maps to look at were those that were related to population of black people. I found that in Kalamazoo while the black population was minimal there was a slight increase over the span of time. I feel like the fact that Kalamazoo is becoming more diverse may have to do with why tweets, even though it may only be one, are coming from this location. I also found that in Baltimore with a high population of black people that there was still a change in diversity over time even though it was the addition of more white people. While I do not think that this has much to do with my #Islamophobia, I do think that the diversity of places can show the willingness people have to be open minded or at least accepting of others. This may be a generalization and assumption but I feel like it could be true. Looking at these maps and this data did not give me a clear look at who was tweeting about Islamophobia because anyone of any race can be sharing tweets on this topic.
In the article, “Defining and Research Islamophobia” the author really divulges what Islamophobia means and how it came about. The opening sentences talks about how this concept really began in the 1990s. This article talks about since the 90s but more specifically since 2001 Islamophobia has been in media constantly. I found this article to be interesting because it talks about how there is not a generally accepted or clear definition of Islamophobia even though it is used throughout media constantly. I also found this article interesting in terms of last week’s labs because I had trouble finding articles on this topic from 2006. This article talks about how it has been a topic in the media for a while now and yet I had a hard time finding any articles on the topic. This article also looked into what it means to be Islamophobic. Overall, I found this article interesting because it gave a greater definition to my meaning of Islamophobia. The second article I choose was one called “Islamophobia and the ‘Privilege’ of Arab American Women”. I found this article to be interesting and relevant because it talks about how Arab men are often seen as the villains in American media while Arab women are not seen this way. More importantly though, the article discusses why this happens. Part of the reason this occurs is because Arab women are reluctant to push gender roles and so instead of addressing these issues they remain in their patriarchal system. This leaves Arab men victims within American society as well as Arab women victims within their own culture. There has also been a dominant view about Arabs in America that has been accepted as the norm following the 9/11 attacks. I found both of these articles to be interesting in different ways. Even though they do not have much to do with my mapping data, I found them very informative about how people view the Arabs in America.
Software-sorted geographies is use to describe how a person’s use of the computer is used to shape their lives and how networks are using this individualized information to make the internet filtered to the consumer. I feel like this idea is applicable to my data set because when using geolocation you will be able to see where people are more accepting of Islam and locations where people are not. By looking at people’s views and personal opinions on topics the internet is able to feed them media that would be appealing to them. While this probably is not a good thing especially in locations that are highly Islamophobic, software-sorted geographies will to be able to filter things based on your searches and interests.
Bleich, Erik. “Defining and Researching Islamophobia.” Review of Middle East Studies 46, no. 2 (2012): 180-89. http://www.jstor.org.ezproxy.trincoll.edu/stable/41940895.
Boyd, Danah, and Kate Crawford. 2012. “Critical Questions for Big Data.” Information, Communication & Society 15 (2): 662–79.
Elia, Nada. “Islamophobia and the “Privileging” of Arab American Women.” NWSA Journal 18, no. 3 (2006): 155-61. http://www.jstor.org.ezproxy.trincoll.edu/stable/40071188.
Graham, Stephen D. N. 2005. “Software-Sorted Geographies.” In The People, Place and Space Reader, eds. Gieseking, Mangold, Katz, Low, Saegert, 133-138. New York: Routledge.