KXL has no home

PART I

I first expected that there would be a lot of tweets associated with #KeystoneXL would be tweeted from Washington, D.C. as the issue continues to be a hot debate in politics with Trump’s advancements of the project. I also expected there would be a lot of tweets from national or local environmental organizations concerned about the implications the project would have on our atmosphere and natural resources, or from the native american reservations that would be also impacted. Thus, given the issue is largely centered in North America, I expect to see most of the tweets related to the issue within 0 to 90 degrees latitude, west of the prime meridian, and 0 to -90 degrees longitude above the equator. With my hometown located just below Washington, D.C. in northern Virginia, I suspect its coordinates are around 50 degrees latitude and 115 degrees longitude. I wouldn’t be surprised if there were a couple of tweets originating from this area as many politicians live within this area or north of the potomac in Bethesda, Maryland.

PART II

Out of a total of 6,240 tweets related to the #KeystoneXL, none contained geo coordinates. However, Jake Bennet’s #Energy found a total of 56,007 tweets where 1,032 contained geo coordinates, calculating 1.84% of the tweets can be mapped. Considering my own data I believe that it under-represents a large population of people that would be impacted by the extension of XKL, such as the various American Indian reservations within the Dakotas and Nebraska. Instead, a lot of my data reflects political advancements in the project, news articles carrying the debate of the project’s pros and cons, and some environmental organizations’ opinions. However, Jake’s data found on #Energy seems to over-represent varying populations whom are concerned with energy in many different facets, creating a data set that contains a broad range of issues and applications of energy forms that people are impacted by everyday. A large majority of Jake’s #Energy tweets are located varying around 40 to 42 degrees latitude and range between 0 to -90 degrees longitude. This would place a lot of the tweets that have been mapped within the United States, presumably because there are a lot of controversial issues circulating the nation regarding the source of energy, its extraction and uses, as well as its applications. The language mainly used is english, which is not surprising, however there were a number of different languages utilized, indicating the topic to a globally relevant and fluctuate meaning in order to express ways that life can be healthier and enriched for individuals and society.

Personally, I don’t think that I have “big data” in the physical sense, but as Boyd and Crawford mention “big data is not always better data” (get actual citation). Given the smaller amount of data I have on XKL relative to other team members, or generally the class, I think my data stays well grounded in its real time debate and brings together different communities to generate a context that can be seen in just the numbers. I would say that Jake’s data collected for #Energy definitely qualifies as “big data” regarding its volume, however it seems to reach many broad levels of issues related to energy where it makes it difficult to be kept within its context. People within my hashtag team have collected far more data that I have for #KeystoneXL, however I believe that the hashtag is pretty centered on this specific issue and is not as broad, but also is in a lull period given the political events circulating the topic and will grow in popularity as more is done on the project.

PART III

 

The above map was created to illustrate the concentration of tweets that originated in common areas related to #Energy throughout time. Using the torque feature allows the data scraped from Twitter on #Energy to be visualized almost as if it was happening real time. I put steps at 130 and the duration set to 25, I also changed the color of the dots to blue to make the denser regions more visible with the light blue starkly overlapping. Generally, it appears that the topic of #Energy is centered within the United States, being more dense in California and Colorado. However, there are a number of tweets coming from Alberta, Canada and Bogota, Columbia, as well as some areas within the United Kingdom. I was expecting and hoping to see more tweets originating from areas where the Keystone pipeline already exists. As well as where the XL project is forecasted to run, like in South Dakota, Montana or Nebraska. While the Washington D.C area is highlighted on the map, I was hoping it would be denser considering that many changes in the nation’s energy goals is being debated currently. Overall, this map reveals that related to the topic of energy, there is a high concern within the United States however this visual lacks what about energy is so specifically concerning. Therefore, this map does little justice in explaining and qualitatively show the context and meaning of the data related to energy and its reasons for growing concern within Twitter.

PART VI

While the data collected from Jake’s #Energy didn’t seem to reflect much related to the Keystone XL project geographically, I decided to look at regions that would be heavily impacted by the pipeline’s expansion. A main argument for the construction of the pipeline is that it is expected to provide many jobs, however a counter-argument is that the project will provide many temporary jobs. Thus, I filtered the data table to view the percentage of unemployed American Indian and Alaskan Native 16 years or older civilians in the labor force. In looking at zip code 57621 you see Bullhead District, one of the eight districts in the Standing Rock Reservation within Corson County, South Dakota. Given the Keystone XL project is predicted to provide employment, I research the unemployment rates for American Indians within the reservation’s county in South Dakota to understand if the trend of unemployment would be maintained or changed.

2010: Corson County, SD 57621

From census tract 9410, out of 238 American Indian and Alaska Native 16 years old or older civilians, 64 are unemployed, calculating 26.89% of the total labor force in Corson County. Where census tract 9411 of Corson county reports 208 out of 641 are unemployed, calculating 32.45%.

1990: Corson County, SD 57621

From census BNA tract 9861 its found that 183 out of a total of 530 American Indian, Eskimo, and Aleut civilians 16 years and older within Corson county are unemployed, calculating 34.53%.

1970: Corson County, SD 57621

Unfortunately, Corson county wasn’t represented in the census tracts in 1970 related to American Indian population or unemployment from insufficient data.

The other location I researched was Roberts county, South Dakota with a zip code 57224 where the Lake Traverse Indian Reservation resides and the existing Keystone pipeline runs through.

2010: Roberts County, SD 57224

From census tract 9407, out of 137 American Indian and Alaska Native 16 years old or older civilians, 16 are unemployed, calculating 11.679% of the total labor force in Roberts county. Where census tract 9408 of Roberts county reports 190 out of 785 are unemployed, calculating 24.204%.

1990: Roberts County, SD 57224

From census BNA tract 9501 its found that 18 out of a total of 127 American Indian, Eskimo, and Aleut civilians 16 years and older within Corson county are unemployed, calculating 14.173%. From census BNA tract 9503 its found that 75 out of 363 of the American Indian, Eskimo, and Aleut civilians in the labor force are unemployed, calculating 20.661%.

1970: Roberts County, SD 57224

Unfortunately, Roberts county wasn’t represented in the census tracts in 1970 related to American Indian population or unemployment from insufficient data. Overall, the census maps focusing on Roberts county containing a different Native Indian reservation that has been impacted by the existing keystone pipeline shows a growing rate of unemployment within their population since the 1990’s, whereas in Corson county the unemployment rate of Native Indians has decreased, although minimally, since the 1990’s. This is interesting as the keystone pipeline is argued to provide jobs and instead it seems that it hasn’t made much of a difference in supplying work to those in Roberts county impacted by the pipeline. This raises the question of whether it will have the same affect within Corson county if the project is approved and begins construction through South Dakota.

PART VI

The article “The Green Room: Tar Sands and the keystone XL oil pipeline” by Amanda Beckrich outlines the many different applications of crude oil utilized as a global energy supply. The author, being an environmental science teacher, notes that as our natural resources are running out and turning to tar sands provides a different opportunity to acquire global energy supply in an achievable means. Thus with the keystone XL pipeline proposed and originating in Alberta, Canada containing approximately 75% of the planet’s tar sands deposits that will be transported into the US and raise the current 10% we currently acquire from this source. While Beckrich notes that there are environmental concerns and debates regarding the native american indian reservations, she does little to expand on these concerns on a personal level. I find this article interesting as not only a perspective from an environmental enthusiast who seems to support the overall goals of the pipeline extension in terms of global energy supply, but also learn that with such a large concentration of deposits in Alberta and question how this shapes and pressures the arguments for the extension. Another article “Kelo’s Influence on Keystone Pipeline Asks ‘Where’s the Public Purpose?’ by Jeffery Kleeger asks the question in light of the Kelo vs. City of New London verdict where land can be obtained from individuals in line of the project’s expansion “for the purpose of economic development.” Kleeger goes on further explaining the public opinion where dispossession of own property “in favor of commercial development, is offensive to personal autonomy.” I find this article especially interesting as Kleeger delves into the projections of taking this argument to turn back the forward movement the project has made and ends up surmising that even such an attack on the idea of public use requirement is not enough. All in all, Kleeger’s article offers a fresh perspective from those that would be directly impacted by KXL in a way that is more personal than what I have seen from my Twitter data. Furthermore, there is a lot of deep-rooted controversy within the areas directly impacted by the extension of the pipeline regarding personal property and intervening of local environments and natural resources, for the national commercial and economical gain.

Graham references software-sorted geographies to explain how an individual’s decision-making and life plan is more controlled by computer technologies than otherwise realized. In relation to my data I can see how different was of media persuasion can be applied to regions where the topic of KXL is on one side or the other, and further the community’s response to those methods to explain events of protest. I think the data collected speaks a lot to the struggle America balances with the greater benefit for all or the moral question of sacrifice for a particular group.

WORKS CITED

Boyd, Danah, and Kate Crawford. 2012. “Critical Questions for Big Data.” Information, Communication & Society 15 (2): 662–79.

https://tyday822.carto.com/builder/c156fa3c-f528-11e6-8226-0e233c30368f/embed

Standing Rock Sioux Tribe,. (2017). Environmental Profile. Standing Rock. Retrieved 18 February 2017, from http://standingrock.org/environmental-profile/

Beckrich, A. (2012). The Green Room: Tar Sands and the keystone XL oil pipeline. The Science Teacher, 79(9), 10-10. Retrieved from http://www.jstor.org.ezproxy.trincoll.edu/stable/43557595

Kleeger, J. (2012). Kelo’s Influence on Keystone Pipeline Asks “Where’s the Public Purpose?” The Urban Lawyer, 44(3), 719-741. Retrieved from http://www.jstor.org.ezproxy.trincoll.edu/stable/24392325

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.