1. I expect to see a lot of people tweeting about #energy mainly in the United States.  Since I can only understand the English tweets that does limit me to reading some tweets.  But that should not inhibit me from seeing the location of my tweeters.  I think I will see a lot of tweets from the US, but also a good global representation because #energy is a global issue. It has to do with the well being and longevity of our planet.  My hometown will not be tweeting about #energy and the longitude and latitude 45N, 74 W.  I expect to see the most tweets at 52 N 1 W.

Total Tweets: 56,007

The percentage of tweets that I can map is 1,131 out of 56,007 tweets, which is 2.01% of my tweets can be mapped.  My data can over represent or under represent a certain population by following a group that are internet able.  Places where data can be used from any location, like the United States, UK, internet rich countries where they have the means to tweet about #energy and be educated on the matter.  Energy is a topic that requires proper reading and study of the field to be able to tweet or write about it.  The majority of my tweets are coming from a 29 N location.  Which happens to be in Texas near the gulf of Mexico, the site location of the BP oil spill.  It is really interesting that the majority of my geo location tweets are coming from Texas.  I thought Texas loved its oil and did not want to see it go away. I have a lot of “en” written in the language columns and that there are some other languages mixed in.  Like I have a lot of “en-gb” which I believe is Great Britain English, meaning it came from the UK.  That the UK is really tweeting about #energy and the USA is.  The languages that are missing from #energy are Asian dialects, there is 1 Japanese, no Chinese or Korean.  It is a massive part of the world that is missing from my data.

 

I do not think that I have big data.  My tweet locations do not span over a global scale.  There are too limited to specific locations.  I believe that I could have big data, but I could only draw that conclusion as my data collection goes on and that I am able to pull from more geo locations.  Knowing the location of only 2% of my tweets does not give me nearly enough evidence. Crawford and Boyd write, “We define Big Data as a cultural, technological, and scholarly phenomenon that rests on the interplay of: (1) Technology: maximizing computation power and algorithmic accuracy to gather, analyze, link and compare large data sets. (2) Analysis: drawing on large data sets to identify patterns in order to make economic, social, technical, and legal claims.  (3) Mythology: 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.” (Crawford, Boyd, pg. 663).  That I do not have big data due to the analysis part of the definition.  I have not yet been able to identify a pattern in my data or make a claim about it quite yet.  Perhaps during our next lab I will have enough data to make a claim.

 

Tyler: 6,000ish

Graham: Sick from class

Taylor: no reply

I can only really draw a conclusion from Tyler and the information she gave me.  I have a lot more tweets than Tyler.  #KeystoneXL is on a much smaller scale in terms of twitter broadness #energy covers a lot of areas from global awareness and global warming down to putting a banana in your body for energy.

 

https://jakeandbake0824.carto.com/builder/3e41bfc8-f5f1-11e6-ae72-0e3a376473ab/embed

The design behind my map is I wanted to show how #energy was being discussed globally. This is an issue of the planet, not just one country like a #makeAmericanGreatAgain hashtag that only pertains to the United States.  This is a global issues I wanted to show that people in New York City, London, Deer Park Texas, Africa, Asia are all tweeting about the same global crisis.  Literally the entire world is tweeting about #energy.  My map tells the story of how people who do not even speak the same language are talking.  They are talking about our global energy crisis and ways it can been rectified.  That this is not a singular country issues that can be solved by government policies and “support.”  Action needs to be taken by every country in the world to find a new sustainable energy source to replace fossil fuels. I take away from my maps that all of the orange dots needs to work together for a common goal, they do not need to be individuals talking about the problem.  They, like the countries of the world, should be talking together, pooling resources to find a new clean type of energy.

1. Location Examination:

USA: Deere Park, TX (right outside Houston) 77536 Zip Code.

Deer Park Texas: Examining Age, income and race.

Deer Park Texas, (Red dots = those citizens below the age of 45 years old).

 

 

 

 

 

 

 

 

 

 

Deer Park Texas, (Red Dots = those households with an income below 15,000 annually)

 

 

 

 

 

 

 

 

 

Deer Park Texas, (Red dots = citizens who identify as white only (90%)).

 

 

 

 

 

 

 

 

 

 

 

 

Deer Park TX (Income below 15,000 annually in 2010 7.19%)

 

 

 

 

 

 

 

 

Deer Park TX (Income below 15,000 annually in 1990 6.76%)

 

 

 

 

 

 

 

Deer Park TX (Income below 3,000 annually which is equivalent to less that 15,000 today in 1970 0.19%)

 

 

 

 

 

 

 

 

 

2. Location Examination:

USA: Sana Monica, CA: 90405 zip code

Sana Monica, CA examining Race, income and age.

Sana Monica, CA (Red Dots = residents under the age of 45)

 

 

 

 

 

 

 

 

 

Sana Monica, CA (Red dots = Residents with an income below 15,000 annually)

 

 

 

 

 

 

 

 

 

Sana Monica, CA (Red Dots = Residents that identify as white only)

 

 

 

 

 

 

 

 

Sana Monica, CA (White Residents in 1970 79.3%)

 

 

 

 

 

Sana Monica, CA (White Residents in 1990 71.8%)

 

 

 

 

 

 

Sana Monica, CA (White Residents in 2010 82.96%)

 

 

 

 

 

 

3. Location Examination

USA: New York, NY: Zip Code: 10001 examining  Age, Race, and Income.

New York, NY (Red dots = Residents under the age of 45)

 

 

 

 

 

 

 

New York, NY (Red dots = Residents with an income below 15,000 annually)

 

 

 

 

 

 

 

 

New York, NY (Red Dots = Residents that identify as white only)

 

 

 

 

 

 

 

 

 

 

New York, NY (White Residents in 2010 68.98%)

 

 

 

 

 

 

 

 

 

 

 

New York, NY (White Residents in 1990 72.73%)

 

 

 

 

 

 

 

 

 

New York, NY (White Residents in 1970 86.32%)

 

 

 

 

 

 

 

 

 

 

 

When we look at #energy age has a massive role in who is tweeting about it.  I found it very interesting that there were three tweets from a small Texas town called Deere Park about 20 miles outside of Houston and another 20 miles from the Gulf of Mexico.  Who played host to the worlds largest oil spill just a few years ago.  Texas stereo typically has always been about that drill baby drill, with pop culture references of the average Texas home having an oil rig in their back yard.  I found it fascinating that people in this small town were tweeting about clean renewable energy.  If we look at the census from 2015 in Deere Park, TX, we see they have a population of 32,521.  With 27.6% of their age population falling between the ages of 25 and 44 years old.  According to statistica.com, a website that sources 18,000 statistics, says that the 42.2% of twitter users fall between the ages of 25 and 44.  The statistics were taken at the same time as the 2015 Deere Park, TX census.  That a large part of the Deere Park population will be in the same range as twitter users.  Those middle aged folks from Texas are also the age range that cares about the environment and sees the issues of global warming and how it is negatively affecting our planet.  That through witnessing the bp oil spill it make Texas people realize that it was a time for change to green renewable energy.  Deer Park Texas is also fairly weathly in the sense that they can all afford the internet.  With poverty line being around 15,000 a year lets say for this map purpose, only 5.8% of households are living below the poverty line.  That is a pretty strong percentage meaning that data and twitter is readily available to the majority of the Deer Park citizens.  Deer Park is also an incredibly white area where 90% of the residents are white alone.  With a 1.8% population of black residents.  This is an extremely white area meaning that people around there are not tweeting about #BLM and other racial issues.  The major problem there is global warming with the heat as so many energy companies work out of Texas and in the Gulf of Mexico. I wanted to look at the income history of Deer Park Texas to see if it could tell me anything about oil money in Texas.  It really did in 1970 the poverty line was less that 3,000 annually, in Deer Park only 0.19% of households were below that poverty line, making Deer Park a very wealthy area.  Spiking most likely due to oil and other fossil fuels in the Gulf of Mexico and Texas area.  So the elders, people above 45 who are not tweeting grew up loving fossil fuels cause it made them rich in that part of the world.  Today they are not as rich as they once were looking for a new type of energy to be produced down by the Gulf of Mexico so that their town can become wealthy again.

As I said above age is major factor that comes into who is tweeting about #energy.  In a place like Sana Monica California, tweets about clean renewable energy are of a surplus.  Cali is the tech hub of the world with places like Silicon Valley, that has played host to the massive tech boom in the world.  That they are always looking for clean new sources of energy.  In Sana Monica 33.5% of residents fall within the age range of 25 to 44, with roughly 20% of it’s population below the age of 14.  That is a massive amount of people who have grown up with social media.  Understanding how it works and being introduced to apps like twitter during its founding.  The majority of the Sana Monica population falling in that 25 to 44 window of average age of twitter users.  Sana Monica has a huge flux when it comes to household incomes.  With 14.5% of houses making less than 15,000 annually, but at the same time 14.1% of households makes more than 200,000 annually.  That is a massive socio economic different in one area.  This could play a major factor in people tweeting about energy because if 14.1% of Sana Monica is well off financially they will be looking into global issues and not worry about where their next meal is coming from.  When money isn’t an issue household find other issues that absorb their time.  In terms of race Sana Monica is 80.3% white.  Sana Monica has a much higher ethic population than Deer Park Texas, meaning that the residents of Sana Monica can be tweeting about other social, political, and other global issues rather than just tweeting about #energy and our planets problems.  There are other issues in Sana Monica like BLM and immigration.  Meaning that there is less of an emphasis on just environmental issues.  I wanted to dive in and look at the race over the last 40ish years in the Sana Monica area.  Interestingly enough the white population was lower in the 1990 probably due to all of the LA riots that were going on in the time it was not a good time to be white in the greater LA area so people moved.  Then in 2010 there was an enormous spike in the population of whites probably due to the tech boom.  I am not saying that all blacks tweet about black lives matter and other social issues, but they have much bigger problems on their plate gaining social justice and full human rights, that global warming and new energy takes a back seat to those issues.  That is why I looked so hard at race is because in those white heavy areas people will care about what is happening in their environment.

I really wanted to look at New York City through social explorer.  It is the the largest city in the world so residents there had to be tweeting about #energy.  I wanted to really look at the racial demographic of New York.  The majority of the cities I had looked at already had been from heavily white areas.  I was curious if New York would be the same way.  But the 10001 zip code that I examined in the city, was an area that was extremely white in the 1970, but as we creep closer to today we see that it’s dropped nearly 20% in 40ish years.  Now something really interesting that I noticed on all the racial graphs is the options that offered in 1970 vs 2010.  In 1970 there are 3 racial options, White, black or other.  In 1990 there are a few more options, and in 2010 there are dozens of options.  That is a social change that has happened over the last 40 years the expansion of different races in our cities, especially a city like New York.  It’s how the U.S. census has adjusted to accommodate the thousands of immigrants that are currently living in the United States.  For the 2015 census on the white population I zoomed out much further on that map because I wanted to show the racial distinctions that occur in New York.  All along the water it is heavily populated with red dots.  Almost so much so that it colors in the borders of Manhattan.  But if we look more central in the city we notice that there are few to no dots in some areas.  New York is an expensive city so there are very few people living below the poverty line.  I found it really interesting how high the less than 45 age is, 67%, that is more than Sana Monica and Deer Park Texas.  That the people living in New York are the ones who are active Twitter users.  Looking at it tweeting from the subway, the back of a cab, or the bus.  Twitter is an app that can get New Yorkers through their stressful commute.  I’m very glad I dove into who is tweeting about energy and what geographic locations are really tweeting about it.  It is beginning to give me a bigger picture into this search I have for #energy and big data.  For me this data was hugely insightful because I was able to see that everyone around the world is tweeting about #energy, not just liberal Americans, like some people would have you believe.  It is a global issue and everyone is talking about it.

 

 

 

 

 

 

 

 

Part VI: Final Refection

1. That new and sustainable energy is a must for globe.  That through global collaboration the world will have to work together to find a new source of energy to replace fossil fuels.  That through wind water, bioenergy or solar energy that if we globally invest and work together we can work past global warming.  It is a global issue and it needs to be solved as a planet according to Destouni and Frank the authors of “Renewable Energy,” an article published in the Special Report: Energy 2050.  “Among the renewable energy sources, hydropower is presently the most important source for electrical power generation.” (Destouni, Frank pg 18). Through my twitter research I want to now expand my tweets and see and see when #energy is tweeted how often the mention of hydropower is with it.  The second article I read discussed Energy use and its accessibility globally.  How people would be able to gain access to it in foreign impoverished lands. The development of the “‘energy poverty line’ as a function of income poverty line, some authors have attempted to do the same by looking at energy use at the aggregate national level in relation to tother broader measures of poverty such as human development index (HDI) or physical quality of life index (PQLI). (Pachauri and Spreng pg. 271).  That energy access is reflection of a quality of life and human development i.e developed lands where there is running electricity.  This is a completely new view on #energy and the compatibility with the globe.  Usually people are talking about the need for new energy not about energy access.

2. “Software-sorted geographies within which computerized code continually orchestrates inequalities through technological systems embedded within urban environments.” (Graham, 562). That surveying urban areas like we have been in this lab it gives us an understanding into the socio economic racial and age rage that people are living through.  It makes the people tweeting about energy more life like.  Makes them more than just a number and gives us a well rounded update on who is involved in this issue.

 

Bibiography for section VI:

1. Renewable Energy

   Georgia Destouni and Harry Frank
   Ambio
   Vol. 39, Supplement 1. Special Report: Energy 2050 (2010), pp. 18-21
   Published by: Springer on behalf of Royal Swedish Academy of Sciences
   Stable URL: http://www.jstor.org/stable/40801586
   Page Count: 4

2. Energy Use and Energy Access in Relation to Poverty

   Shonali Pachauri and Daniel Spreng
   Economic and Political Weekly
   Vol. 39, No. 3 (Jan. 17-23, 2004), pp. 271-278
   Published by: Economic and Political Weekly
   Stable URL: http://www.jstor.org/stable/4414526
   Page Count: 8

3. Graham, Stephen D.H. “Software-Sorted Geographies.” Progress in Human Geography 29.5 (2016): 562-80. Web. <http://www.dourish.com/classes/readings/Graham-SoftwareSortedGeographies-PHG.pdf>.