Tuesday, December 14, 2010

Introduction of project.


In April 20, 2010 an explosion and fire on BP's Deepwater Horizon drilling rig killed 11 workers. The rig, owned by Transocean Ltd and licensed to BP, was drilling 42 miles southeast of Venice, Louisiana, in 1,500 meters of water. The well had reached 3,900 meters under the seabed. This was the beginning of a major catastrophe. And only two days after the Deepwater Horizon sank had a 5-mile (8-km) oil slick formed. For three months, oil flew. I find human caused catastrophes interesting because of what it brings about. It means that we as humans needs to work together and through our gained knowledge solve the situation. This project is based on my knowledge of digital humanities. It means that this historic event will by analyzed using different digital tools and digitalizing materials.

Similar projects or, at least parts of it can bee seen, BP have on their homepage a interactive map and several shenomorph maps that you can download which will be helpful when explaining difficult data. Due to time restriction I will only be able to perform text analysis on one BP press release and one article about the leak from the Washington Post. Then I will compare and I will discuss similarities and patterns from the visualizations. The project will also include an interactive map that will show the location where Deepwater Horizon sank, and the fishing boundary that the oil leak led to. And finally a natural preserve, with a seashore rich of wild life. These locations will be marked on a map by using Google Maps.

Text analasis of a press release and a news article.


Article 1. ”Gulf of Mexico oil spill creates environmental and political dilemmas”
The article is published 27, April 2010 by Steven Mufson. 
Link to article

By using ManyEyes skills I ran a article from the Washington Post through the word cloud generator and this was what came up. All words are kept, I have not erased any.
The words that I found interesting was spill, oil and drilling. I then looked up the Word Tree function that ManyEyes offers. So, the next step in my analysis was to use the word tree to see how the author used this word.
Below is the result of that search. If we look at the result form my hypothesis viewpoint, the words that follows are clearly negative ’loaded’.
These two sentences are examples would fall into the category of negative loaded sentences, and follows my hypothesis ”Oil – Rig – workers are missing and presumed dead”, ”Oil –Spills –Are extremely harmful…”
I then checked the following words to see what types of sentences I would find, spill and drilling.
Searching for ’Spill’ generates the following sentences. The findings are interesting because it follows the findings in my previous search. The result is that the word are used in a negative way.  
  
My last word is drilling. Using ManyEyes word tree this is was what came up. 
 
Drilling only generated 6 hits, which is the fewest compared to the other two, but the findings are still interesting. The first sentences ”drilling rig explosion widened…”, is interesting from that point that the word explosion is used. And explosion must be seen as something negative. The remaining sentences uses the word in different context, in more neutral environment. It is not connected with other words that can seem negative.

Press release:

Press release 1. Title; BP Initiates Response to Gulf of Mexico Oil Spill
The press release is published 22, April 2010.
Link to press release

I found this press release to be interesting because it is within the same time period as the article analyzed above. The word cloud is generated by the 327 letters and numbers that the press release contained.

No words was deleted and the numbers were kept, thats why the triple zero turned up.
Two words that we recognize from the article turned up, spill and oil. I will look closer at these words in the press release as well. The findings can be interesting from a comparative point of view. The third and last word that I will look closer at will be ’BP’
 


 
The first word,’spill’, resulted the following:
According to my hypothesis the press releases should be more neutral in their choice of words.

The word ’spill’ is mostly associated with the word ’response’, which in this context must be seen as a positive word. Even if the words are seen negative it does not mean that the whole sentence needs to be negative. I will return to this in my conclusion.
 

The next word is ’oil. The word gave the following word tree.



We can directly see that the word ’oil’ is associated with the word ’spill’ and I have already analyzed that. The two remaining sentences does not use either positive words or negative words, they are more neutral.
My next and last word to look at in the press release is the initials of the company name British Petroleum, ’BP’. 

 
’BP’ are used in sentences that seem positive, examples of this are ”bp has also initiated a plan for the drilling of a relief well, if required” and ”bp today activated an extensive oil spill response in the us gulf of mexico…”. Words as activated, extensive, mobilized, initiated can be seen as powerful. BP sends signals that they are doing everything in their power to fix the problem.


Monday, December 13, 2010

Conclusion


The sample size may not in anyway be enough to draw any generalizations or new conclusions from and the result has in a high degree been influenced of my social background. But nevertheless, the result and technique is interesting. The projects text analysis purpose, to look at how words are being used different are interesting because of the influence this types of sources has. My result shows that a press release tends to use more neutral or positive words then the article did. Which strengthens my hypothesis. But as I stated above, the study needs both a larger sample size and more concrete variables defined, example; how to categorize. But my analysis proves that the digital shenomorph programs really can be useful when to find other perspective on subjects. The tools can be used in many ways and in different areas.