Thai Crisis Snapshot Theory

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The "Thai Crisis Snapshot" Theory

Overview

Over the past two days I had been trying to create a word picture snapshot (a Wordle), if you would call it, using the script from Worldle.net, I wanted to find out what are the different keyword(s), words that most internet users in Thailand were most actively talking, conversing, discussing about, or which word(s) regarding the Thailand Crisis were most mentioned Twitter, or on websites or blogs that were relayed through Twitter, those all of I was able to gather data upon. Below I have described (in detail) as to how I went about gathering data, refinements I had to do to the data and the processes used to create the word picture snapshots.

Please note hereby, that this is NOT a scientific analysis nor a statistically significant snapshot of the exact situation in the Thailand Crisis. My data is only limited to the time periods between the 14th of May, 2010 starting at 1900 hrs (GMT+7) until 17th of May, 2010 ending at 1600 hrs (GMT+7).

Data Gathering Process

Ultimately, all my data is only limited to enormous amount of Twitter feeds, those which I only managed to gather at various installments (at varying frequency and consistency) throughout the two days of the activity period I had had. Moreover, the data is also limited to only a handful of the most active and most frequent Twitterers on the Thailand Crisis that I was able to follow and acquire data from. Even though the most consistent data was acquired from English language tweets, I was also able to obtain a bulk of twitter activity in Thai and from a huge set of Thai language Twitterers, which were later translated, spelling normalized, centralized in order to blend with the English meanings or references.

As I could not find any proper Twitter backup software, or any other method of automatically accumulating various tweets, therefore I had to do it manually (which was really laboring), whereby I copied all the live tweets that would show up on my live feed, then paste them into a file, refreshing every minute and gathering all the tweets which would emerge at the very fast rate and then pasting them on top of the earlier feeds. I also copied all the retweets, as well as all discussion related to the tweet, and so on, as it was almost impossible to filter everything out fast enough manually. Below is a list of some #hashtags from which I gathered tweets, as well as a truncated list of Twitterers whom I started following in order to keep informed.

story continues: http://sethisuwan.blogspot.com/2010/05/text.html

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[321niti123]

Interesting

BTW..what are those "@"?

Interesting how Abhisit is not even in there

BTW, nice tool, same one my teacher uses to analyze a novel

[anothertorres]

the "@" is a twitter handle. a twitter user. if you want to build something that is relative to the "crisis", you should exclude the twitter account. in other words, people weren't talking about @georgebkk or @freakingcat. clean your data up and you've got something very interesting.

[wileycoyote]

Good idea !

[londonthai]

a nice, colourful picture, I bet tomorrow it will be printed on the t-shirts for tourists as a souvenir from thailand