Japan Earthquake: What are they tweeting about?

What are they tweeting about?

One key feature of social media is that it provides a snapshot of a moment’s mood, reflected by the content of what people are tweeting about in real time.  In order to analyze the emotional and psychological state of the nation in the days after the disaster, I have taken the tweet content text in the UCLA archive, and divided them into 30 text files, one for each day following the Earthquake, starting on March 11, 2011.  To measure day to day fluctuations of emotions, I will use a similar methodology employed by Eiji Aramaki PhD (Tokyo University) which takes words from an “Emotion Dictionary” (感情表現辞典) and matches it against the tweet content.  The dictionary classifies different emotions into 10 groups:

  1. 喜び – Happiness
  2. 怒る – Anger
  3. 哀しい – Sad
  4. 怖い – Fear
  5. 恥 – Shame
  6. 好き – Like
  7. 厭 – Unpleasant
  8. 昻 – Nervous
  9. 安 – Relief
  10. 驚く – Surprise
In order to visualize the relationship between various emotions keywords against the different days following the earthquake, a visualization was generated using Gephi.  The words are color coded by emotion type, and line thickness of the connectors represents the strength of the connection between the word and the days.

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Top 20 emotion words:

Word Emotion Category Per 10000 Tweets
1 like 3,242.58
2 relief 1,151.22
3 nervous 324.83
4 嬉し泣き happy 322.78
5 sad 322.78
6 誇る happy 292.07
7 心痛 fear 228.80
8 享楽 happy 121.40
9 relief 121.40
10 like 120.92
11 不安がる fear 104.83
12 傷付く sad 74.57
13 恐怖感 fear 53.37
14 悲しみ sad 51.65
15 愛情 like 47.32
16 難苦 unpleasant 45.29
17 怯れ fear 44.97
18 like 43.35
19 深謝 happy 38.77
20 驚愕 surprise 34.45

Emotions by Day

The following animated chart (press the play button to start it), shows the changes for each emotion category over the 30 days.

(view full screen)