Spot by Jeff Clark.
From the post:
Spot is an interactive real-time Twitter visualization that uses a particle metaphor to represent tweets. The tweet particles are called spots and get organized in various configurations to illustrate information about the topic of interest.
Spot has an entry field at the lower-left corner where you can type any valid Twitter search query. The latest 200 tweets will be gathered and used for the visualization. Note that Twitter search results only go back about a week so a search for a rare topic may only return a few. When you enter a query the URL is changed so you can easily bookmark it or send it to someone…
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The Different Views
Here is a complete list of the views and what they show:
- Group View (speech bubble icon) places tweets that share common words inside large circles
- Timeline View (watch icon) places tweets along a timeline based on when they were sent
- User View (person icon) shows a bar chart with the people sending the most tweets in the set
- Word View (Word Circle icon) directly shows word bubbles with tweets attracted to the words they contain
- Source View (Megaphone icon) a bar chart showing the tool used to send the tweets (or sometimes the news source)
What do you like/dislike about the visualization? Is it specific to Twitter or do you see adaptations that could be made for other data sets?