After a long public hearing on Tuesday, City Council yesterday debated the proposed financial framework and ultimately whether or not they wanted to proceed with the downtown arena project. They voted 10-3 in favor of the framework, and also voted to spend $30 million to complete the design to 60%. Here’s my analysis of the the arena-related tweets posted by Edmonton users between 9:30am and 9:30pm.
By graphing the tweets per minute, you can very clearly see the time the vote took place (~3:03pm):
I was curious to know if the things people were tweeting before and after that moment were different. Here’s a word cloud of the tweets prior to the vote:
Caterina was mentioned a lot, which makes sense considering he turned out to be the surprise dealmaker of the day. The other Councillors were mentioned quite frequently too, as myself and others tweeted their comments.
Here’s a word cloud of the tweets posted after the vote:
It’s very interesting that “Edmonton” was tweeted so often after the vote passed. There were a lot of tweets similar to “Edmonton will get a new arena” that were retweeted after the vote. You can also see that “Iveson” was fairly prominent after the vote, reflecting the large number of tweets about his final remarks on the deal.
- It was another busy day for tweets in Edmonton with more than 42,000 posted by Edmontonians. That works out to an average of about 30 per minute.
- More than 880 users posted at least one arena-related tweet.
- On average, 5.0 arena-related tweets were posted per minute between 9:30am and 9:30pm. The peak was 43.
- Roughly 14% of the tweets were replies to other users.
- Roughly 29% of the tweets were retweets.
Here are the top 20 most active local users (most tweets to least):
Here are the top 20 most retweeted local users (by other local users, most retweeted to least):
I gave Paula a run for her money, but she remained the most retweeted user on the arena issue!
UPDATE: I’m always looking for better ways to analyze tweets. Finding a good, reliable way to do sentiment analysis (are tweets positive or negative) is a challenge, partially because tweets are so short and because they usually include weird entities like hashtags (weird from a natural language processing point-of-view). To analyze the arena-related tweets, I used uClassify’s Sentiment Classifier. Here are the results:
I would say this is pretty much as expected. Tweets before the vote probably expressed less emotion one way or the other. Most people tweeting after the vote seemed happy with the decision Council made.