This past weekend saw a coordinated day of action to protest Bill C-51, the Government’s proposed anti-terrorism legislation. As with most modern protest movements, there was a significant amount of online activity leading up to, during and even after the day of action.
In fact, there has been a significant amount of online chatter expressing concern about specific clauses of the Bill and motives of the Government. Coupled with the protests, online participation and amplification has helped raised the profile opposition to the legislation.
We’ve used Sysomos MAP to prepare a summary analysis of the online chatter spanning March 11 through March 15, inclusive, using specific search criteria relevant to the Bill. Our analysis reveals the following high-level stats which always seem to get popular attention.
- 103,915 tweets were issued by 52,993 unique Twitter handles
- 3,266 mentions in online discussion forums (including Reddit)
- 3,134 mentions on Tumblr
- 2,585 publicly-available mentions on Facebook
- 979 news mentions (includes syndicated stories printed in multiple locations)
- 605 photos publicly-available photos published to Flickr
- 377 blog mentions
- 177 videos were published to 116 unique YouTube channels
By the nature of the tool and the culture surrounding its use (and the shear volume of data), Twitter affords opportunities to conduct additional analysis.
The following image summarizes the volume and nature of the tweets issued. Among the findings are splits in participation by gender (59% male, 41% female). We also see that amplification (in the form of retweets) accounts for 72% of all Twitter activity while original content (regular tweets) accounts for 22% and conversations (@reply tweets) only 6%. Also, 72% of participants came and went in a single tweet suggesting most of the participation over the evaluation period was transient.
Peak participation over the course of the evaluation period occurred on March 14. In all, 54,764 tweets were issued by 24,678 unique Twitter accounts that day (2,282 tweets/hour). While interest was understandably concentrated in Canada, there was some international participation in the Twitter chatter. Often this comes through communities/networks of like-minded Twitter users.
A Buzzgraph illustrates the connections between key terms in the online chatter. The stronger the connection between the words, the thicker and bolder the connection line. Buzzgraphs show three strengths of connections illustrated by a thick solid line (strong), a thin solid line (medium) and a thin broken line (light).
The Buzzgraph for our analysis shows us how the public is connecting the ideas and players and where messages are sticking the most. The dominance of of strong and medium-grade connections suggest the overall volume of activity is high and the messaging/concerns are consistent. Our analysis of online conversations during the Idle No More and Occupy movements, and political issues including the Senate Scandal and Rob Ford’s cascading scandals during his term as mayor showed more fractured chatter.
Since I invoked the memory of the Idle No More movement for this post, it’s worth noting the biggest #IdleNoMore day on Twitter was January 11, 2013 when 56,954 tweets were issued.
The most popular tweet issued during the evaluation period came from Elizabeth May. Her “Thousands gather in #YYZ against #C51 to #RejectFear #StopC51 #GPC” tweet attracted 443 tweets. The tweet had a half-life of two hours and 48 minutes, and achieved a depth of 28, meaning the tweet moved 27 degrees from the original as it moved through networks of networked Twitter users.
The five accounts responsible for the greatest spread of the tweet are @ElizabethMay (242 retweets at level 0), @IdleNoMore4 (18 retweets at level 3, 40 minutes after original), @PatOndabak (12 retweets at level 2, 13 minutes after original), @Can_ada (10 retweets at level 2, 24 minutes after original) and @CanCivLib (8 retweets at level 1, 28 minutes after original).
As valuable as this summary analysis is, the real value comes through a deeper analysis in to the issues, sentiment and participants. That’s a much bigger job.
For more on how Twitter has influenced public policy, read our analysis of #TellVicEverything.
Sysomos MAP boolean search string
billc51 OR c51 OR “c-51” OR stopc51 OR c51dayofaction OR stopbillc51 OR rejectfear