Mark Blevis

Here is the long overdue follow-up analysis of the Treasury Board’s #OpenGovChat which tool place December 15th (click here to read my initial analysis). In this post, I look at the breakout of signal-to-noise during the Twitter consultation.

Platforms and times

Analysis of the full session suggests future consultations would be more effective if conducted over platforms better suited to substantive conversation. Also, feedback, while positive, suggests future consultations take place over a greater period of time (full day? half day?) to better accommodate participation across the country. Regardless, the challenge will be dealing with the amount of meta-talk (discussion about the discussion) and partisanship (people taking the opportunity to take shots at politicians and their activities).

TOTAL #OPENGOVCHAT TWEETS (captured during consultation period, 5pmET and 5:45pmET): 854

SIGNAL

• On-topic tweets: 362 (42.4%)
• Retweets of on-topic tweets: 191 (22.3%)
• Tweets by TBS and Tony Clement: 41 (4.8%)
• PURE SIGNAL (on-topic not incl. RTs or tweets by TBS and Tony Clement): 130 (15.2%)

NOISE

• Meta tweets (tweets about the consultation and related Twitter activity): 378 (44.3%)
• Trending tweets (tweets about #OpenGovChat trending on Twitter): 7 (8.2%)
• Partisan tweets (taking shots at politicians and their activities): 81 (9.5%)
• GCpedia tweets (tweets about GCpedia, the internal public service wiki): 15 (17.6%)
• PM tweets (tweets about or relating to the PM): 15 (17.6%)
• SPAM (unrelated, commercial or porn): 3 (3.5%)
• PURE NOISE (meta and off-topic tweets): 492 (57.6%)