Social Media Breakfast Seattle: What’s Being Tweeted?

by Steve Broback on February 19, 2010

Adam Schoenfeld over at blog.20dbs.com has written an informative post dissecting the tweets issued today during and after the excellent SMBSeattle 2/18 Event. His analysis has measured:

* Tweet Volume
* Tweet Mix (Mentions, Retweets, Other)
* Most active tweeters

Not to be outdone, (and in anticipation of my metrics session at the Seattle Twitter Conference next month) I decided to throw our analysis engine at those tweets to add in a few metrics of our own:

Sentiment:
91% of the tweets were positive in tone toward the event
9% were neutral in tone
0% expressed negativity toward #SMBSeattle

Links:
The most frequently linked to editorial within the tweets was the Ustream channel for the event.

Second place was Adam’s post.

Then came “3 Examples of Real World Social Media Conversion” by Jake Matthews.

Terms Mentioned:
Below are the most frequently mentioned terms.

And as a word cloud:

{ 3 comments… read them below or add one }

Jaremy February 19, 2010 at 2:27 am

Thanks for the follow-up on Adam’s post, Steve. Out of curiosity, what tools did you use for this analysis? I’m curious as to what the best tools are for sentiment analysis, specifically – the free tools I’ve used on my own are SocialMention (http://socialmention.com/search?q=%23smbseattle&t=microblogs) and Twitter Sentiment (http://twittersentiment.appspot.com/search?query=%23smbseattle) and I saw different results from you. I’m just curious as to what tools you use personally.

Warren Sukernek February 19, 2010 at 11:47 am

Steve,

Nice post! Thanks for the analysis and spreading the word about the Social Media Breakfast. As you can tell from the sentiment, the topic really resonated with our audience. We’ll have to get you speaking at a future event.

Thanks,

Warren Sukernek
President, Social Media breakfast Seattle

Steve Broback February 19, 2010 at 12:13 pm

Hey Jaremy — we have developed our own social tagging system which does sentiment (and a lot more.) If you look at the “negative” results that socialmention and Twitter Sentiment flagged, you’ll see why we felt the need to go our own route. Most systems can detect an overall negative tone, but are challenged at figuring out what that tone is directed AT.

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