Twitter Approval Matrix – June 2009

Last month I posted the first Twitter Approval Matrix with data that spanned the month of May and different sources such as Hashtag.org, scraping archives, and observations. This month I received some help from Joe Fernandez the CEO of Klout.com and Dan Zarrella the Social & Viral Marketing Scientist for danzarella.com. They provided some great ‘hard’ data that allowed me to better place more items on the grid this month.

A quick refresher, the matrix shows four quadrants used to describe trends found on Twitter, or related sites such as hashtag.org, tweestats.com, etc. The Y-axis is partly analytical and shows popularity (mostly through scraped numbers) or perceived popularity (in the future nominated by you). The other part of the grid is more curated and subjective. The X-axis has been plotted based on my personal opinion. You may agree or disagree with my placements and that’s all good to me. After all, it is about taste. The matrix and plots do not represent a thorough analytical treatment, but rather a view of the trends that could be found in data sources allowing me to plot with some sense of relevance.

TwitterApprovalMatrixJune.png

For this post, I’ve limited the data and activity to the month of June. Again, I’ll continue with this project as long as I get enough feedback/help. So, if you are interested in contributing, you can comment here, or read the original post to figure out the best way for you to submit your plots.

I hope you enjoy this and see it as a potentially useful tool to monitor trends that your fellow readers are tracking.

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  • http://www.geero.net/ Andy Geers

    As boring as complaining about bad service might be when it’s coming from my followers (re:AT&T) it is a very useful function of Twitter in the aggregate to be able to see particular problems in the list of trending topics. Not really sure you can have one without the other.

  • http://tweetsentiments.com Tom Zeng

    Mike, great and very interesting work. If you are interested, I can help you add sentiment analysis on those twitter users using tweetsentiments.com.

  • http://friendfeed.com/murliman Murli Nagasundaram

    Interesting. Could you somehow capture these two factors:

    a) the number of tweeters tweeting about a subject
    b) the number of tweets about a subject

    The two are distinct. ‘Number of Tweeters’ could be a surrogate for ‘interestingness’ and ‘Number of Tweets’ for ‘hotness’. If a lot of Twitterers are tweeting on a subject, then by definition, it is interesting. Further, the volume of tweets in given period of time also indicates how hot the subject is.

    With this you eliminate the subjectivity in your analysis.

    Cheers.

  • http://friendfeed.com/alfpace Alfonso Pace

    I like the boring-smart hot-cold dichotomy

  • http://www.twitterdirectory2000.com Twitter Directory 2000

    We need to cut through the clutter and find the good, bad, and worthless before Twitter becomes too overwhelming and we all just move on to the next big thing.

  • http://www.julianchappa.blogspot.com Julián Chappa

    The Era of «Twitterminator 2.0»?