Twitter Approval Matrix - November 2009

by Mike Hendrickson | @mikehatora | comments: 1

This is the sixth post for the Twitter Approval Matrix with data that spanned the month of November and different sources such as klout.com, tweetsentiment.com, twopular.com, scraping archives, and observations. This month I received help from Joe Fernandez the CEO of Klout.com. Joe continues to provide some great 'hard' data that allowed me to better place more items on the grid this month. This month I have included Twitter Trends which is simply the raw trend found on Twitter. When I mention "influence scale" this comes from Klout and is basically a weighted measure that shows how much amplification a message/topic gets from Tweeters who have lots of followers, get lots of RTs, and get a message widely disseminated.

A quick refresher, the matrix shows four quadrants used to describe trends found on Twitter. 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, this is partially about taste and numbers. 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.

For this post, I've limited the data and activity to the month of November. 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 both contributing to and tracking.

Twitter Approval Matrix - October 2009

by Mike Hendrickson | @mikehatora | comments: 6

This is the fifth post for the Twitter Approval Matrix with data that spanned the month of October and different sources such as tweetsentiment.com, scraping archives, and observations. This month I received help from Joe Fernandez the CEO of Klout.com. Joe continues to provide 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. 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, this is partially about taste and numbers. 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.

For this post, I've limited the data and activity to the month of October. 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 both contributing to and tracking.

Twitter Approval Matrix - August 2009

by Mike Hendrickson | @mikehatora | comments: 3

This is the fourth post for the Twitter Approval Matrix with data that spanned the month of August and different sources such as Hashtags.org, scraping archives, and observations. This month I received help from Joe Fernandez the CEO of Klout.com. Joe 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 hashtags.org, tweetstats.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, this is partially about taste and numbers. 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.

For this post, I've limited the data and activity to the month of August. 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 both contributing to and tracking.

Twitter Approval Matrix - July 2009

by Mike Hendrickson | @mikehatora | comments: 5

This is the third post for the Twitter Approval Matrix with data that spanned the month of July and different sources such as Hashtags.org, scraping archives, and observations. This month I received help from Joe Fernandez the CEO of Klout.com and Tom Zeng the creator of tweetsentiments.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 hashtags.org, tweetstats.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.

For this post, I've limited the data and activity to the month of July. 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.

State of the Computer Book Market - Mid-Year 2009

by Mike Hendrickson | @mikehatora | comments: 15

If you have read previous State of the Computer Book Market posts, you know we typically publish between 3-5 posts that summarize the computer book market for a given year. SInce it's mid-year, I thought I'd do a shorter, one-post summary of where things stand in 2009 thus far. The picture looks like our US economy: lots of bad news peppered with small glimmers of hope. So let's look at the Market, Categories, Publishers, and Languages.

The market has been on a steady decline since mid-2008 and has continued downward right through the first half of 2009. And there are very few signs that the book-buying slump is going to turn around anytime soon. Overall, the market saw 595,821 fewer units sold in the first half of 2009 than were sold in the same period of 2008. Although we do not have data to show the trends between 2000 and 2003, the market performance this year is the worst we've seen since the fall of of 2001. You'll notice in the chart below that the seasonal patterns have remained consistent, but sales are at a much lower volume than any previous year.

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Twitter Approval Matrix - June 2009

by Mike Hendrickson | @mikehatora | comments: 6

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.

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.

Twitter Approval Matrix

by Mike Hendrickson | @mikehatora | comments: 6

There is a lot of interest in figuring out how to most effectively use Twitter. The Twitter Book is a great start to put some of the of the puzzle pieces together. The book got me thinking about some of the people and tags that are popular. I was amazed at how Ashton Kutcher, @aplusk, surpassed 2 million followers relatively quickly. My curiosity led me to scraping his tweet archive and producing a Wordle of his tweets. I found very little substantive content as compared to Kathy Sierra (@kathysierra) or Tim O'Reilly (@timoreilly). Don't get me wrong, Ashton does tweet, but it's about boring stuff, IMO. But boring to me could be exciting to one of his followers.

This got me thinking further about tastes. We all have different tastes. I like to make sense of the world around me by collecting as much information as I can, analyzing it (in my head and in programs), and then visualizing it. So, that led me to the matrix idea. Why not plot Twitter activity, trends, users, tags on a matrix? For years, I've been reading the New York Magazine and always scanned its Approval Matrix. They describe their Twitter version as, "Our deliberately oversimplified guide to whose tweets are worth following." I thought I'd do the same, but with more than just who but also what is worth following. I decided to throw in some analysis and a user contributed component: you. The "you" part is for the future. That is, I would like you to contribute coordinates for where you think items should land on a future grid similar to the one below.

This matrix shows four quadrants used to describe tastes 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.

For this post, I've limited the data and activity to the month of May. I will make this a monthly post if I get enough feedback/help. So, here's how you can nominate topics or people for the matrix:

• You can tag any of your tweets, RTs using #approvalmatrix and I'll find it.
• Tweet to @mikehatora
• DM mikehatora
• Send email to mikeh {at} oreilly {dot} com

If you want to suggest where the tweet or subject belongs on the matrix, do this:

• Notice the numbers on the grid, 1-10, in North/South and East/West directions.
• Notice the quadrant tags NE, SE,NW,SW, on the outer corners of each quadrant.

So NE, 6,8 would put your suggestion between #jobs and #followfriday.

Here are a couple of examples that could end up on future ApprovalMatrix postings:

• @mikehatora #wwdc, NE 5,9 Interesting new stuff from Apple, but seems to have NOT leapfrogged ahead again this year. The plot is hot [N], because lots of hastags have #wwdc and the comment shows it is interesting [E] but not at the 8-10 scale of smart but rather a 5-right, 9-up on the plot]. You could say a topic like this is hotter than it is smart/interesting/useful.
• Starting new job on Monday, thanks to Twitter posting. #ApprovalMatrix This will be picked up in a scrape and added to the jobs/careers bucket. It'll likely will be a NE 5,8 aggregated with the other job data and comments.
• #approvalmatrix NE 7,8 RT @timoreilly Three-part series on how Google does search quality evaluation, starts here: http://bit.ly/QIgwX Here the tweeter is Re-Tweeting someone (timoreilly) and indicating that it is an important item in the Hot and Smart quadrant (NE). I'd look to see how many RTs have happened after the initial tweet.
• DM mikehatora SE 7,8 #hr Indicates the hashtag #hr, which is Human Resources, is not trending up, and is boring according to the sender.

Feel free to nominate people, tags, related news, etc. I can't guarantee your nomination will make it into next month's post, but it just might. This is a chance for you to put things on our Radar while letting us know what your tastes are.

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

State of the Computer Book Market 2008, part 5 -- eBooks and Summary

by Mike Hendrickson | @mikehatora | comments: 7

In this final post, 1, 2, 3, and 4 were posted earlier, I will provide a summary of the first four posts, provide some insight into a view of top Authors, and include some data on electronic books and how the digital world is catching up to the print world.

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State of the Computer Book Market 2008, part 4 -- The Languages

by Mike Hendrickson | @mikehatora | comments: 25

In this fourth post (parts one, two and three are found here) on the State of the Computer Book Market, we will look at programming languages and drill in a little on each language area.

Overall the market for programming languages was down 5.9% in 2008 when compared with 2007. There were 1,849,974 units sold in 2007 versus 1,740,808 units sold in 2008, which is a decrease of 109,166  units. So the unhealthy 8% loss in the Overall Computer Book Market was not completely fueled by programming-oriented books.

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State of the Computer Book Market 2008, Part 3: The Publishers

by Mike Hendrickson | @mikehatora | comments: 5

In this third installment, (see part one and part two; part four to come later this week), we will look at how Publishers fared in 2007 when compared to 2006. The chart below shows our dashboard view of the Large publishers’ results for 2007. The most notable factor is that Wiley continues to hold the leading spot as the largest publisher, with 30% market share of units sold, while Pearson lost 2% market share and O'Reilly gains 1%. (We’ll look at revenue share later in the analysis.)

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