Shaped Word Cloud: Canada

By: Jeff Clark    Date: Wed, 01 Jul 2009

Happy Canada Day ! This is a Shaped Word Cloud created from the text of approximately 168,000 tweets containing the word 'canada'. The tweets were gathered over an 11 month period from July 31, 2008 to June 30, 2009.

Basically, the larger the word the more frequently it appears in the text. Stop words were discarded. I also adjusted the size based on the relative frequency of the word in the canada dataset versus a baseline dataset containing tweets about india and china. A word like 'country' or 'travel' is used approximately the same for canada as for india and china and so will be de-emphasized. Words like 'hockey' , 'canadian', 'snow' and place names within canada will appear bigger. Because of the baseline content the result will not properly reflect any strong associations between canada and india or canada and china. As usual you can click on a word to see the current twitter search results.

Word Search: Canada Map

By: Jeff Clark    Date: Tue, 30 Jun 2009

Here is another Shaped Word Search in honour of Canada Day tomorrow, July 1st. This one is in the shape of a map of Canada and uses Provinces, Territories, and cities in the word list. Click on the image or here for the PDF version.

Feel free to print this in any newspaper or magazine. I only ask that you keep the reference to http://neoformix.com and that you send me an email letting me know.

Click on the image to download a hi-res PDF version suitable for printing

Word Search: Maple Leaf

By: Jeff Clark    Date: Tue, 30 Jun 2009

In honour of Canada Day tomorrow, July 1st, I have created a Shaped Word Search with a maple leaf design and words I associate with Canada. I improved my tool slightly to sort the words in alphabetical order so it is more convenient to look them up. Thanks to Joe S. for the suggestion. Click on the image or here for the PDF version.

Feel free to print this in any newspaper or magazine. I only ask that you keep the reference to http://neoformix.com and that you send me an email letting me know.

Click on the image to download a hi-res PDF version suitable for printing

Word Portrait: Michael Jackson

By: Jeff Clark    Date: Sat, 27 Jun 2009

Here is a Word Portrait of Michael Jackson created from the titles of many of his top songs.

Click on the image to see a larger version

Twitter Venn: Celebrity Deaths

By: Jeff Clark    Date: Fri, 26 Jun 2009

Here is a Venn Diagram made with Twitter Venn that shows the relative frequency of tweets made about the recent deaths of three celebrities - Michael Jackson, Farrah Fawcett, and Ed McMahon. This analysis was done around 7am EST today and the absolute numbers for tweets/day will certainly increase as more people in the US come online. I expect the proportions among the various combination regions to stay roughly the same.

A couple of points of interest:

• Celebrity interest ranked by number of tweets is Michael > Farrah > Ed with ratios 62:6:1
• Ed was mentioned together with both Michael and Farrah more often than he was by himself

To explore the data using the interactive application click on the image below or this link: Twitter Venn for #michaeljackson, #farrahfawcett, and #edmcmahon.

Twitter Employee Clusters

By: Jeff Clark    Date: Thu, 25 Jun 2009

Here is a different view of the relationships between the Twitter employee accounts first presented in this post. I measured the similarity between all the twitter employee accounts based on the overlap in vocabulary used in their last 200 tweets. A clustering algorithm was then used to group them together based on the pairwise similarity scores. The algorithm was tuned to limit clusters to have a maximum of 8 members.

The image below was created from the cluster members data, the similarity between clusters, and the similarity within each cluster. To minimize line clutter I am only drawing a connection if it is one of the top 2 strongest for either end node. The clustering and layout code is based on what I used for the Toronto Twitter Community project but has been recently enhanced to support some new client work.

Here is the PDF version of the Twitter Employee Clusters.

Shaped Word Search - Twitter

By: Jeff Clark    Date: Mon, 22 Jun 2009

Here is another example of a Shaped Word Search. This one uses a Twitter Bird as the image and a list of words related to twitter. I also experimented a bit with adding distractors in order to make the puzzle more difficult. There are a couple of partial matches for each word mixed in to the letter matrix. Click on the image or here for the PDF version.

Click on the image to download a hi-res PDF version suitable for printing

A Shaped Word Search - Malta

By: Jeff Clark    Date: Sun, 21 Jun 2009

I celebrated Father's Day this weekend with my wife's parents. While there, I spent a frustrating and unsuccessful 15 minutes looking for one of the few remaining words in a giant word search my father-in-law was working on. We found out later by checking online that there was an error and the word wasn't even present in the puzzle!

Much more enjoyable was the hour or so we spent doing a virtual tour of Malta using Google Earth. My father-in-law was born there and we had great fun zooming in with the aerial views finding the house where he lived, the church where he was baptized, etc. We were also able to easily see wonderful pictures of the many famous churches and natural features like the Blue Grotto. It's a beautiful and fascinating place and I'd love to visit sometime.

Well, the ideas of Malta, word search puzzles, and the usual mishmash from my coding projects mixed together in my brain while I was sleeping and I woke up early realizing I could easily write a tool to create 'Shaped Word Search Puzzles'. Basically, I can take a template image and a list of words and automatically construct a word search puzzle shaped and coloured to match the image.

The first example is below and uses a Maltese Cross with a list of words related to Malta. Most of the words are place names but there are a few other things mixed in as well. For example, Pastizzi are one of my favourite Maltese foods.

Click on the image to download a hi-res PDF version suitable for printing

IranElection Tweets Phrase Net

By: Jeff Clark    Date: Sat, 20 Jun 2009

I have uploaded the set of tweets I used to create the Iran Election Word Cloud to the wonderful Many Eyes and created a Phrase Net visualization for the data. This image below shows the net for the pattern word1 and word2. So, for example, the arrow connecting 'police' to 'riot' means there were lots of instances of the phrase 'police and riot'.

Static image of the phrase net for #IranElection Tweet Data (see below for interactive version)

See below for the interactive version.

Iran Election Tweet Narrative II

By: Jeff Clark    Date: Sat, 20 Jun 2009

I have updated my Tweet Narrative about the Iran election. This one uses 141,000 tweets from the time period June 14-20th, 2009. I have also improved the algorithm that selects the characteristic tweets. The changes are difficult to describe succinctly but did reduce the number of tweets that started with 'RT'. This helps meet my primary goal of constructing a readable summary of the content. For this analysis I also only counted the first 10 tweets from any particular account which helps prevent the tweets from a few individual accounts from dominating the results.

Iran Election Word Cloud

By: Jeff Clark    Date: Thu, 18 Jun 2009

This is a Shaped Word Cloud created from the text of approximately 84,000 tweets containing the term #iranelection. The larger the word the more frequently it appears in the text. As usual you can click on a word to see the current twitter search results.

Feel free to follow JeffClark on Twitter to get more updates on my work.

Iran Election Tweet Narrative

By: Jeff Clark    Date: Tue, 16 Jun 2009

The world is watching with great interest the demonstrations in Iran related to the recent election. The twittersphere is filled with discussion of the event and, of course, much of it is redundant. I have built a Tweet Narrative based on a collection of ~ 60,000 tweets containing the tag #IranElection. Basically, I divided the tweets into 30 groups based on the time they were published and then statistically select the one tweet most representative for that time slot.

Twitter StreamGraph Update II

By: Jeff Clark    Date: Mon, 15 Jun 2009

I have posted a small update to the Twitter StreamGraphs application to make it more useful. Previously it used Twitter Search to get results for simple queries of the type 'from:twitterid'. Twitter Search currently only gives results going back about 14 days - it used to be much longer. For most people who don't tweet frequently this resulted in a poor quality streamgraph because there weren't many results to work with.

I'm now using the standard Twitter API to retrieve the tweets for any simple user query and it will graph up to a maximum of 1000 tweets irregardless of how far back they go. The difference is shown below for Clay Shirky. The second image shows the new improved results which, for him, go back almost a year. The graph is much richer than the first one which can only base the graph on tweets in the last two weeks.

Previous results limited to approximately 14 days due to Twitter Search limitation
 
New results for simple queries of the type from:twitterid

Chinese Ideogram for Flower

By: Jeff Clark    Date: Sun, 14 Jun 2009

Here is another design made with the flower images from Wikimedia Commons. It's the chinese ideogram for 'flower' rendered with flowers.

Others in this series: FlowerTank, FlowerCycle, and John Lennon Flower Portrait.

Venn: Iran, Iraq, Afghanistan

By: Jeff Clark    Date: Sun, 14 Jun 2009

Here is the result of a Twitter Venn query for Iran, Iraq, and Afghanistan. The recent controversial elections in Iran have obviously grabbed a lot of attention in the Twittersphere. It's interesting that the number of tweets mentioning both Iran and Iraq is roughly the same as the number mentioned Afghanistan and Iraq even though tweets about Iran are so dominant.

Click on the image to see the current Twitter venn diagram for these three terms.

Celebrity Twitter Accounts

By: Jeff Clark    Date: Sun, 14 Jun 2009

I recently made some improvements in my graph display code for a client and have used it to create a new graph showing the vocabulary relationships between many celebrities on Twitter. The post More Twitter Account Graphs explains a little about what the similarity is based on.

The central people in this set appear to be RyanSeacrest, PaulaAbdul, and TheEllenShow. The similarity score between Ryan and Paula is 19.8% and the top words connecting them together are: 'radio', 'game', 'guys', 'adam', 'movie', 'coast', 'studio', and their respective Twitter IDs.

Another interesting grouping is BarackObama, schwarzenegger, and timoreilly. The similarity score between Obama and Schwarzenegger is 16.7% with the top connecting words being 'health' , 'care', 'video', 'president', 'address', 'vote', and 'event'.

I included jtimberlake in the analysis as well but he was removed from the final graph because he wasn't connected strongly enough with anybody else. His closest match was only 4.5% and was with Oprah.

Beetles

By: Jeff Clark    Date: Thu, 11 Jun 2009

After my previous John Lennon Flower Portrait I had the Beatles on my brain and stumbled across a lovely set of photographs of beetles on COLOURlovers. I have tried creating an image of The Beatles using beetles but haven't yet come up with a decent design. Instead I made this beetle outline image from 24 different species. I have seen a lovely physical display of beetles arranged in this manner but I'm not sure where it was. It may have been at the Royal Ontario Museum.

Click image to see larger version

John Lennon Flower Portrait

By: Jeff Clark    Date: Tue, 09 Jun 2009

Here is a flower portrait of John Lennon created from the image on the page 100 Portraits of Iconic People of all time. The flower images are from Wikimedia Commons.

John Lennon Word Portrait

By: Jeff Clark    Date: Tue, 09 Jun 2009

It has been a while since I've created a Word Portrait. Here is one of John Lennon created from the image on the page 100 Portraits of Iconic People of all time.

Here are links to Word Portaits of Obama and Einstein.

Cairo Speech Word Graph

By: Jeff Clark    Date: Thu, 04 Jun 2009

Here is another way to look at Obama's speech in Cairo calling for A New Beginning with Muslims. It uses a standard node link graph to show which words were used near each other in the text. There are virtual springs connecting words that are used frequently together and forces pushing apart nodes so they don't overlap too much. The nodes in orange have been fixed to a certain location and the other nodes move based on the springs and forces until a stable configuration is reached. This allows us to stretch out the graph and easily see where terms lay along a spectrum between 2 or more words of interest.

This first view shows that there was more discussion of 'peace' than 'war' and that words like 'palestinian', 'israel', and 'god' were highly associated with 'peace' relative to the other highlighted words.

Click image to see a larger version

This second view below is of the same graph but with different words pegged in place. The terms 'nuclear' 'weapons' and 'united' 'states' are both closer to 'iran' than the other countries. Similarly, 'women' 'denied' 'equal' is more associated with 'afghanistan'.

Click image to see a larger version

An obvious way to improve these would be to use word stemming to combine different forms of the same word. For example, 'muslim' and 'muslims' would use one node, as would 'peaceful' and 'peace'. This would reduce the number of nodes and probably more clearly expose any relationships.

The code to construct these was written with Processing and makes use of the excellent Traer Physics library.