Visual analysis of WWW2010 Conference
The WWW2010 Conference took place on April 26-30. I couldn’t attend it but I collected all the tweets with the hashtag #www2010 from March 31 to May 3. As an image is worth more than a thousand words I made a visual analysis of the Conference from this data.
(Click on the image to see it larger)
Who were the most active Twitters?
|
What were the most used words?
|
What were the most cited sites?
|
What were the shorten urls services used?![]()
|
What were the most retwittered URL’s? Twitter Papers at the WWW 2010 Conference
(22) WWW2010 Twitter Roomstreams (19) RTP Meetup (15) Futureweb (schedule) (13) What is Twitter, a social network or a news media? (12) Elon University/Pew Intenet Project (Futureweb) (11) Durham, a Tobacco Town, Turns to Local Food (10) Fresh Direction: A Farm-to-Table Restaurant (10) |
What were the most clicked URL’s? (1) xkcd (2.870)
Facebook’s Eroding Privacy Policy: A Timeline (1696) Truly W3C Community building at WWW2010 (Part 1) (1577) Web 2.0 Suicide machine (1248) Tim Berners-Lee on the next Web (1085) Privacy and Publicity in the Context of Big Data (1011) Why Twitter Is the Future of News (996) What is Twitter, a Social Network or a News Media? (739) Open Graph protocol (359) |
How often did users twitter by day?
|
How often did users twitter by the hour?
|
Highlighted data:
- Users: 3,093 tweets were written by 900 different users, with an average of 1.24 tweets / user. 71.35% of tweets were written by 20% of users (Paretos’s Law). The most actives users were: @futureweb2010 (125), @LaTerribleLiz (119), @BoraZ ( 96), @fabien_gandon ( 88), @smalljones (67), @tommyh @olgag (57), @apisanty (47), @karenchurch.
- URLs: 1,112 urls were found, 549 of them were different. There were 845 (76%) shorted URLs. Bit.ly was the most shorten url service used with a share of 65.9%.
- Trends: there is a growing interest in Twitter, it is present in most RTs and clicked URLs. However, it maybe due to people who use twitter being more interested in Twitter.
- RT vs. Clicks: There is not a correlation between RTs and Clicks, as can be seen in the image:
Methology
- Own tools were used to extract data
- The bit.ly API and the Python-bitly library were used to get the number of clicks for each URL.
- Many eyes web service was used to data visualize
DataSet:
(1) This ranking is only for URLs shorted with bit.ly. Others URLs couldn’t be measured
Alex,
Thanks!!
Very interesting your paper, I’m going to read it in depth.
Interesting !
You may also have a look at http://journal.webscience.org/314/2/websci10_submission_79.pdf for an analysis of the use of Twitter on other conferences