Visualization Tools for Twitter A review and analysis of visualization tools in the Twitter domain...

Visualization Tools for TwitterA review and analysis of visualization

tools in the Twitter domain

By Joseph Vincze

Twitter Overview• Twitter is a micro-blogging social network whereby its users send and

receive short 140-character messages called "tweets". People use Twitter for sharing all manner of information – their thoughts, ideas, opinions, and sentiment; anything that is affecting them at that moment.

• Since Twitter’s public launch in July 2006 programmers and social scientists have been searching for ways to gather and analyze its data. Much of that data is public and available for mining and analysis.

• According to Pear Analytics (2009) tweets fell into the following six categories:

– Pointless babble– 40%– Conversational – 38%– Pass-along value – 9%– Self-promotion – 6%– Spam – 4%– News – 4%

The four pillars of Twitter

• Influence on Twitter

• Connectedness in the Twittersphere

• Twitter sentiment

• Currently “trending” on Twitter

21 tools were analyzed in regards to their effectiveness in visualizing these four categories.

Influence on Twitter

Influence can be estimated by the quantity and quality of one’s Twitter followers. Also, whether you followers are re-tweeting your posts – an indication of the level of trust they place in you. In order to engage with your followers more, you need to know the trends they are following and their preferences. In addition, information about what time to tweet and what might be of interest to your followers is important.


http://www.tweetbinder.com/

http://www.tweetstats.com/

http://tweetreach.com/

http://tweetchup.com/

https://tweepsmap.com/

http://www.socialmention.com/

http://www.tweriod.com/

https://monitor.wildfireapp.com https://followerwonk.com/

Influence on TwitterPerceptual Coding Interaction

Position X Direct Manipulation X

Size X Immediate Feedback

Orientation X Linked Displays

Texture Animate Shift of Focus

Shape Dynamic Sliders

Color X Semantic Zoom

Shading Focus plus Context

Depth Cues Details on Demand X

Surface Output / Input

Motion Information Density

Stereo Maximize Data-Ink ratio X

Proximity Maximize Data Density X

Similarity Minimize Lie Factor X

Continuity

Connectedness

Closure

Containment

Toolbox for followerwonk: To quote Aristotle, 'The whole is greater than the sum of its parts.”. That being the case, followerwonk is the clear winner - encompassing all the visual-analytics tools for analyzing one’s influence in Twitter. Sure you could go the cheap route and piece together tools from the free and freemium services, but it is too inconvenient and troublesome. Since the majority of the visuals in followerwonk are pie charts, it will be the basis for filling out the InfoVis Toolkit

Connectedness in the Twittersphere

How far does your influence extend? See yourself as a node on a social network diagram. See how many nodes away you are from a famous celebrity or a potential business contact.


http://mentionmapp.com/

http://hashtagify.me/

http://bluenod.com/


Toolbox for Mention Mapp: It was difficult deciding between Mention Mapp and Hashtagify Me since they were both excellent network diagram tools. Mention Mapp shows the connectedness of Twitter users and hashtags, whereas Hastagify Me shows the connectedness of related hashtags. I like the theory of the six degrees of separation - that we are only separated to any person on the planet through a chain of five-seven acquaintances (so Mention Mapp wins).

Perceptual Coding Interaction


Size X Immediate Feedback X

Orientation X Linked Displays X


Shape Dynamic Sliders X







Proximity X Maximize Data Density X

Similarity Minimize Lie Factor X

Continuity

Connectedness

Closure

Containment

Twitter Sentiment

People share their feelings on Twitter, both positive and negative about events in their lives. That emotion might be textual and/or represented in an emoticon.

Twitter Sentiment

http://www.csc.ncsu.edu/faculty/healey/tweet_viz/tweet_app/

http://twistori.com/

http://www.sentiment140.com/

http://www.ccs.neu.edu/home/amislove/twittermood/

Twitter SentimentToolbox for Tweet Sentiment Visualization : The most sophisticated sentiment tool of the bunch is Tweet Sentiment Visualization. Using a sentiment dictionary they are able to estimate the sentiment of the tweet based on the rating of the words in the text. There are eight different visualizations for this tool. For the purpose of filling the “InfoViz Toolbox” – I chose to interrogate the main scatter plot.














Similarity X Minimize Lie Factor X

Continuity

Connectedness

Closure

Containment

Twitter Sentiment

Sentiment. Each tweet is shown as a circle positioned by sentiment, an estimate of the emotion contained in the tweet's text. Unpleasant tweets are drawn as blue circles on the left, and pleasant tweets as green circles on the right. Sedate tweets are drawn as darker circles on the bottom, and active tweets as brighter circles on the top. Hover your mouse over a tweet or click on it to see its text.

Twitter Sentiment

Topics. Tweets about a common topic are grouped into topic clusters. Keywords above a cluster indicate its topic. Tweets that do not belong to a topic are visualized as singletons on the right. Hover your mouse over a tweet or click on it to see its text.

Twitter Sentiment

Heatmap. Pleasure and arousal are used to divide sentiment into a 8×8 grid. The number of tweets that lie within each grid cell are counted and used to color the cell: red for more tweets than average, and blue for fewer tweets than average. White cells contain no tweets. Hover your mouse over a cell to see its tweet count.

Twitter Sentiment

Tag Cloud. Common words from the emotional regions Upset, Happy, Relaxed, and Unhappy are shown. Words that are more frequent are larger. Hover the mouse over a word to see how often it occurred.

Twitter Sentiment

Timeline. Tweets are drawn in a bar chart to show the number of tweets posted at different times. Pleasant tweets are shown in green on the top of the chart, and unpleasant tweets are shown in blue on the bottom. Hover the mouse over a bar to see how many tweets were posted at the given time.

Twitter Sentiment

Map. Tweets are drawn on a map of the world at the location where they were posted. Please note most Twitter users do not provide their location, so only a few tweets will be shown on the map. Hover your mouse over a tweet or click on it to see its text.

Twitter Sentiment

Affinity. Frequent tweets, people, hashtags, and URLs are drawn in a graph to show important actors in the tweet set, and any relationship or affinity they have to one another. Hover your mouse over a node, or click on a node to see its tweets.

Twitter Sentiment

Tweets. Tweets are listed to show their date, author, pleasure, arousal, and text. You can click on a column's header to sort by that column.

Currently “trending” on Twitter

• A “trending topic” is a word, phrase or topic that is tagged at a greater rate than other tags via Twitter (Twitter, 2014). Trending topics are often spurned by an event that prompts people to talk about it.


http://visibletweets.com/

http://www.tweetbeam.com/

http://onemilliontweetmap.com/

http://trendsmap.com/ http://tweettopicexplorer.neoformix.com/

Currently “trending” on TwitterToolbox for Trendsmap: All the trending tools were noteworthy in their own right. Ultimately I chose Trendsmap because it was the most true to the concept of trending – displaying in real time Twitter topics around the world, superimposed on a map. It gives a good representation visually what is being tweeted globally – though it can be a bit too busy at times.





Texture Animate Shift of Focus X









Similarity Minimize Lie Factor

Continuity

Connectedness

Closure

Containment

ReferencesFollowerwonk. (n.d.). Followerwonk Homepage. Retrieved from https://followerwonk.com/ Hashtagify Me. (n.d.). Hashtagify Me Homepage. Retrieved from http://hashtagify.me/ Mention Map. (n.d). Mention Map Homepage. Retrieved from http://mentionmapp.com/Pear Analytics. (Aug., 2009). Twitter Study – August 2009. Retrieved from

https://www.pearanalytics.com/wp-content/uploads/2012/12/Twitter-Study-August-2009.pdfPulse of the Nation. (2010). Pulse of the Nation: U.S. Mood Throughout the Day inferred from Twitter. Retrieved from

http://www.ccs.neu.edu/home/amislove/twittermood/Raymond, M. (Jan., 2013). How Tweet It Is!: Library Acquires Entire Twitter Archive. Retrieved from

http://blogs.loc.gov/loc/2010/04/how-tweet-it-is-library-acquires-entire-twitter-archive/Sentiment104. (n.d.) Sentiment104 Homepage. Retrieved from

http://www.sentiment140.com/Social Mention. (n.d.) Social Mention Homepage. Retrieved from

http://www.socialmention.com/The one million tweet map. (n.d.) The one million tweet map Homepage. Retrieved from http://onemilliontweetmap.com/Trends Map. (n.d.) Trends Map Homepage. Retrieved from http://trendsmap.com/#]TweetBeam. (n.d.). Tweet Beam Homepage. Retrieved from http://www.tweetbeam.com/Tweet Binder – (TB). (n.d). Tweet Binder Homepage. Retrieved from http://www.tweetbinder.com/Tweet Reach. (n.d.). Tweet Reach Home Page. Retrieved from http://tweetreach.com/Tweet Sentiment Visualization - (TSV). (n.d.). North Carolina State University. Retrieved from

http://www.csc.ncsu.edu/faculty/healey/tweet_viz/tweet_app/Tweet Stats – (TS). (n.d.). Tweet Stats Homepage. Retrieved from

http://www.tweetstats.com/ Tweet Topic Explorer. (n.d.). Tweet Topic Explorer Homepage. Retrieved from

: http://tweettopicexplorer.neoformix.com/Tweetchup. (n.d). Tweetchup Homepage. Retrieved from http://tweetchup.com/Tweriod. (n.d.). Tweriod Homepage. Retrieved from http://www.tweriod.com/Twitter. (2014, December 13). In Wikipedia, The Free Encyclopedia. Retrieved 15:18, December 13, 2014, from http://

en.wikipedia.org/w/index.php?title=Twitter&oldid=637890345Visible Tweets. (n.d.). Visible Tweets Homepage. Retrieved from http://visibletweets.com/Wildfire. (n.d.). Wildfire Home Page. Retrieved from https://monitor.wildfireapp.com/?https://monitor.wildfireapp.com/=undefinedZeltser, L. (Jan. 22, 2009). How to Use Twitter for Information Mining. Retrieved from

https://isc.sans.edu/diary/How+to+Use+Twitter+for+Information+Mining/5728

Followerwonk. (n.d.). Followerwonk Homepage. Retrieved from https://followerwonk.com/ Hashtagify Me. (n.d.). Hashtagify Me Homepage. Retrieved from http://hashtagify.me/ Mention Map. (n.d). Mention Map Homepage. Retrieved from http://mentionmapp.com/Pear Analytics. (Aug., 2009). Twitter Study – August 2009. Retrieved from

https://www.pearanalytics.com/wp-content/uploads/2012/12/Twitter-Study-August-2009.pdfPulse of the Nation. (2010). Pulse of the Nation: U.S. Mood Throughout the Day inferred from Twitter. Retrieved from

http://www.ccs.neu.edu/home/amislove/twittermood/Raymond, M. (Jan., 2013). How Tweet It Is!: Library Acquires Entire Twitter Archive. Retrieved from

http://blogs.loc.gov/loc/2010/04/how-tweet-it-is-library-acquires-entire-twitter-archive/Sentiment104. (n.d.) Sentiment104 Homepage. Retrieved from

http://www.sentiment140.com/Social Mention. (n.d.) Social Mention Homepage. Retrieved from

http://www.socialmention.com/The one million tweet map. (n.d.) The one million tweet map Homepage. Retrieved from http://onemilliontweetmap.com/Trends Map. (n.d.) Trends Map Homepage. Retrieved from http://trendsmap.com/#]TweetBeam. (n.d.). Tweet Beam Homepage. Retrieved from http://www.tweetbeam.com/Tweet Binder – (TB). (n.d). Tweet Binder Homepage. Retrieved from http://www.tweetbinder.com/Tweet Reach. (n.d.). Tweet Reach Home Page. Retrieved from http://tweetreach.com/Tweet Sentiment Visualization - (TSV). (n.d.). North Carolina State University. Retrieved from

http://www.csc.ncsu.edu/faculty/healey/tweet_viz/tweet_app/Tweet Stats – (TS). (n.d.). Tweet Stats Homepage. Retrieved from

http://www.tweetstats.com/ Tweet Topic Explorer. (n.d.). Tweet Topic Explorer Homepage. Retrieved from

: http://tweettopicexplorer.neoformix.com/Tweetchup. (n.d). Tweetchup Homepage. Retrieved from http://tweetchup.com/Tweriod. (n.d.). Tweriod Homepage. Retrieved from http://www.tweriod.com/Twitter. (2014, December 13). In Wikipedia, The Free Encyclopedia. Retrieved 15:18, December 13, 2014, from

http://en.wikipedia.org/w/index.php?title=Twitter&oldid=637890345Visible Tweets. (n.d.). Visible Tweets Homepage. Retrieved from http://visibletweets.com/Wildfire. (n.d.). Wildfire Home Page. Retrieved from https://monitor.wildfireapp.com/?https://monitor.wildfireapp.com/=undefinedZeltser, L. (Jan. 22, 2009). How to Use Twitter for Information Mining. Retrieved from


https://followerwonk.com/



https://www.pearanalytics.com/wp-content/uploads/2012/12/Twitter-Study-August-2009.pdf


http://blogs.loc.gov/loc/2010/04/how-tweet-it-is-library-acquires-entire-twitter-archive/




http://trendsmap.com/

http://www.tweetbeam.com/

http://www.tweetbinder.com/

http://tweetreach.com/

http://www.csc.ncsu.edu/faculty/healey/tweet_viz/tweet_app/

http://www.tweetstats.com/

http://tweettopicexplorer.neoformix.com/

http://tweetchup.com/

http://en.wikipedia.org/w/index.php?title=Twitter&oldid=637890345





http://visibletweets.com/

https://monitor.wildfireapp.com/?https://monitor.wildfireapp.com/=undefined

https://monitor.wildfireapp.com/?https://monitor.wildfireapp.com/=undefined


https://followerwonk.com/



https://www.pearanalytics.com/wp-content/uploads/2012/12/Twitter-Study-August-2009.pdf


http://blogs.loc.gov/loc/2010/04/how-tweet-it-is-library-acquires-entire-twitter-archive/




http://trendsmap.com/

Visualization Tools for Twitter A review and analysis of visualization tools in the Twitter domain...

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