I harvested tweets containing the #comtech2011 hashtag and created a TreeCloud. The workshops (twitter, digital cities, fooding, keynote by @ericbot) are all captured in the TreeCloud.
I am not attending Ascilite 2010, but thought it would be useful to get an overview of the twitter stream from the conference. Twapperkeeper contains the archive for the #ascilite10 hashtag. I have used a TreeCloud visualisation, which has the benefit of being able to separate tweets based on word proximity.
What do you think? Is the essence of the twitter stream for Ascilite 2010 captured?
A TreeCloud is a visualization technique that uses a tree structure to display words used in close proximity of each other. I thought the technique would be useful if applied to tweets from an event, given the temporal nature of posts. I used TwatterKeeper to export tweets containing the #ozchi hashtag for the first two days of the OzChi conference. The TreeCloud visualization was able to group together tweets about the keynotes (John Seely Brown, Elizabeth Churchill and Jacob Buur) and other themes such as vote for the student posters, get the OzChi iPhone app, travelling to OzChi in Brisbane and me (@aneesha) tweeting about analysing Ozchi paper abstracts over 5 years. I have included an annotated version of the TreeCloud for OzChi 2010 tweets below.
Software to create TreeClouds is available from http://www.lirmm.fr/~gambette/treecloud/. The code is written in Python. An online tool to create TreeClouds is also available.
I am attending my first OzChi conference - OzChi 2010 in Brisbane, Australia. Having not been to any OzChi conferences before, I was interested in analysing papers across years in order to find common themes. I have used a matrix decomposition algorithm to uncover the main research themes from previous conferences and well as the current OzChi conference. Each year (2006 - 2010) was analysed separately, with only the paper abstracts being included in the analysis. I used jQuery to extract the text for the abstracts from the online proceedings. Each abstract was then added to a term-document matrix with common words such as “design, paper, present, presented, display, displays, displayed, develop, developed” removed. The Non-negative Matrix Factorisation algorithm was used to uncover themes or topics within the accepted papers for each year. The main words found in the top 5 themes for each conference are listed. Mobile and location aware application research seems to be present from across all years analysed.
OzChi 2006
| Theme | Main Words |
| Theme 1 | awareness [16] social [33] technology [50] cue [9] study [35] |
| Theme 2 | usability [29] software [26] model [18] mobile [25] develop [28] evaluate [27] |
| Theme 3 | keyboard [11] key [11] input [13] wearable [7] text [9] |
| Theme 4 | develop [28] technique [19] software [26] tool [21] participatory [7] |
| Theme 5 | probe [20] technology [50] culture [15] method [24] children [9] |
OzChi 2007
| Theme | Main Words |
| Theme 1 | gesture [25] remote [17] physical [19] |
| Theme 2 | mobile [17] tool [21] everyday [11] usage [8] life [7] |
| Theme 3 | visualization [22] support [35] information [18] tool [21] |
| Theme 4 | speech [11] cognitive load [11] multimodal [7] |
| Theme 5 | physical [19] interaction [42] community [21] game [9] social [8] |
OzChi 2008
| Theme | Main Words |
| Theme 1 | community [44] technology [41] social [34] interact [46] design [31] network [14] |
| Theme 2 | game [25] player [8] participation [26] study [37] interact [46] approach [14] |
| Theme 3 | speech [10] cognitive load [6] measure [5] |
| Theme 4 | mobile [30] usage [10] phone [13] feature [11] |
| Theme 5 | interact [46] design [31] body [10] kinesthetic [7] |
OzChi 2009
| Theme | Main Words |
| Theme 1 | technology [47] social [26] design [28] support [31] practice [15] participation [23] |
| Theme 2 | scroll [22] tilt [8] flick [5] task [19] |
| Theme 3 | active [43] physical [13] game [9] user [27] play [7] |
| Theme 4 | location [23] share [10] data [15] map [10] phone [9] |
| Theme 5 | group [23] study [40] older [8] research [39] adult [6] feedback [8] |
OzChi 2010
| Theme | Main Words |
| Theme 1 | experience [61] game [18] interact [51] product [9] person [16] ux [4] |
| Theme 2 | search [21] web [20] inform [38] cognitive [13] style [7] find [23] |
| Theme 3 | cloud [14] tag [13] table [6] visualisation [4] social [32] task [17] |
| Theme 4 | mobile [30] news [6] profession [8] quality [12] study [51] evaluation [25] |
| Theme 5 | technology [47] social [32] people [22] inform [38] older [9] isolated [4] |
| Theme 6 | real-time [8] coordination [5] challenge [11] sound [3] musician [3] explore [26] |
| Theme 7 | inform [38] role [18] interact [51] copresence [3] eparticipation [4] |
I have built an interactive theme or topic explorer tool as part of my research at QUT. The tool is powered by the Non-negative Matrix Factorisation and Latent Dirichlet Allocation algorithms. The tool allows users to interact with algorithm parameters, includes techniques to assist with data interpretation and was used to perform the analysis. Feedback on the analysis is welcome and appreciated.
Making sense of the twitter feed from OzChi 2010 will be published tomorrow. Stay tuned!
I sometimes express angst via my @aneesha twitter account, never thinking that anybody takes notice of what I choose to complain about. I was surprised to realize that the @safaribooks does indeed listen. The story begins with me being given access to a book I really wanted to read via Safari Books Online. In all honestly, I could not get comfortable with reading the book via the web-interface that Safari Books provides. It was hard to scroll between pages, the font rendering was blurry, and I needed to be online while I read the book. This all gave me a headache which prompted me to tweet - “Safari books - your web-based e-book reader with crappy font rendering has given me a headache.” Not my best articulation of a problem but I have an excuse - I had a headache. I really did not think this feedback would go any further but the next day @safaribooks replied with “@aneesha A headache is no good at all. I will share your feedback with our product management team.”. Now that’s pretty impressive and proactive customer support. …which gets even better when I then receive an email from customer support wanting further details of my issues. So thank you Safari Books for actively seeking to improve your product and monitoring sentiment via twitter feeds even though I wonder how you got my email address.
Madonna blond or Madonna brunette? Madonna started her career as a blond and though her style changed between the "Like A Virgin" to "True Blue" albums, it was not until "Like A Prayer" that we really got the power brunette look. I sense a "Like A Prayer" moment coming for Lady Gaga soon….. Just a matter of time….
It is quite inspiring to view the early paper based sketches of popular web apps such as Flickr, Twitter and Vimeo. Everything has to start somewhere….
I like the "rip-mix-burn" Teacher as a DJ metaphor proposed by "Iterating Towards Openness". I promise to refrain from changing the lyrics of Just Dance to match this concept, but I will tell you that, "I’ve had a little bit too much…", is actually "… a little bit too much of boring lectures". So remember to Strike A Pose!
More and more I am posting little snippets to Twitter. Follow me: My username is aneesha
I am also thinking about using Twitter as a storytelling platform. Look out for a micro story called Escape. Its coming, I promise.
WikiEducator can export a collection of Wiki pages to an IMS content package, which can then be imported into Blackboard (or any other LMS). This is a great feature! Learning content can be authored collaboratively and versioned prior to be loaded into an LMS. Ah but should the LMS not support this by default? Wondering whether this is a feature Confluence could also support?
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