Using Onodo to Learn Network Analysis and Visualisation

During our seminar on Network Analysis and Visualisation in DH6010/6019 this past semester as a group we enjoyed a case study involving network analysis of the Star Wars characters presented by Evelina Gabasova ( She does a superb job of combining analysis, explaining her methodology, deriving some fascinating deductions – all with a fun cinematically familiar network. The familiarity combined with Gabasova’s well crafted blog posts really helped everyone grasp the basic precepts of graph theory and set up hands-on network visualisation instruction using Gephi.
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One of the challenges in approaching and using Gephi ( is that it has so much flexibility, power and such powerful capabilities that is can be off-putting for new users. The interface is not immediately intuitive and even with many of its panels minimised it tends to scare people off. It takes time and a deeper understanding of graph theory to appreciate its benefits and to be able to use it effectively – especially for analysis.

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Data Source Handbook: A Guide to Public Data

data source handbookThe Data Source Handbook by Pete Warden provides a concise and handy guide to some of the main sources of public data accessible on the web today. It’s a very short book of 40 pages. This in itself does not stand against the book. These sources are rapidly changing and compiling and committing an exhaustive survey to a printed volume would damn it to almost instant obsolescence. It would also prevent any treatment of individual datasources in any useful detail.


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Mining the Social Web by Matthew A Russell

mining the social web.gifIn Mining the Social Web Matthew A Russell offers to instruct in identifying social connections, trends in discussion and locations by tapping into social media data. He succeeds in spades. This fast-paced and rich handbook jumps right into the fray and provides an immediate and useful exercise in accessing the Twitter API using python and doing a very quick visualisation of trending subjects. I was hooked and greedily and immediately consumed a few more of his lessons. His approach is to go direct to real world applications of why you’d want to mine data from social media such as Twitter, Buzz, Facebook and utilise other freely available tools such as Google Maps to look for patterns and present solid research findings.

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Digital Nomadacity

The consistently thought-provoking Chris Brogan explores how current digital tools opensocial.jpgprovide for greater freedom in employment and life in general. Chris makes some prescient referrals to technologies and ponders why one should focus on being more mobile or consider being more nomadic. His post explores the equation from the perspective of the nomad. I wonder what the perspective is from the other side – from those that would consider the nomad’s services. He raises the critical question about data security and I wonder if this doesn’t extend to a larger question of trust. I have only rarely been on the nomad employing side of the equation, but even by appreciating the nomadic perspective, I am challenged to feel comfortable with the nomad. It’s not really about the results – or about my level of trust. I agree with Chris and with Mark Harrison who affirmed that the nomad should be paid for delivering results. What concerns me is the breadth of digital relationships. Continue reading

Viégas on Visual Analysis of Social Networks

What a treat! I had had the honour of meeting and spending the last two days chatting with Fernanda Viégas from the Visual Communications Lab. fernanda.gifHer work has been and continues to be inspirational for me personally and to the information visualisation community more substantially. She presented a tantalizing talk at the Social Network/ing conference at OISE/UofT. ‘Visualizing and Analyzing Social Networks’ quickly demonstrated a small facet of Many Eyes to a new audience and gave us a sneak preview of a new tool soon to be available through ManyEyes called PivotGraph. The logic of the PivotGraph is one of those ah-ha moments – it makes all the sense in the world, but leave it to Fernanda and Martin Wattenberg to visualize the problem, and come up with a brilliant way to solve it. Consider that social networks have traditionally been visualized in two ways: the node-link map and the matrix. The common to node-link method is very intuitive, but also becomes quickly cluttered and loses visualization value as the scale of the network being mapped grows. The second is the representative matrix, which scales very well, but sacrifices intuition for clarity. Realizing that there had to be a way of combining the strengths and minimizing the weaknesses, the PivotGraph hybridize these two forms using a collapsible node-link metaphor that, interactively aggregates like nodes and allows for focus on individual vectors. It’s nothing short of amazing to see in action! Continue reading

Goldfarb on Collabouration and BITnet

Avi Goldfarb presented a fast, concise and effective discussion of what conclusions could be drawn about multi-institutional goldfarb.gifcollaboration between US universities during the era of BitNET adoption, 1981 – 1990. A bit of internet history, my ears perked up immediately. His more general framing question: How do changes in collabouration cost change how we produce knowledge.
His study examined 270 institutions as they connected to the BiTNET during this period and cross-indexed this with the number of coauthored journal articles subsequently produced. Goldfarb’s paper ‘Restructuring Research: Communication Costs and the Democratization of University Innovation’ concludes that collaboration was enhanced, but that the gain to institutions was not uniformly realized and physical distance between collabourators remained a factor. Continue reading

Easterbrook on Socio-Technical Congruence

Despite technical difficulties (presenter’s worst nightmare – LCD projector bulb burnout), Steve Easterbrook demonstrated the usefulness of steve.gifcomparing software structures to social networks of developers to measure operational effectiveness. His well argued and logical presentation ‘Increasing Shared Understanding in Software Teams through Informal Knowledge Transfer Networks’ extended Conway’s Law to social network analysis. This technique of measuring socio-technical congruence is especially valuable in larger scale development projects, where it is probably less obvious about whether a development process is functioning effectivelly. By mining the data rich environment of communication and revision logs, it is possible to generate a social network map of developer interaction that can be connected to a software development schematic to determine Socio-Technical congruence. Continue reading

Is the Visible Network a Good Thing?

Social Network/ing Week at the University of Toronto kicked off tonight with a fascinating keynote by Cornell’s Jon Kleinberg. kleinberg.gif‘The Geography of Social and Information Networks,’ was one of the most fascinating applied mathematical lectures I can say to having ever attended (and before I go too far I will stress that the math was made very, very approachable for a layperson such as myself). His introducer indicated that he invented algorithmic sociology and although this sounded rather presumptuous (an Al Gore and the Internet sort of thing?), I can’t help but be quite willing to give this some credence after listening to this presentation.
Kleinberg opened with a quote from Jim Gray, that “the emergence of cyberspace and the world wide web was like the discovery of a new continent.” Kleinberg was quite deliberate in this juxtaposition of the geographic with the technological and he then teased this into a further merge with the social. But he questioned whether maps are actually an appropriate metaphor for something as aphysical as social networks – but chose to let this stand on the need to have some common vocabulary with which to be able to relate. Continue reading