Tag Archives: Visualisation

Visualising The Worth Of Facebook To The Individual

What Is The Worth Of Facebook To The Individual? What’s A Simple Way To Collect Data On This Topic? How Do We Then Visualise That Data?

Social media plays a big role in our daily lives – keeping us connected with friends and family, formulating into our everyday routine, providing a platform to be mentally and socially active, and allowing us to create and maintain our online identity and online citizenship. But how much is Facebook really worth in the eyes of users?

For my ARTS2090 Visualisation project, my group and I decided to visualise ‘The Worth Of Facebook To The Individual’. In particular, I wanted to see what the affects on usage of the social networking site would be if the whole site itself, or several of its features, were hidden behind paywalls. We know that the Times now implements an online paywall for its articles and content, but what if social networking sites were to adopt this practice? Would YOU boycott Facebook if it hid behind a paywall? How much do YOU value Facebook?Paywalls are seen as a boundary to publishing, especially when the nature of the internet is to share information. In one of my earlier blog posts The Affects On Paywalls On Digital Publishing And What It Could Mean For My Own Publishing’, I looked at how paywalls would affect the way we publish information, in particular in regards to news content and social networking. A “voluntary sharing and exchange of information for the purpose of connectivity” (Ibrahim 2008, Nardi 2005). Also, as Facebook plays such an important role in the lives of many, how much do they value it? Are they dependant on it. Using new-media has become a ‘Media Ritual’ (Couldry 2003).

Sample of the design of our survey

So, my group, consisting of Kady Holt, Jana Malos & I, set off to collect data in order to visualise the worth of Facebook to individuals. How did we go about collecting the data? The easiest data collecting tool that we found, and that a few of the other assignment groups used was the simple question survey. We created a survey on, consisting of 9 simple questions, each with different answering methods such as as ratings, choosing one answer, choosing more than one answer, written responses, etc.After creating our survey, we published the links to it via Facebook so that we could get Facebook users particularly around the same demographic as ourselves in order to obtain the data. Once we had gotten 100 responses, we closed the collection links, and then Survey Monkey analysed our data for us.

Sample of how our data was analysed after collection by Survey Monkey. (Click On Image To Enlarge)

The next step was to visualise this data, and compile the visualisations together in one format. So here are the slides containing the visualisations of the data received from our 9 questions:

I’ll quickly explain 2 of the visualisations I created:

The question we asked our respondents was ‘Which Facebook Feature Do You Most Value?’. As respondents could only choose one answer, the results were easy to visualise. So, sticking to our Facebook theme, I decided to emulate the act of “liking” a certain status or page on Facebook, and visualised the data this way. As such, “Wall Post – 41 people like this” = 41 people said that this is the feature they most value. For the “Other” response, created my version of “commenting” on a status. Respondents could fill in an answer box what they value that wasn’t part of the initial options, hence the “commenting” visualisation.

We asked users what their intentntions were when posting information on Facebook, and they could choose more than 1 answer, hence the numbers. Using paint, which I did for all each of my 3 visualisations, I created this little men with different expressions that correspond to the intention, and then one added to the powerpoint, I then made the speech bubbles. It’s a unique way to publish and visualise data, but one that I thought suited this question.

Overall, we visualised data about an important topic in social network and publishing, and looked at a new way of publishing data through visualisations. Every aspect of this visualisations – the colours, images, texts, variables, etc – are important, like the Actor Network Theory suggests. All these elements combine to best represent the data and emerging patterns in ‘The Worth Of Facebook To The Individual’. Furthermore, the publics that would find this information useful, Facebook users, non-users, and the Facebook/Social Networking companies have here some basic models to understand just how much individuals value Facebook.


  1. Couldry, Nick. “Media Rituals: The Short and the Long Route.” Media Rituals: A Critical Approach, London, Routledge, 2003, pg 1-20
  2. Ibrahim, Y 2008, ‘The new risk communities: Social networking sites and risk’, International Journal of Media & Cultural Politics, vol. 4, no. 2, pp. 245-253.
  3. Nardi, B.A. 2005, ‘Beyond Bandwidth: Dimensions of Connection in Interpersonal Communitation,’ Computer-Supported Cooperative Work, 14: pp. 91–130.

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Visualizations (Making The Invisible Visible) & How They Enhance Debates On The Issue Of Climate Change

How Do Visualisations Aid The Communication Of Science Within The “Public Sphere”?

Amidst the continuous Climate Change debate, more and more data from both the “Climate Skeptics” and the “Scientific Consensus” is published. There is so much information from each of the respective publics being added to the ever-growing flow of data, and a lot of it may seem invisible to us. So how then do we go about making the “invisible” data “visible”? We “Visualise“.  Visualisation enables us to discover the unknown, to make the invisible flows of data visible, through the use of images to structure new relationships, and exemplify and identify existing patterns of data.

The “Scientific Consensus”  publicise their data in scientific journals & textbooks, public or university lectures, books, through graphs & visuals, websites, newspapers, mainstream media, etc. “Climate Skeptics”  publicise through lectures, websites, blogs, newspapers, mainstream media, visuals, videos, etc. There’s so much information being published that even if you have a particular stance towards Climate Change, understanding all the arguments isn’t always easy, nor is it easy to bring all that information together so a proper debate can be had.

Even the portrayal of Climate Change issues and perspectives in the media can be biased. Power & personal opinion  editors or owners of media organisations have an influence on what type of information is published, and thus influences how the public debates issues. Newspapers or forms of media may publish a more favourable amount of “scientific consensus” perspective articles/editorials as opposed to “climate skeptic” perspective articles, and vice versa.

As such, for people either of a particular stance towards Climate Change, or looking to develop a broader understanding to help shape their opinion, they need a way to have both perspectives & arguements brought together. This is where an amazing infographic visualisation entitled ‘Climate Change Deniers vs. The Consensus brings together arguments from both perspectives in this big graphic of both text and images about the issue of Carbon Dioxide influencing Climate Change. It was created by David McCandless in December 2009, and is published on the great infographic site, Information Is Beautiful, where “ideas, issues, knowledge, data [are] visualised”. The graphic is huge, so I’ve cut it up into particular sections to make analysing it easier, but to view all of it & and a whole, just click on the link two sentences above! Why not have a read of the arguments as you look at the pictures too!

The layout of the image presents the “Climate Skpetics” perspectives on the left side of the visual, with their argument/thesis made bold and clear in pink. The “Scientific Consensus” perspectives are on the right with their argument/thesis made bold and clear in green. In the “Global Warming Skeptics vs The Scientific Consensus” section that begins the visualisation, the clear arguments of both sides are presented in text so that they can not only  be clearly identified, read, and understood, but be presented in a way that signifies equal importance. The first opposing arguments centre around the relationship between CO2 emissions and rising temperatures. You have the two arguments each on their respective side with their respective colour, and as well a graph in the middle that both sides can relate to, or draw their arguments from. This is the layout for issue/section of the infographic: 



As you can see from the above pictures, different types of graphics are used, including graphs, maps and scientific diagrams. A combination of text, colour and dynamic visuals enhance visualisations enhances the experience for those who learn better through text, and those who learn better through visuals. The graphic diagrams in the centre of each opposing arguments gives the viewer data to aid in developing their own opinion/understanding.

This visualisation not only presents a series of arguments for both the “Climate Skeptics” and “Scientific Consensus” in a fair and equal weight, but uses various resources for its images and information, as most images are reference. A conclusion to both arguments is provided at the bottom, so in fact, you have a whole debate all in this one infographic. The “Climate Skeptics” conclude that Man made CO2 cannot be driving Climate Change, whereas the “Scientific Consensus” has the opposite conclusion. But along the way, both arguments have been supported by evidence & graphics to further both arguments. At the bottom you have the sources used for both sides arguments, and a link to further sources.

As such, this amazing infographic visualisation allows for an easier understanding of the debate about Climate Change by taking an objective stance and equally presenting both perspectives. The author looked to simulate what is was like researching Climate Change online.  Henceforth, visualisations don’t just transform how data is published, they can bring together differernt froms of data into one piece of publishing. It’s a good example for future visualisations depicting information on Climate Change.

* All Images are adaptations of the original image found belonging to, and found at


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Posted by on April 24, 2011 in Week 9 Tutorial 8


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