Evolution+of+Privacy+on+Facebook

Magdalena Ho
 * //CCT470 Case Study//**

Link to Data Visualization: Evolution of Privacy on Facebook

__Evolution of Privacy on Facebook:__
 * [[image:magdalenaho/Content_is_attributed_to_Matt_McKeon.png align="center" caption="Content is attributed to "Matt McKeon""]] ||
 * Content is attributed to "Matt McKeon" ||


 * __Case Study: The Evolution of Facebook Privacy__**


 * Overview:**

This data visualization, titled ‘The Evolution of Facebook Privacy,’ was created by Matt McKeon. McKeon is a “Developer with Visual Communication Lab at IBM Research’s Centre for Social Software.” This is a radial-like graph that depicts, in nine categories, the increasing privacy default settings of Facebook over the years from 2005 to April 2010. It uses a logarithmic scale to measure audience. The potential audiences of this visualization are Facebook users, and people who are concerned about privacy on social networks. The sketch was created using Processing.js.


 * Strengths:**

__Design:__

The colour scheme is simple and matches with Facebook’s colour scheme of white and blue, which makes for good contrast. The typography used is non-serif font that functions for easy readability with small sized print.

__Effectiveness of Showing Data:__

This data visualization is effective because it shows visually how much Facebook privacy has transformed over the years (2005-2010 April.) It shows visually how Facebook’s default privacy settings are getting less and less over the years.

The time frame is non-linear. Statistics are taken at different points in each year, sometimes more than once a year. **UPDATE:** I feel as though the time frame is still effective, although non-linear, because there was a drastic change of privacy between November 2009 and December 2009.

Compared to typical graphs depicting the same information, such as this panel chart (Figure 2) as viewed on Chandoo], McKeon’s data visualization is more compact and compiled together that more effectively show the vast contrast between 2005 and April 2010. The panel chart uses the same statistical data McKeon used for his data visualization; "The Evolution of Privacy on Facebook."


 * [[image:magdalenaho/panel_chart.png align="center" caption="Figure 2. Panel Chart from Chandoo Website"]] ||
 * Figure 2. Panel Chart from Chandoo Website ||


 * Shortcomings:**

__About the Data:__

The data was presented utilizing a logarithmic scale. As read on Wikipedia, this scale is typically used when values of a large range (in this case, 100s and 1 billion) can be compared.

There are some broad categories, such as “the entire internet,” which could have multiple definitions. Also, some categories, such as the “Like” category, did not come into existence until half way into the data visualization.

The data that the graph is made of, is not completely accurate, as some data used included “personal memories,” and information “derived from [his] interpretation of the Facebook Terms of Service.”

Audience size was calculated based on “averages, interpolations of those averages across time, and guesses from my personal experience where that data was unavailable” as read on the Matt Mckeon website.

McKeon mentions that this visualization was implemented to be visually pleasing rather than accurately scaled.

__Compared to Other Data Visualizations:__

This data visualization is not one that requires much interaction of the reader. It can even be depicted as a still image visualization and the effectiveness would not be affected.


 * Improvements:**

A possible improvement could be that perhaps a different type of graph that more accurately portrays the data, as this one, as read on Matt Mckeon website, is distorted. If another type of graph was used, the parameter, or category “You” can be omitted. McKeon does update the graph as he finds more data, or gets data corrected, so improvements are ongoing. McKeon acknowledges changes through an Update feed on the right column of the Matt Mckeon website.


 * Conclusions:**

Keeping in mind that “The Evolution of Privacy on Facebook” is an ongoing data visualization project, this visualization is effective in showing contrast of data but the data itself may not be extremely accurate. This is because part of the data used included his “personal memories” and ”wild guesses.”

There is a column on the website that shows Updates ongoing for this data visualization. Updates include verification for some of the data used which makes the visualization more credible.