Archive for July 13th, 2010

A map of Team GWS on Facebook

Posted by Laura on Tuesday, 13 July, 2010

I love visualizing data.  It can make things so much easier to understand.  If you haven’t heard, there is going to be a new AFL team called Greater Western Sydney or Team GWS.  There are a number of Facebook fanpages and groups dedicated to the team.  I went to,, and  I created a list of everyone who belonged to those fan pages and groups and the networks that those members were part of.  I then counted the total members of each networks, identified the geographic location of each network, added the total number of people from a city together… and yay! I got the pretty map below.

View full map

People who know Australian geography better than me: Are the fans in New South Wales from western Sydney?

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Methodology: Draft/Free writing (part 1)

Posted by Laura on Tuesday, 13 July, 2010

One of the ways I learn best is by talking through a problem.  I compare and contrast things.  I ask people their opinions.  I read things to people.  I get into in depth conversations about practices.  I ask questions.   Write now, I’m in the process of writing my methodology.  At this point, I feel like what I’m really doing trying to outline the current practices in social media research, explaining how they are done and giving examples.  Once that is done, I can justify using a population study as the analysis process to help answer my research question and then go into a bit more depth regarding that.  Outlining the available methods seems important because the processes can be a bit different than traditional sociology methods.  Or at least, it feels that way.  This will be updated as I go along.  How often that happens depends on my motivation to write.


When conducting social media research, there are ten general methods that can be used to gather and analyze data.  These are:

1. Individual case studies for how a business uses social media and the web,
2. Search and traffic analytics analysis,
3. Sentiment analysis and reputation management,
4. Content analysis,
5. Usability studies,
6. Interaction and collaboration analysis,
7. Relationship analysis to try to determine how people interact and to identify key influencers, and
8. Population studies
9. Online target analysis of behavior and psychographics,
10. Predictive analysis.

Each of these methods offers insights into various aspects of the web and its population.  The type of analysis used is often specific to the purpose of the research, involved blended approaches from traditional analysis types, and different methods are often used in conjunction with each other.  These methods often blend quantitative and qualitative analysis.  Choosing the correct method of gathering analyzing data can be one of the biggest hurdles for being able to measure ROI and understand how a community works.
This section will provide a brief summary of each type, explain how to conduct this type of research and give examples that used that methodology.

Predictive analysis
A search on 13 July 2010 on SPORTDiscus had three results for “predictive analysis.” A search on the same date on Scopus had 605 results, 275 of which were in engineering, 132 in computer science and 102 in medicine. Predictive analysis is probably one of the least used analysis methods, especially in social media and fandom.
What is predictive analysis?  At its simplest, it is identifying a future event or events, monitoring selection actions that precede the event and seeing if those events can be used to predict the outcome of similar events in the future.  If a predictive value is found, an organization can monitor behaviors to help make more informed decisions.
An example of this type of research is “Predicting the Future With Social Media” by Asur and Huberman (2010).  Their goal was to determine if tweet volume and sentiment on Twitter prior to a movie being released could be used to predict how well a movie performs at the box office.  Their methodology involved identifying movie wider release dates that took place on a Friday, creating a list of keyword searches related to those movies, and using the Twitter API to collect all tweets and aggregate date that mention those keywords over a three month time period.  The authors then compared the tweet volume to box office performance.  They concluded that social media “can be used to build a powerful model for predicting movie box-office revenue.” (Asur & Huberman, 2010)
This type of research can be used in conjunction with other methods.  It can be used along side a population study to see if certain actions will result in demographic changes.


Asur, S., & Huberman, B. A. (2010). Predicting the Future With Social Media. Social Computing Lab. Retrieved from

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