Ozzie Sport

And just to mix it up today and support the idea that I actually do write things, this would be a draft of some methodologies that will be headed into my appendix. A lot of it feels really simple, already gets stated inside existing chapters as I use the data and would eat up word count in my methodology in a really unhealthy way. (I’ve got about 20 of these methodologies to do. I should really do a summary about each particular site I’m using too. We’ll see. This section first.)

Appendix A
Data Gathering Site Specific Methodologies

43 Things
User information
To get user information from 43 Things, the first step was to identify goals that related to an Australian or New Zealand based sport club.  Searching using various keywords, reading the goals that related to the keywords and determining if they related to the search accomplished this.  Once a goal was identified and people were identified as having completed the goal or intending to complete the goal, the goal was recorded on a row in a 43 Things specific spreadsheet.  In a separate column, the team and league to which the goal related to were also recorded.  After this was completed, the user pages for people with that goal were visited.  Their username, city, state, country, birthday, website, and date joined were all recorded.  The last notation to the row was to include the date that this information was gathered.
During the time that this data was gathered, 43 Things changed the information that was available on the profiles.  This was done sometime between early June 2010 and  early November 2010.  Subsequently information such as city, state, country, birthday, website were not available on user profiles.  Only data gathered prior to this time exists except in cases where the data was checked at a later date and the user’s information had previously been recorded.

Total user information
Attempts were made to benchmark the level of interest in a team by recording the number of relevant search results on 43 things.  This was done by documenting the league and team that were being searched for in a row.  After that, the keyword used for the search was recorded in the same row.  The search was then completed and the total results were recorded.  A textual analysis of the search results was conducted and the total number of relevant results was recorded.  Of those relevant results, the total number of people working to accomplish them was then recorded.  Finally, the date the search was conducted was recorded.

Alexa
Site rankings
A list of websites related to Australian and New Zealand sport was created.  This was recorded on a spreadsheet, with columns that listed the league and team that the domain featured.  For every domain on the list, the page about the domain on Alexa was checked.  The Alexa page URL for the domain was also recorded on the relevant row.  When visiting the page, the world rank was recorded.  If an Australian rank was also available, it was recorded in a separate Australian specific column.  Next, the date that this information was gathered was recorded.  After that, any notes the author had regarding the site were recorded.  This was mostly to identify the type of domain or if it ranked in a country outside Australia.  Lastly, in some cases, the paragraph of information provided by Alexa regarding the site’s traffic and demographics was recorded.

Bebo
User  information
Profile information from bebo users was gathered by running a search related to a specific team or league.  The league and team that the search was related to was documented.  Once this was done, the people search results were copy and pasted to Notepad.  The search results were then formatted for pasting to the bebo user spreadsheet. Once copy and pasted, the author attempted to convert user-inputted locations into real locations of city, state, country.  The location field results were then found in columns for city, state, country instead of a location column.  The columns that existed then were league, team, name, gender, age, city, state, and country.  A final column was added that recorded the date this data was gathered.

Videos, Groups, Band information
There are three different search tabs on bebo beyond people that have information about the community size and audience for Australian and New Zealand sport.  They are Video, Groups and Bands.  Searched related to a specific team, player or league were run.  The relationship between the searches and the league and club were recorded.  The search results were then copy and pasted to Notepad where the results were formatted so they could be pasted on to a separate bebo related spreadsheet.  Once this was done, the following headers where information could be found included type, total (fans/viewers/members), loves, profile views, group created, genre, city, state, country, uploaded, uploader, and description.   The city, state and country information was documented using the same methodology as the bebo profile information.  Finally, a column was added that included the data that this data was gathered on.

Total search results
Total search results data came by recording the search term used, and recording the team and league that connect to that search term.  Once that was done, the total results were recorded for People, Video, Music, Groups, Apps and Skins. The date the search was conducted was then recorded.  Finally, any notes regarding the search or its results were recorded.
When recording the results, in almost all cases, the total results were included.  In a few select cases, generally when the results were 20 or less, the total number of results deemed relevant were recorded.  This was deemed important for smaller sport fan communities where one or two videos or groups may represent the whole community.  An example search where this was done involved a search for “Giants Football Club” because the results picked up rugby league teams and the New York Giants.

BlackPlanet
User information
User information was gathered once a search had been conducted and resulted in a user appearing.  If a user appeared for that search, the league and team related to that search were recorded.  The user name was then recorded.  The user page was then opened and the following data was collected: Country, gender and age. Lastly, the date this information was gathered was documented.

Total user information
To gather total user information, a search phrase was thought of and recorded.  In separate columns, the league and team the search related to were recorded.  The profile search was then conducted and the total number of results were recorded.  Finally, the date the search was conducted on was recorded.

Blogger
User information
User information was gathered once a search had been conducted and resulted in a user appearing.  If a user appeared for that search, the league and team related to that search were recorded.  The user name was then recorded.  The user page was then opened and the following data was collected: Age, Gender, Astrological sign, City, State, Country. Lastly, the date this information was gathered was documented.

Total user information
To gather total user information, a search phrase was thought of and recorded.  In separate columns, the league and team the search related to were recorded.  The profile search was then conducted and the total number of results were recorded.  Finally, the date the search was conducted on was recorded.

Related Posts:

• Socceroos: A creative research data dump (part 1)
• Distribution of Australian sports fans by league and location
• The Impact of Jason Akermanis’s Comments on the Western Bulldogs’s Online Fanbase
• Data absent context can change the meaning: Did Julia Gillard hurt the Bulldogs?

This is the last of my data dumps from this weekend.  I’ve heard that the penetration of the Alexa toolbar in Australia is really low.  Given that, these numbers are probably less than reliable.  Still, given the absence of other public data, you work with what you have.  This is one of those cases.  Because of some issues, this only includes NRL and AFL urls.  (My actual list is a bit longer and includes more teams.)

Related Posts:

• More popular Australian (and Kiwi) sport related Facebook fanpages and groups (November 23)
• More popular Australian (and Kiwi) sport related Facebook fanpages and groups
• Most popular Australian athletes, clubs, leagues and sport organizations on Twitter (October 11)
• Most popular Australian athletes, clubs, leagues and sport organizations on Twitter (October 4)

I’ve been some what lax with collecting data during the past month.  This morning, I decided to remedy this a bit by updating my Alexa rank list for Australian sport clubs and teams.  This is what can be found below.  (The list isn’t all comprehensive.  I tend to mostly focus on the AFL and NRL.) It is interesting to see who is doing well, especially when compared to other clubs in the same league or clubs playing in the same geographic area.

Related Posts:

• Most popular Australian athletes, clubs, leagues and sport organizations on Twitter (October 11)
• Most popular Australian athletes, clubs, leagues and sport organizations on Twitter (October 4)
• Most popular Australian athletes, clubs, leagues and sport organizations on Twitter (version 2)
• Most popular Australian (and New Zealand) sport related Twitter accounts (November 16)

I’ve been busy collecting all sorts of bits of random, creative data for the Socceroos in the lead up to the World Cup.  There is a whole lot more that I want to get but I’ve only so much time.  And time is what is holding up my ability to do an analysis prior to the World Cup regarding what some of this data could mean.  I figured I would share it so that others like you might use it to do your own analysis.  Just a word of caution: Random data is random.

43 Things
This data was checked again on June 12, 2010. These are all the questions where people mentioned Socceroos. They were found by searching 43 Things for Socceroos.

Alexa
I’ve been getting data for other sport teams since early May. It took me a long time to consider adding this one…

Bebo
I wanted an idea as to the demographic make up of fans. Bebo data is often the easiest to get. (And it didn’t close down like it was rumored to have on June 1 if AOL didn’t find a buyer. Yay!) The other benchmark is for the change in total people listing them as an interest or related keyword.

Changes in interest listing on bebo

Black Planet
It isn’t entirely surprising that no one lists the team as an interest on Black Planet.

Blogger
At some point, I will get demographic data off blogger…

Care2
Included the All Whites. They tend to pick up a lot of irrelevant data.

Compete
Tracking your traffic… only limited information, and month by month. If you pay, you get access to better data. I can’t afford it so limited is what you get.

Related Posts:

• Appendix A: Data Gathering Site Specific Methodologies (draft 1)
• Online Activity in the Wake of the Melbourne Storm Controversy
• Most popular Australian (and New Zealand) sport related Twitter accounts (November 24)
• Most popular Australian (and New Zealand) sport related Twitter accounts (November 18)

I was curious as to which team had the most popular website in the AFL.  There are three places to get this information: Quantcast, Alexa and Compete.  Each has various advantages and disadvantages.  In this case, I chose Alexa as I can get the rank of a website in Australia.  I can’t get that information using Compete or Quantcast. Alexa has its issues and I can’t translate this into real traffic numbers but it is the best option. While doing the AFL, I wanted to look at some other teams to see how they compare.   These ranks date to today, June 5, 2010.

This list is not comprehensive.  It does not include every major team in Australia.  At some point in the future, I’ll update this list and it will be more comprehensive but just not today.  That AFL teams generally are near the top, NRL teams coming in just below them.  The NBL, W-League and A-League are scattered around in the bottom 2/3rds.  As these leagues are not currently active, that can offer a bit of an explanation.  These leagues also draw smaller crowds, which also goes to explain their comparatively low ranking.

Related Posts:

• Alexa rank for Australian leagues and clubs
• Most popular Australian athletes, clubs, leagues and sport organizations on Twitter (October 11)
• Most popular Australian athletes, clubs, leagues and sport organizations on Twitter (October 4)
• Most popular Australian athletes, clubs, leagues and sport organizations on Twitter (version 2)