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 an updated version of from November 13 , November 16 and November 18.

If there is anyone missing, please let me know. I’m always happy to improve this list. I feel like there are probably more roller derby accounts out there that I’m missing. I also feel like there should be more Kiwi women on the list that I’m just not seeing. If anyone knows a good place to begin to find either group, please comment.

If anyone wants the list of followers for these accounts and all the public information that you basically see in the list below, please let me know and I will be happy to send you a csv file containing that information. I’m just hesitant to upload it as I only have so much bandwidth and I have about 805 files with follower information.

The biggest movers on this list appear to be ItsStephRice, RochelleGilmore, Sally_Fitz, gypsy_gilmore, libby_trickett who have all gained 50+ followers. This contrasts with kristy_giteau, MelissaBreen_, muirsop, TheFlyingBats, saltydolls, samikennedy, SportingSheilas, watsonjessica who all lost between 1 and 3 followers, which if you think about it isn’t that many followers.

Related Posts:

• Most popular Australian (and New Zealand) sport related Twitter accounts (November 24)
• Most popular female Australian (and New Zealand) sport related Twitter accounts (November 18)
• Most popular Australian (and New Zealand) sport related Twitter accounts (November 18)
• Most popular female Australian (and New Zealand) sport related Twitter accounts (November 16)

Yeah, it is that time again! I’ve added about 10 new accounts to this list. They were mostly journalists, people I saw referenced on my Twitter feeds or people that were mentioned in the comments of my previous post. There are a few that where the accounts to have been deleted or otherwise just did not get counted and those are just left off this list rather than be signified with a 0. This is an updated version of Most popular Australian athletes, clubs, leagues and sport organizations on Twitter (version 2), October 4 and October 11, November 11, November 16 and November 18. If I’m missing anyone or anything, let me know.

For probably 99% of these, I have a list of all the person’s followers. If you want to see that information, please let me know and I will be happy to send you the csv with that information.