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An NRL social media / web data pack

Posted by Laura on Saturday, 11 December, 2010

Draft: An NRL social media / web data pack.

On Wednesday, I started to consolidate my social media and web data into a packet. My intention was that it would be similar to the packet I did about Australian and New Zealand’s women’s sport fan communities. That packet finished at 108 pages. For the NRL, I’m up to Facebook and I’m about 90 pages in. I believe I probably have another 100 to 200 pages. For the moment, I’ve decided to stop working on my NRL packet. I need some feedback and to determine if this information is useful and worthwhile.

Draft: An NRL social media / web data pack.

Some context (or explaining my thoughts): The women’s packet was very important from my perspective. There isn’t a great deal of research being done on women’s sport fandom in the region. There appears to be even less understanding as to what various sites mean to women’s sport. The community for women’s sport is also much smaller. The situation with the NRL is different: There is more research being done about the league and the fan community is that much larger. Where an Australian female athlete (or team) may have one or two Facebook fanpages dedicated to her, NRL teams are more likely to have about 40. Where an Australian female athlete (or team) may be lucky to have a world rank on Alexa for her site, most NRL teams rank in the top 100,000 Australian sites. Because of this, Alexa provides information about their audience.

I’m rambling. Long and short: Not much being done for women’s sport. More being done for NRL. Not much data for women (often containing 0). NRL has huge community leading to data glut.

The data glut is probably where I get frustrated. The women’s data I can contextualize a lot better. The NRL data is much harder for me to contextualize and provide a narrative to what is happening with the data. There is also such much of it that it feels overwhelming and it is much harder for me to offer explanations as they are hard for me to see when I’m looking at this data. This is coupled with the fact that in providing the raw data, there is a battle about providing framework to explain the methodology, to explain patterns, to explain site usage patterns, to make this data more relevant… and to just provide the data. If I do the first, it makes packets even longer and it takes a lot longer to put the packet together. If I do the second, the data potentially becomes less useful as people are less likely to understand what they are looking at. (The packet itself, just based on sheer size, probably would make that second problem even worse.)

If I’m continuing with the packet, I have the following sections I could add data for:

  • Facebook group/fanpage growth.
  • Facebook demographic data.
  • Facebook network membership.
  • Facebook posting patterns by clubs on their official pages.
  • Flickr image totals by date.
  • Flickr group totals by date.
  • Flickr group stats by date.
  • Foursquare checkins by game.
  • Friendster profile interest totals by date.
  • Gaia Online profile interest totals by date.
  • Gaia Online profile demographics by date.
  • Google search result totals by date.
  • Google Trends.
  • Gowalla checkins by game.
  • hi5 profile search result by date.
  • hi5 group information.
  • IceRocket total posts for past three months.
  • LinkedIn search result totals by date.
  • LinkedIn group information.
  • LinkedIn company information.
  • LiveJournal (and clones) profile demographics.
  • LiveJournal (and clones) interest listing by date.
  • LiveJournal (and clones) community information.
  • MySpace search results by date.
  • Orkut search results by date.
  • Picasa image totals.
  • Trade Me listings by date.
  • Twitter follow totals by data.
  • Twitter data using Tribalytics.
  • Twitter followers by team by city.
  • Twitter follower count for NRL combined by city.
  • Wikipedia article views by month.
  • Wikipedia (and Wikia) article edit counts.
  • Wikipedia (and Wikia) article edit counts by location information.
  • Yahoo!Groups posting volume.
  • YouTube uploader demographics.
  • YouTube video statistics.
  • YouTube total search results by date.

In the end, will anyone use this? Do my readers think it is worth investing another week or two and trying to complete this?  Is there anyone who would be interested in the completed packet that I could send it to?

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