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I started using this app myself at about the time I started using Twitter, and it has helped me to understand Twitter a lot better. It's quite interesting how different types of tweets spread. E.g. this tweet

http://twitter.com/paulg/status/27959363780

got a large number of retweets but had a comparatively small total reach because it was retweeted mostly by hackers, who didn't have many followers. Whereas the retweets of this one

http://twitter.com/paulg/status/25998745559

generated a much larger total reach, presumably because it was about Twitter itself, and thus was retweeted by some community insiders who had lots of followers.

Maybe my experience is unusual because I happened to start using both at the same time, but I couldn't imagine using Twitter without Crowdbooster.




What's interesting about "reach" though is that it seems not correlated with influence, as in the test done by Christakis and Fowler http://edition.cnn.com/2010/OPINION/11/16/fowler.christakis.... So maybe your 1st tweet had much more "impact" (>number of retweets could already indicate that btw) even if much lower reach.

A 2cts idea on impact ('did it resonate with your crowd or cross the board'), staying on twitter (vs. if people did sthg you recommended to do like in their study 'buying a book') could be to see the n degrees of cascade retweets. Ie. if your direct follower retweet that's "level 1 retweets" if some of their own follower retweet "level 2 retweets" etc. to see if there is a cascade effect or not.


This doesn't strike me as a particularly surprising insight though and I think any serious twitterers would know this already. I've only written a few blog posts, but when I wrote about something popular (Google Prediction API) it got picked up by MIT's Technology Review. The other ones no one really cares about.

People seem to appreciate context more than raw data. If you can tell them the "whys" so you didn't have to presume, then you've got a valuable service.




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