Mining Twitter for Content

Take 14 minutes out of your day today or tomorrow and watch this video: Web 3.0 from Kate Ray on Vimeo. Is it sad that this excites me? I love Tim Berners-Lee’s last statement: “If we end up building all the things I can imagine, we’ve failed.” This coming from the “father of the World Wide Web”. The video really talks about now that we have all this information on the web how do we organize it and make it work for us? In the past week I’ve radically shifted the way I use Twitter, that more closely aligns with this new semantic web approach. It’s been an eye opening experience for me and once again I’m excited about the possibilities that are twitter. It’s very much about connections, and Twitter is a connection between people. I follow people who I believe will lead me to good content. But how do you know what that good content is in a stream that is over 3,000 people? That is where using semantic web tools such as Twittertim.es comes in. If you haven’t yet given this site a go….I strongly recommend it. We’ve said for a while now that the “cream raises to the top” and now with a semantic tools like Twittertim.es we have that. Basically what Twittertim.es does is make since of your twitter stream by collecting all the links that are being shared by those that you follow and gives weight to them based on the amount of times a link appears. Those links with the most tweets and retweets create your Twittertim.es style newspaper. The Twitter Times – Video Tour from Maxim Grinev on Vimeo. I no longer follow a stream of people, I use the people to lead me to the best content out there. Today I opened my twittertim.es page and the top 10 stories were all interesting to me. There isn’t another newspaper out there that could do that. This is completely tailored to my specifications based on the people I follow and the news they are reading and retweeting. Using this same idea, over the weekend I completely redid the decks in Tweetdeck on my computer. I deleted all the lists of people I was following and recreated decks around content. I’m now mining Twitter for the content that is relevant to me. At first I thought that I’d miss my lists of...

Read More