Pre-script: iLike is the post series that I was planning to start lately. From this week onwards, on every weekend, I’ll be writing about the things that got my attention on that week. The iLike things that I’m going to write about will be mostly on the tech side. I’ll try my best to keep the focus on Java + Web + Design theme. But sometimes I might write about things that does not fit into this theme, too. In this week, I’m starting the iLike series with these three interesting things related to Twitter.
Please Rob Me:
No, not only me. It could be you also, if you are tweeting too much. Please Rob me is an interesting Twitter based application. These days, many people use Twitter service to update their current location. The application brings out the danger side of this behavior. Please Rob me monitors the public twitter statuses of people who are tweeting when they leave their home. It then lists those tweets in the site’s home page, as the opportunity(!) to rob. Seems funny, huh!? But the tweet could easily turn dangerous as it invites the local robbers to pay a visit to your home. So, think again when you tweet about your current location, here after. But first, do check if you are on the rob list.
World of Emotions:
World of Emotions (WEM) is another twitter based service that got my attention recently. Similar to the Please Rob Me, the WEM is also monitoring the public twitter statuses, but for other reasons. The service has several twitter bots (@wem_smile, @wem_glad, @wem_happy and @wem_love) which actively look for certain key words in your tweets. For example, the @wem_smile bot tracks the smiley words like ha.ha etc. And then it collects the similar tweets around the world to display them on a world map to collectively identify the emotion of the world. Plus, it retweets your tweet too!
Twitter Analytics:
With out a doubt, twitter messages represent the pulse of the web community at any given time. There are millions of tweets are already there in twitter database and the count is increasing rapidly every minute. This huge amount of data gives the wonderful opportunity for the data mining. If the tweets are analyzed properly, it could reveal interesting facts about several things. And that is exactly what Twitter Analytics team is currently doing. Recently, Kevin (@kevinweil) – a member of Twitter Analytics team, has published such analytics for the Super Bowl. And, this article from High Scalability discusses on how Twitter team uses technologies like Hadoop to prepare the Twitter system to analyze 100 billion tweets! If you are building a scalable systems, you might find this interesting.
So, that’s it for the week. I’ll come with more interesting things for the next week. Subscribe to this blog, if you want to receive the updates in your feed reader.
{ 0 comments… add one now }