What are your sources of information about the topics you care most about? Do you use an RSS reader to keep up with blogs or news sites? Do you rely upon the links posted, liked, tweeted, or shared by a circle of friends or authorities? Do you browse aggregator sites and curated collections of links on particular topics?
There’s a tremendous amount of reading material out there, and even when you’ve let go of the idea that you could “keep up” with it all, chances are good that you might be missing some things that would be of interest to you, if only you knew where they were.
Enter Trapit, (trap.it) a web service that combines machine learning algorithms with user-selected topics and filters. (The algorithms used in this project stem from the same research that led to Apple’s Siri.) After creating an account, you create a “trap” by entering in a keyword or short phrase into the Discovery box. Once you save your trap, you personalize it by clicking thumbs up or thumbs down on a number of articles in your trap. The more articles you rate, the closer attuned the trap becomes to the kinds of material you want to read.
That’s it. The trap fills up with web content, and can be accessed by logging into Trap.it and through optional daily, weekly, or monthly email digests of recent content in your traps. Using Trapit is the opposite of searching for something specific. Instead, you’re describing a general topic and seeing what shows up. But your individual preferences shape your trap, so two users with a trap set to the keyword “fitness,” for instance, may receive very different items in the trap because of how they’ve rated items.
Trapit integrates social sharing options for Twitter, Facebook, Google+, and Pinterest. An iPad app is under development and listed as “coming soon.” You can also mark items to be saved for later in a reading list, if you want to scroll through the trap quickly to clear out things you’re not interested in.
I’ve been trying out Trapit for a few weeks now, with traps set on a variety of topics. I’ve found it more useful for non-academic topics: my yoga and vegan traps have led me to many interesting articles I wouldn’t have read otherwise. Sources include news and commentary sites, magazines, and blogs from institutions and individuals. I also found the exercise of training the trap brought me additional awareness about my interests, which helped me define new and better traps.
The traps I set related to my academic interests, including Victorian literature and text mining, have been far less useful, in part because these are more narrow topics, and also because they often pull in sources that I’m already following in other ways. If your academic research focuses on technology, social media, popular culture, or other topics more heavily represented on the web, then Trapit might be a useful professional tool as well.
The one significant drawback for me in using Trapit is that there’s no easy way to put items from Trapit into my Instapaper account. When you open the article in Trapit, it opens in a viewer that doesn’t work with the Instapaper toolbar widget. The best workaround I’ve found is to copy the article’s URL from the upper left frame bar and manually add it into Instapaper via another open browser tab. That’s several more steps than I’d like to have to use to corral my Instapaper reading list together with my Trapit reading list.
But I’ll probably continue to check in on my traps once a week or so, because I have enjoyed adding new kinds of material to my personal reading list. If you feel that your online reading is getting stale from focusing on a limited number of sources, Trapit can open up your horizons very quickly.