I was searching for various intelligent filtering web applications and I came across the AideRSS service that has the tag line: "read what matters". I played around with it today and have come to the conclusion that I both like the model of the approach (makes sense) and the specific service itself (makes me feel warm inside).
The filtering model is constrained to a user-defined feed, in which each post is assessed based on it's "user engagement". Specifically, this is a social assessment mechanism they call PostRank that assesses each post in terms of the web-based contributions of others related to the post (so-called conversations), such as: comments, bookmarks, diggs, page rank, and so on. The tractability of the model is in its restriction to a single feed, and therefore the feed-relative scoring and normalisation that assigns each post a PostRank between 1-10 (I believe).
An early proposal of the per-feed model is described on Ilya Grigorik's (the project lead) blog titled: PostRank RSS Filtering. This model grew out his early assessment of the state of RSS filtering problems and solutions in a post titled: Reinventing RSS Readers. I like the simplicity of the model because it solves a different problem to the state of reader applications, specifically: what is interesting in a user specified feed (filtering), rather than: what is interesting in the blogsphere related to what I read (recommendation). The chosen model feels like an abstraction of the simpler problem of displaying popular or interesting posts on a blog (mentioned in the comments of the above post), although the use of broader social indicators is clever.
The core service is the application of the "user engagement" filter to popular high-traffic feeds (Slashdot, RWW, TechCrunch, Reddit). This is done by simply subscribing to a filtered version of a specified feed at the desired interest-level. Variations on this theme include the application of the filtering approach to aggregations of RSS feeds (filter the stream), and the integration into GoogleReader via a Greasemonkey-based plug-in.
Publishers (bloggers) can use the service to assess their content (see the state of NeverReadPassively), display a listing of interesting posts in a widget (I've included one on the right panel of this blog), and offer feeds of their work at various interesting levels (top, best, great, good, all). Finally, for developers the site provides an API, which some applications have exploited such as Lijit and integration into NewsGator RSS tools.
The site is built on ruby (back-end) and rails (front-end) and uses AWS (at least EC2). The service came out of private beta mid 2007 and since then has received support in the tech-press including: a review on Slashdot, a review on RWW, hype regarding the GoogleReader plug-in, and hype regarding funding. There are many approaches to RSS filtering and applications that claim to possess similar features (fav.or.it and thoof for example), although the standout features of this service in my eyes are as follows:
- It is free
- It does not require a user context (no lock-in!)
- It is simple
- It does what it claims to do (qualitatively well!)
Blog and Post-based widgets are good for publishers and would help promote this cool service virally. Regarding widget customisability, the present state of the widget does not display properly on my blog (cannot read the PostRank scores), so I had to right align the thing (ugly but readable).
The social-basis for the ranking algorithm means that there may be a delay between post time and bubble up time. Rather than a negative, I like this feature because like social news, old topics can resurge and break through to the front page (filtering levels). In this way, the chosen model allows each feed to be treated as it's own isolated social news site, presumably reassessed daily by the AideRSS systems. It would be interesting to see for example how the reddit front page compared to a filtered version of the raw-story submission scheme (whether reddit conversations correlate with broader conversations). Anyway, I think I may have a tinker with the API.
4 comments:
I have observed an interesting behaviour in myself of late. I am checking out how each post is positioned in the AideRSS listing rather than checking Google analytics. This is a shift in monitoring from page views and related metrics to social impact, something that means a whole lot more. Perhaps there is something there. An elaboration of Technorati's reactions (more) as a set of post/site metrics.
I have recently being trying out the AideRSS GoogleReade plug-in. Very nice. What is interesting is that they are using the private beta as a controlled mass-feed modelling approach, slowing building their feed index. (obviously in addition to usage on their website and newsgator) clever.
I got a note from Mark suggesting two additional intelligent RSS filtering applications, as follows: FeedZero a free service that uses a Bayesian model (Naive Bayes?) to filter content and requiring training, and Shrook that provides an offline application (Mac) along the same lines.
Jason, thanks for the great feedback and suggestions for improvement! To address some of your comments:
1) Can you elaborate more on ways you’d like to customize the widget? Are you referring to links colors, background?
2) We’re working on an interactive version of the sparkline. If you’re willing to do some beta testing, ping me. ;) (ilya at aiderss dot com)
3) Great idea, on the embedded PostRank widget – we’ll work on that.
Last but not least, let me know what the problem was/is with the widget, we’ll fix the layout!
Cheers,
Ilya
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