Thanks for the feedback. The summaries are put in manually when the comment is posted, so nothing fancy. In practice one just has to remember to grab some text before using the bookmarklet (which fills in the rest).
A lot of people have said that the ragged bottom takes away a bit from the look and feel. There doesn't seem to be an easy way to fix that. The best I can come up with is to try and estimate the line height of each story, and if it exceeds a certain amount then truncate it, but only if it is on a page w/ other stories.
I'll play around with the top-top headlines idea. Is it inline with the look and feel of newspapers.
Thanks for the suggestions!
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Edit: The headlines are now bigger. It is better, thanks!
I moved them from 1em to 1.25em after trying it via firebug.
Regarding summaries, I think it would be possible to actually pull some text using Arc (although currently there seems to be no decent way to open a client connection, and certainly there don't seem to be any libraries for client-side HTTP). Of course the summarization would have to be done too. Hmm.
What I could do is if you use the bookmarklet, then it will pull in a best guess as to what the summary is and put it into the box. Then the user can edit that if they want. That wouldn't be too hard.
With ajax I could do the same thing once the user fills in the url.
IMO the hard part is the "best guess". ^^ I've been looking for papers about summarization and haven't found much. Hmm. Maybe look at the title and try to fetch words around words in the title, i.e. use the title's terms as search terms.
There is an easy way and a hard way to do it. For most articles, if you take the first element in the DOM that is a paragraph and contains above a certain number of words, then I am guessing that would most times be the leader paragraph.
The second easy way is to do the above most of the time, but have some site-specific things that are used instead.
You could also use some classifying software to ID the proper paragraph. You could have a training set of all the descriptions that have been on the site before, and find text that most matches that text, and use that. Or find the first bit of text that matches beyond a certain threshold, and use that.
The hardest way is to automatically generate a summary. I work in the automated document analysis business, and this is indeed pretty hard to do.
