Michele Martin asked how I did the comment analysis to see which posts have generated the most conversation. This is task 18 in the comment challenge. I actually manually typed the numbers into OpenOffice Calc (after scanning the list of posts in my WordPress dashboard for posts with a decent amount of comments). However, there is a faster way to get a “quick and dirty” analysis of your comments and conversations.
AideRSS is a tool that lets you filter a feed for the “best” posts. It ranks your posts by how much conversation they have generated, based on comments, del.icio.us links, tweets, Diggs, and Google trackbacks. Enter your URL and let it do the analysis. View the “Top 20” to see what they consider to be the best conversations.
For blogs that have been going a while, this isn’t ideal as an overall picture. It doesn’t go back far enough in your history. My Top 20 goes back to last July, but I think that’s because I actually played with this tool previously. Michele’s Top 20 only goes back to February 26. When I checked hers today, it let me know that they had never analyzed her blog before. I guess the first time it only goes back 90 days. It would let you know about recent activity though, and for a newer blog it wouldn’t matter.
AideRSS is actually designed to let you filter sites with lots of post to just get the “cream of the crop,” but I think it would work for the challenge. I’m sure some blog hosts have a good way to do this already, but I don’t think WordPress has anything built in to see stats on comments.
If you know of another way to get a quick and dirty analysis like this (without installing Google Analytics or something similar), let me know. I’d love to hear about it!
Hi Christy–thanks for the suggestion to use AideRSS. That’s definitely a quicker way to do things. Although as you say, it only goes back to July 2007, in my case I don’t know that I had a ton of posts with lots of comments before then. What would be great is if you could rank by number of comments or number of del.icio.us saves because I’ve found that those don’t always go together. I’ve had several posts that generated relatively little conversation but lots of saves to del.icio.us and vice versa.
Strangely, I have analyzed my blog there before–not sure why it made it look like I hadn’t. Thanks for the tip!
P.S. I ended up looking at my “best” posts (the top 28%) because the top 20 were based on more than just comments and in looking at the best posts, I got more posts with comments.
I wonder if I did a different variation on the URL than you did for your analysis. That could explain why it said it didn’t recognize your site.
I’ve had posts that didn’t get comments but have been bookmarked, too. I also noticed that AideRSS picks up scrapers as trackbacks, which artificially inflates my Synergy features post in their ranking.
Looks interesting – could certainly do with something like this for my social media/tech blog reading. I’ve been using Particls but found it just too intrusive and frequently feeding me articles I’d already read days previously.
I haven’t tried Particls. Actually, although I’ve known about AideRSS for a while, I haven’t really been using it myself. I have thought about offering it as a link on my site though. It effectively filters out most of the bookmarks posts.
It’s probably something I’ll experiment with more after this comment challenge is done. I subscribed to the “best of” feed for my blog just to see what it picks up and how it works.
Hi Christy – Currently feeds analyzed only go back to last July because that’s when the functionality was first put into production.
For those who want the biggest possible picture of their stats, we can clear the feed in our system and run the analysis again, if the feed settings have been changed to give us access further back. We haven’t automated that yet simply because there haven’t been that many requests for it.
Hope that sheds a bit of light. Please feel free (Michele, too) to give me a holler if you’d like older stats included, or have any other questions or suggestions.
Thanks for the explanation Melanie. That makes sense; Michele did say that she had used the site before, so that must be why it picked up the February date. I can see that most people wouldn’t actually be looking for stats farther back. Your service is more about filtering than analyzing; it just happens to have this nice side effect for analysis.