Aggregating

published

The value proposition of social media sites like Twitter has always been somewhat vague to me. I’ve stated before that I’m skeptical of social media, and that I’m not one to jump on social network bandwagons. I recently purged a bunch of people from the list that I follow on Twitter because I wasn’t seeing any value to reading what they had to say. There’s only so many hours in the day, and I’d prefer not to spend them reading about what other people had for lunch.

I know that part of my problem with aggregating too much information is the workflow I use. I’m extremely linear when I process things: I work from oldest to newest when reading news in Google Reader. It’s only in the last couple of months that I’ve started marking whole categories as read, even if I hadn’t read them: “if I’m not reading them, why am I aggregating them?” is the question I ask myself. When I reload the Twitter home page, I scroll down to the last thing I read (or the bottom of the page, if I’m that far behind) and then work my way up. I rarely page back to see items pushed off the home page. I use the Twitter home page because I haven’t found a dedicated Twitter client I like.

But the thing that’s really stuck in my craw right now is duplication of information. Most of the people I follow on Twitter are also people included in my list of feeds in Google Reader. Whenever someone posts a new blog entry, there’s almost always a Twitter message declaring that fact (our software automates this for us). I almost never click the link from the Twitter message to the blog post, knowing that the post will eventually be picked up by Google Reader for me to review. Most of the people I follow on Twitter also tweet enough other stuff to make it worth continuing to follow them on that service. A notable exception is, interestingly, CrunchGear: the overwhelming bulk of the CrunchGear tweets are simply the new posts that have gone online. Since I’m aggregating CrunchGear in Google Reader anyway, what’s the value in following them on Twitter?

I could, of course, aggregate the Twitter feed(s), so that Google Reader is my sole source of incoming information. But I’ve noticed a pretty big lag in Google Reader most days, such that a tweet posted early in the morning by someone might not be displayed to me in Google Reader until mid-afternoon. Most of the time, this might not be a big deal, but every now and again someone will tweet something that merits an immediate response: either a question for which I know the answer, or a request for a recommendation, or even an invitation. These things can be time sensitive, and I’ll have missed the window of opportunity if I rely on Google Reader catching them and displaying them to me.

It’s this delay that also prevents me from using something like Yahoo Pipes to create some kind of filter to weed out the extraneous bits, so that I can focus on the compelling data from each disparate service I use.

The thought that started this little tirade was the idea that I might integrate my Twitter posts directly into my blog, in a fashion similar to Chris’ lifestream. Rather than a dedicated page, though, I would simply grab my tweets and store them as a new Habari content type for display alongside my normal posts. I could then also include my Flickr photos, and whatever else I wanted, making the front page of my site the complete clearinghouse for all my online activities. Then folks could simply aggregate one site to follow what I’m doing.

It’s a nice idea, but it fails in execution. In addition to the delays noted above for feed readers acquiring new data, the convenience of replying on Twitter is made more complex: a reader would have to see in my feed what I had posted to Twitter, then go compose their reply either at the Twitter site or in their Twitter client. Similarly for commenting on my blog, or on any Flickr photos I posted: following the lifestream is just one piece of the puzzle. Interacting with the information presented in that stream is the next hurdle.

What do you think? How would you like to simplify and integrate interactions with aggregated information?


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