As I did last year, I’ve set up Martin Hawksey’s Twitter Archiving Google Spreadsheet (TAGS) to cover this year’s Code4Lib conference twitter hashtag. This is a really neat tool that comes with its own dashboard, links to various visualizations, and access to the complete archive so you can make up your own derivatives.
Martin has also created a couple of visualizations of tweets based on the archive:
The archive is updated automatically every 5 to 10 minutes.
Earlier this month I found myself apologizing for some errant tweets that ended up in my Twitter stream1, and realizing that I had fallen into a pattern of sorts thought it would be useful to document. (This post, too, will be a good one to use as the ‘website’ link on my Twitter profile.) So here it goes. If you are following me on Twitter, these are the things you’ll see, in order of probability — from most likely to least likely.
Over the weekend I got the bright idea of asking OmniGroup to ask an iPhone voice recognition application (like Dragon Dictation) to add a link to the OmniFocus iPhone application. That way I could simply dictate new inbox items on the iPhone rather than laboriously typing them with the on-screen keyboard. Before making the suggestion, I searched the OmniFocus User Forum for “voice recognition” to see if anyone else had suggested the same thing. As it turns out, there were a few posts that had instructions from people using Twitter as an intermediary. Unfortunately, they either required a desktop Twitter client to be running all of the time or used the now deprecated BasicAuth-based Twitter authentication scheme. So I created my own.
Emily Clasper of the Suffolk County Library. This sounded like a really great idea because it is an out-of-band (e.g. something that doesn’t rely on OhioLINK infrastructure for reporting downtimes) way to get messages to member staff and users. But I didn’t get a chance to work on my implementation for a while, so for over a year ideas have bubbled around in my head about ways to apply this technique and improve on it. I finally carved out some spare time to actually work on it, and came up with my take on the concept. The result is the OhioLINK Status-Via-Twitter service.
Okay, I know this is starting to seem like an obsession, but I can’t figure out why someone(s) would be constructing tweets that consist of my blog post headlines and links back to my postings. I’m wondering how wide spread this problem is, so I constructed a list of URLs to blog posts based on the Planet Code4Lib Atom feed and pointed them to the Ubervu service. Ubervu has a view into the Twitter firehose, and constructs reports of Twitter mentions of URLs. For instance, I can see all of the for my previous postings through this service. I can then easily scan through the list for other people that seem to be affected by this strange phenomenon.
The following may not be news to those who regularly hang out in Twitter-land, but the extent of the problem recently became clear to me: there is a bunch of spam in Twitter. More specifically, there appear to be robots that do nothing but scan the web for keywords and create tweets with links back to them. There appear to be some that value this service (judging by the number of followers of these Twitter users), but for me it just adds to the general clutter I find in Twitter.
The new NPR site is now live. Kudos to the team for bringing the new site to its opening, and in doing so showing good practices for shared Twitter accounts.
As a youth I remember intently studying the troubles of others — what they did when they got into trouble and how they got out of it. If the saying “You Learn From Your Mistakes” was so true, I wanted to be able to learn from the mistakes of others. I don’t do that as much anymore — probably because I have more than enough of my own mistakes now to learn from — but every once in a while a situation comes up where this urge strikes. The case ofresurfaced that youthful urge.
As libraries feel the need to join the social media landscape to meet a segment of their user population already there, it is useful to step back and get acclimated. There is a pace of information flow that is unlike anything else in the physical world, and a minor incident — be it an ill-advised policy decision or an unfortunate slip of the tongue — can quickly spiral out of your control. And that is probably the key word: control. You don’t, can’t, and won’t have it. It isn’t the nature of this media. “Damage control,” if you want to think of it like that, is honest, sincere, decisive, and quick communication with your users. As a counter example, I offer the case of Clinical Reader.