One thing I can say about Kindle: error reporting is easier.

You report problems in context, by selecting the offending text. No need to explain where - just what the problem is.

Feedback receipt is confirmed, along with the next steps for how it will be used.

By contrast, to report problems to academic publishers, you often must fill out an elaborate form (e.g. Springer or Elsevier). Digging up contact information often requires going to another page (e.g. ACM.). Some make you *both* go to another page to leave feedback and then fill out a form (e.g. EBSCO). Do any academic publishers keep the context of what journal article or book chapter you’re reporting a problem with? (If so, I’ve never noticed!)

Altmetrics is hitting its stride: 30 months after the Altmetrics manifesto¹, there are 6 tools listed. This is great news!

I tried out the beta of a new commercial tool, The Altmetric Explorer, from Altmetric.com. They are building on the success and ideas of the academic and non-profit community (but not formally associated with Altmetrics.org). The Altmetric Explorer gives overviews of articles and journals by the social media mentions. You can filter by publisher, journal, subject, source, etc. Altmetric Explore has a closed beta, but you can try the basic functionality on articles with their open tool, the PLoS Impact explorer.

"The default view shows the articles mentioned most frequently in all sources, from all journals. Various filters are available.

Rolling over the donut shows which sources (Twitter, blogs, ...) an article was mentioned in.

Sparklines can be used to compare journals.

A 'people' tab lets you look at individual messages. Rolling over the photo or avatar shows the poster's profile.

Altmetric.com seems largely aimed at publishers². This may add promotional noise, not unlike coercive citation, if it is used as an evaluation metric as they suggest:³

Want to see which journals have improved their profile in social media or with a particular news outlet?

Their API is currently free for non-commercial use. Altmetric.com are crawling Twitter since July 2011 and focusing on papers with PubMed, arXiv, and DOI identifiers. They also get data from Facebook, Google+, and blogs, but they don’t disclose how. (I assume that blogs using ResearchBlogging code are crawled, for instance.)

1. J. Priem, D. Taraborelli, P. Groth, C. Neylon (2010), Altmetrics: A manifesto, (v.1.0), 26 October 2010. http://altmetrics.org/manifesto
2. “Altmetric sustains itself by selling more detailed data and analysis tools to publishers, institutions and academic societies.”, says the bookmarklet page, to explain why that is free
3. ‘This quote from an editor as a condition for publication highlights the problem: “you cite Leukemia [once in 42 references]. Consequently, we kindly ask you to add references of articles published in Leukemia to your present article”’-from the abstract of Science. 2012 Feb 3;335(6068):542-3. Scientific publications. Coercive citation in academic publishing. Wilhite AW, Fong EA. summary on Science Daily.

“Wikipedia discussions can thus be seen as a mirror of a stream of public consciousness, where those elements which are still not part of a shared consolidated heritage are object of a continuous negotiation among different points of view.”

There is No Deadline – Time Evolution of Wikipedia Discussions. (2012) Andreas Kaltenbrunner, David Laniado. arXiv:1204.3453v1

via summarizing it for Wikipedia Signpost, longer summary space on AcaWiki

From today’s Twitter stream, more juxtaposition:

Gabriela Avram: #LmkTH You’re half way through, and you’re all doing a fantastic job! Keep on the good work!

Laura Dragan: 50% done – #21k in 2h30min – not looking fwd to the hills that are coming :) sun still shining ..loving it!

I’m amused because Gabriela’s comment about the Limerick Tweasure Hunt could be a great reply to Laura’s Connemara marathon status update.

Marcel asked:
>http://bottlenose.com/
>anyone with experiences and opinions about it?

Definitely worth trying–it focuses on your network in order to pull more interesting stuff to the fore. I put it in my bookmar bar when I first encountered it — it was briefly useful (slowed down the stream, found things that my network had heavily retweeted, making interesting suggestions of the few things I should read).

Its classification is ok — the genre classification seems decent (news/videos/pictures) — the message type classification (Question/Opinion/Notification/Check-In/How-To/etc) seems less exact, but may still be useful.

It kept suggesting the same things so I stopped checking it regularly — but I just checked it and am intrigued since they’ve added some features. In particular, they seem to be pulling out keywords (you can visualize one/all of people, topics, hashtags, message types–see screenshot). That might be especially interesting when doing exploratory searches.

There’s also a lot of customization possible — you can make your own rules for what to put in streams, and they have a wizard (screenshot below):

If there were a marketplace for sharing rules, that might be good — I’m not likely to spend time on customizing my own, so I’m just relying on the defaults (‘suggested for you’ and ‘popular’).

I’d be cautious of posting from Bottlenose without first checking the documentation — they accept posts of any length, but may also modify them (add hashtags, say).

I suppose for some people, the ability to pull in from multiple networks (for now Twitter & Facebook) could be useful, though there are lots of tools that do that.

I’d be curious to hear what other people think–have you found uses for Bottlenose?

-Jodi
PS-They seem to be going by klout score for invites for now; if you can’t get in that way, give me a shout (I’ve 10 invites if you want one).
—-
I’m taking a listserv post as the source of a blog post again; channeling jrochkind I suppose.

There have been some interesting posts on BIBFRAME recently (noted a few of them).

Karen Coyle also pointed to her recent blog post on transforming bibliographic data into RDF. As she says, for a real library linked data environment,

we need to be creating data, not records, and that we need to create the data first, then build records with it for those applications where records are needed.

What is this Quantified Self stuff, anyway? Here’s a brief intro (prettier PDF version) Nathan Yau and I wrote.

This weekend I’m in Amsterdam for Quantified Self Europe. So far this morning I’ve met Arduino hackers, seen several talks about monitoring heart rate (continuously, cool, or even with swimming goggles) and lung capacity. Oh, and given a talk about Exercise and Weight tracking.

There’s lots of blogging/photoblogging going on. Twitter hashtag (formerly #QSelfEurope) is #QS2011.

I’ve been digging SoundCloud lately.

Today I noticed time-based comments in their tracks. It’s a bit disorienting to have comments pop up as you’re listening. Maybe after adjusting, there’s a pleasant sense of having a conversation going on around you. Definitely feels like you’ve got company!

Comments pop up as the track plays

Avatars appear below the track to indicate that there are comments, and you can scroll over avatars to read comments. You can also hide the comments if you prefer.

Entering a comment from the timeline

Avatar icons appear in the overview

Example track due to Duncan.

A few weeks ago, I noticed something new on YouTube: an “I dislike this” button.

I wonder how long that’s been there?

When I talk about online argumentation, a frequent comment is “too bad there’s only +1 and Like; we need more expressivity”.

See related discussions:

• Misusing like
• Mood classification on GetSatisfaction
• Using reactions instead of comments on blogs

EPUB is just HTML + CSS in a tasty ZIP package. Let’s have more of it!

That’s the message of this 3 minute spiel I gave David Weinberger when he interviewed me at LOD-LAM back in June. Resulting video is on YouTube and below.