Pete Warden discusses why anonymized social media datasets can be so easy to match up again:

“[T]his anonymization process is an illusion. Precisely because there are now so many different public datasets to cross-reference, any set of records with a non-trivial amount of information on someone’s actions has a good chance of matching identifiable public records. Arvind first demonstrated this when he and his fellow researcher took the “anonymous” dataset released as part of the first Netflix prize, and demonstrated how he could correlate the movie rentals listed with public IMDB reviews. That let them identify some named individuals, and then gave access to their complete rental histories. More recently, he and his collaborators used the same approach to win a Kaggle contest by matching the topography of the anonymized and a publicly crawled version of the social connections on Flickr. They were able to take two partial social graphs, and like piecing together a jigsaw puzzle, figure out fragments that matched and represented the same users in both.” (via)

(Photo by Ell Hind at Flickr)

How do you track scholarly impact, beyond citation-counting? Princeton computer scientists Sean Gerrish and David Blei developed a model based on the hypothesis that the most impactful publications will impact the mix of terminology used in subsequent work in the field, using corpora from Nature, PNAS, etc.:

“Identifying the most influential documents in a corpus is an important problem in many fields, from information science and historiography to text summarization and news aggregation. Unfortunately, traditional bibliometrics such as citations are often not available. We propose using changes in the thematic content of documents over time to measure the importance of individual documents within the collection. We describe a dynamic topic model for both quantifying and qualifying the impact of these documents. We validate the model by analyzing three large corpora of scientific articles.” (via)

For example, they show how after the publication of “Molecular cloning of a cDNA encoding human antihaemophilic factor” in 1984, terms very frequently used in the highly-cited paper (e.g. “expression” and “blot”) became much more commonplace in the field. This content-based approach makes for an interesting supplement to bibliometric approaches that rely primary on author-generated citations.

Read more:

• “A Language-based Approach to Measuring Scholarly Impact” (on CiteSeer)
• Related story in The Economist, focusing on topic-grouping aspects

Can solid database replication support have global health impacts? Global health tech company Dimagi discusses how they use CouchDB (a NoSQL document-oriented database) for health data management in rural Zambia:

“We’ve got computers at clinics that are maintaining patient records…None of these clinics have Internet out of the box, so most of the time our only Internet connection is through a GSM modem that connects over the local cell network. It’s very hard to move data in that environment, and you can’t do anything that relies on an always-on Internet connection with a web app that is always accessing data remotely…CouchDB was a really good option for us because we could install a Couch database at each clinic site, and then that way all the clinic operations would be local. There would be no Internet use in terms of going out and getting the patient records, or entering data at the clinic site. Couch has a replication engine that lets you synchronize databases — both pull replication and push replication — so we have a star network of databases with one central server in the middle and all of these satellite clinic servers that are connecting through that cell network whenever they’re able to get on, and sending the data back and forth. That way we’re able to get data in and out of these really remote, rural areas without having to write our own synchronization protocols and network stack.” (via)

Link

Deep links to content enhance users’ ability to discuss and comment specific parts of a site — and that extends out to intra-page elements.

The New York Times recently open-sourced Emphasis, the technology they use to allow users to link directly to individual paragraphs and sentences of each story on their site.The technology, including the clever fuzzy hashing mechanisms they use to create close-to-permanent identifiers for potentially changeable text, is described on their blog.

“The solution seemed clear: create a unique identifier or key for each paragraph. But how to do that? The identifiers need to be consistent for all readers, and they must remain intact when a paragraph is edited and a page is republished. So it’s not simply a matter of generating the identifiers on the back end — with that approach, you might end up with the insane idea of building a mini-CMS for managing paragraph keys. On the flip side, how do you generate the same key each time the piece of content changes?”

They solved the problem by knowing their data. For example, the New York Times‘ developers know that it’s more common for paragraph order to change (e.g. if an update para gets added to the beginning of the article) than sentence order within a given paragraph, and their fuzzy hashing mechanism reflects that.