I've just published an article over on the SAGE Ocean blog, all about Image Tagging: "In part one of this series we introduced the topic of automated image tagging and showed how Cloud Vision APIs such as Clarifai can be used to classify images into different categories. We showed examples of SAGE images and the tags assigned by different Cloud Vision APIs, then discussed use cases for this innovative technology—primarily in discoverability and accessibility. In this follow-on post, we focus on data analysis and specifically co-occurrence networks. By way of example we present a co-occurrence network derived from Clarifai image tags, which represents a kind of mental model of the SAGE journal images we processed. The following image is a visualization of the co-occurrence network that we created" You can read the full article here .
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Introduction Click for high resolution version A couple of years ago, the publisher Springer Nature entered into a strategic relationship with Zapnito , an “Expert Network” platform. The goal was to facilitate knowledge sharing between employees, academic experts, and other interested parties, and there are now more than twenty different Springer Nature communities hosted on Zapnito, twelve of which are “Nature Research” communities and are the focus of this article. This network of communities represents an interesting opportunity to explore the relationships between expert communities, along with the way Zapnito is facilitating knowledge sharing. This blog post introduces the Springer Nature communities, then provides a light-touch exploration of community structure and connectivity, and its relationship to knowledge sharing and dissemination. The post is a result of a collaboration between Zapnito, Springer Nature, and myself, and is cross-posted on the Zapnito blog