CIRCA:Viral Analytics Paper Proposal

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Contents

Viral Analytics: Embedding eVoyeur in Content Systems

Authors: Geoffrey Rockwell, Ashley Moroz, Stéfan Sinclair, and Corey Slavnik

Introduction

How can we better mash tools together with texts for interpretation? One model is to create embeddable badges that, like a YouTube video can be dropped into content. To that end the Viral Analytics project has developed and tested an embeddable text analysis micro-environment based on Voyeur Tools [1] called eVoyeur. eVoyeur is able to perform text analysis on web pages on which it is embedded without authors needing to install software on their server. It is an example of what Siemens calls a professional reading tool. [2] For more functionality eVoyeur can also be tucked in as a plug-in for common Content Management Systems (CMS) like WordPress for blogs, Drupal and the Open Journal System (OJS) – the CMS plugins interact intelligently with the backend database and are able to operate on customized sets of documents as defined, say, by categories or tags. Authors thus can give readers access to analytical badges like word clouds that run in the client’s browser when they look at a blog post or article. This paper will discuss eVoyeur and the results of usability interviews with journal and blog editors in the digital humanities that helped us understand how we can better support content editors. This paper will:

  1. Introduce embeddable tools and plug-ins in general,
  2. Demonstrate eVoyeur in the context of common content management systems like WordPress and OJS,
  3. Discuss the feedback from usability interviews that we conducted, and
  4. Conclude with a discussion of the future of the project.

Demonstrate eVoyeur in Drupal, Wordpress and OJS

eVoyeur is an embeddable tool capable of performing text analysis on any page on which it sits. It builds on the TAToo project that created a Flash embeddable tool for blogs. [3] The eVoyeur micro-environment is a sizable badge that can show different views on the content of the page including a word cloud, a list of high-frequency words, a graph of collocations and statistical summary of the content of the page. Cirrus is a Wordle-like (see wordle.net) word cloud where the most frequent words in the document are sized and posititioned according to their frequency. The Frequency Grid shows the overall word frequencies for the entire corpus as well as information about how word frequencies are distributed over documents within the corpus. Links finds collocates for words and displays a network graph of the linked words. The Summary tool provides the longest and shortest document, highest vocabulary density, most frequent words, notable peaks in frequency and distinctive words. In this paper we will demonstrate how the tools work as analytical badges for the reader and then how they can be installed as plug-ins in common CMS systems.

Methodology and Results of Usability Interviews

In order to determine how analytical badges could be useful to editors of online content we conducted usability interviews with journal and blog editors in the digital humanities. Before the interview an illustrated introduction to the eVoyeur tool was sent to the interviewees to give them ideas. The interviews were conducted over Skype following a loose interview guide that allowed editors to tell us what kinds of text analysis tools would be useful to their audiences. Interview notes were shared back with the interviewees for correction. A preliminary analysis of the interviews shows that the most useful tools are the Cirrus word cloud and the Frequency Grid. Interviewees felt that many of tools suffered because of the small size of the badge imposed by the design of the content management systems. We are now trying to more efficiently use the space allocated to the badge and adding a feature that lets the user expand the view for those tools that don’t work in the small.


We also asked interviewees for suggestions for new features. A couple wanted the tool to operate not just on the page it appears on but also on collections of articles. Another wanted the tool adapted to Omeka and one wanted link analysis. Finally, this being the digital humanities, someone wanted a TEI wrapper. In this presentation we will summarize the results of our interviews and how we have adapted the tool in response.

Conclusions

Our goal is to make eVoyeur as attractive as possible to editors of digital humanities. We believe that easy to use analytical badges are one way to bring interpretative tools to content, but not the only way. Large projects will want tools that are more closely integrated and under their control, but for the small online publication eVoyeur can provide accessible functionality that resembles the badge tools that have proliferated on the web. The next step once we have responded to our editor interviewees with an improved micro-environment is to test the tool in real journals and blogs. To that end we are looking for projects willing to include eVoyeur in their interface.

Notes

[1] Voyeur Tools can be used at <http://voyeurtools.org>.

[2] Siemens, Ray et al. "A Study of Professional Reading Tools for Computing Humanists." A report at <http://etc.uvic.ca/public/pkp_report/>.

[3] For the TAToo (Text Analysis for me Too) project see <http://ra.tapor.ualberta.ca/~tatoo/>. For a discussion of this tool and our experiments see “Ubiquitous Text Analysis” in the Poetess Archive Journal, <http://paj.muohio.edu/paj/index.php/paj/article/view/13>.

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