Book: E-Research: Transformation In Scholarly Practice

Book: E-Research: Transformation in Scholarly Practice

A new book E-Research: Transformation in Scholarly Practice edited by Nicholas W. Jankowski on the ways social science research is being changed by the rise of social media has just been released by Routledge.  My colleagues and I contributed a chapter on the ways that information visualization of social media is a useful technique to identify research questions and discover answers about the nature of human association when mediated by computation.  The volume contains work from an all-star line-up of researchers who address the opportunities and challenges of performing research with computer-mediated data about social life.

The blurb about the book describes it as:

“No less than a revolutionary transformation of the research enterprise is underway. This transformation extends beyond the natural sciences, where ‘e-research’ has become the modus operandi, and is penetrating the social sciences and humanities, sometimes with differences in accent and label. Many suggest that the very essence of scholarship in these areas is changing. The everyday procedures and practices of traditional forms of scholarship are affected by these and other features of e-research. This volume, which features renowned scholars from across the globe who are active in the social sciences and humanities, provides critical reflection on the overall emergence of e-research, particularly on its adoption and adaptation by the social sciences and humanities.”

Our chapter is “A Picture is Worth a Thousand Questions: Visualization Techniques for Social Science Discovery in Computational Spaces”, co-authored by  Howard T. Welser, Thomas Lento, Marc Smith, Eric Gleave and Itai Himelboim.  In it, we describe the ways that using information visualizations of social media data sets is a useful way of discovering insights, patterns, and clusters.  We illustrate the paper with several examples of social media information visualizations that display the range of behavior among contributors to social media spaces.

Here is the table of contents for the volume:

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Paper In The Journal Of Computer-Mediated Communication: Discussion Catalysts In Political Discussions

Paper in the Journal of Computer-Mediated Communication: Discussion Catalysts in Political Discussions

2009 - JCMC- Discussion Catalysts - Himelboim, Gleave and Smith JCMC Article: Discussion Catalysts My co-authors Eric Gleave, from the University of Washington, Department of Sociology and Itai Himelboim, from the University of Georgia, Department of Communications, are pleased to…

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Paper: Reader-to-Leader Framework: Motivating Technology-Mediated Social Participation, Preece & Shneiderman

Paper: Reader-to-Leader Framework: Motivating Technology-Mediated Social Participation, Preece & Shneiderman

I just read a new paper from Jennifer Preece and Ben Shneiderman that provides a nice framework for the ways people contribute at different rates to collective projects in general and social media on the Internet in particular. Preece, Jennifer…

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ICWSM 2009 – Pictures and Posters

The recent 2009 ICWSM conference featured research into the nature of a wide range of social media. [flickrset id="72157618579371124" thumbnail="square" overlay="true" size="medium"] Some highlights: An Examination of Language Use in Online Dating Profiles Meenakshi Nagarajan, Marti Hearst Event Detection and…

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Liveblogging ICWSM 2009 – Day 2

Liveblogging ICWSM 2009 – Day 2

ICWSM 2009 in San Jose

[Vladimir Barash is liveblogging the ICWSM conference]

10.30am A categorical model for discovering latent structure in social annotations (Said Kashoob)
Given a collection of web objects, users and tags, can we model the underlying tag generation process?

-Discover implict communities of interest?

-Categories of related tags?

-For given category, id most relevant objs for category

-compare categories

Initial thoughts: content-based topic modeling (Latent Dirichlet Allocation, LSA). Recent work applying LDA models to tags (Wu 2006, Zhou 2008)

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