This visualization represents the textbase of women writers online, a collection of 401 electronically-encoded historical texts by women writers. The right-sided visualization shows a holistic view of the collection by genre and publication year. The center visualization is a bipartite network showing the relationship of words and phrases of a particular in-text element to the genre of the text it resides in. Four in-text elements are included in the visualization and are populated by clicking the respective button. The third piece is a list of the texts included in the collection. The intention is that with increased user interaction, the user can filter down to a smaller number of texts and can see them in the right column.
You can see a live demo at www.wwp.northeastern.edu/wwo/lab/names-viz or visdunneright.github.io/WWOVis and watch our demo video:
- Open terminal/command prompt.
- Fork and clone the github repository to your local system in a dedicated folder.
- Change to the public directory.
- At the command line, run python -m http.server with the version Python 3.
- Visit http://localhost:8000/ in your browser.
Sarah Campbell, Zheng-yan Yu, Sarah Connell, and Cody Dunne, "Close and Distant Reading via Named Entity Network Visualization: A Case Study of Women Writers Online", Proc. 3rd Workshop on Visualization for the Digital Humanities. VIS4DH. 2018.
Sarah Campbell, Zheng-yan Yu, Sarah Connell, and Cody Dunne
Northeastern University Data Visualization @ CCIS, College of Art Media and Design, and Digital Scholarship Group.
This project is licensed under the MIT License.