Understanding Shakespeare: What We've Learned (So Far) - RSA 2016
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The document summarizes a project by JSTOR Labs to create an online tool called Understanding Shakespeare that connects quotes from Shakespeare's plays found in scholarly articles on JSTOR to the passages in the Folger Digital Texts. It details how the tool was developed through a partnership between JSTOR and the Folger Shakespeare Library. It also describes the matching algorithm used and provides usage statistics and information on the open API. It concludes by suggesting potential applications of the matching technology to other texts and corpora.
Understanding Shakespeare: What We've Learned (So Far) - RSA 2016
- 1. UNDERSTANDING SHAKESPEARE: WHAT WE’VE LEARNED (SO FAR) 1 April, 2016 Alex Humphreys, JSTOR Labs @abhumphreys RSA 2016 Panel: Folger Digital Agendas II – Scholarly Conversations and Collaborations
- 2. JSTOR is a not-for-profit digital library of academic journals, books, and primary sources. Ithaka S+R is a not-for-profit research and consulting service that helps academic, cultural, and publishing communities thrive in the digital environment. Portico is a not-for-profit preservation service for digital publications, including electronic journals, books, and historical collections. ITHAKA is a not-for-profit organization that helps the academic community use digital technologies to preserve the scholarly record and to advance research and teaching in sustainable ways.
- 3. JSTOR Labs works with partner publishers, libraries and labs to create tools for researchers, teachers and students that are immediately useful – and a little bit magical.
- 4. PARTNERSHIP WITH FOLGER • Open, collaborative partnership with Folger Shakespeare Library • They had: - Shakespeare Quarterly - Folger Digital Texts - Scholars and students • We had: - Full run of SQ - 2,000 more journals - A new Labs team • Flash Build - September, 2014: - From ideation to working site - One week at the Folger in DC
- 6. Understanding Shakespeare… “...is the most exciting project in digital Shakespeare in many years, and takes a major step forward in creating a ‘living variorum’ for Shakespeare studies on the web.” -Peter Donaldson Ford International Professor in the Humanities, MIT
- 7. MATCHMAKER ALGORITHM 1. Identify candidate set of articles from JSTOR 2. Extract quotations - quotations, not allusions - text within quotes or block-quotes 3. Run fuzzy text matching of quotations against primary text 4. Calibrate to minimize false positives and negatives - quotation length - % confidence
- 8. Usage vs. Scholarship 100% = 26,233 100% = 441,032
- 9. OPEN & PUBLIC API labs.jstor.org/developers Play Data (from Folger Digital Text) genre, play, act, scene, line, speaker, speaker_gender, on_stage Scholarship Data (from articles on JSTOR) title, authors, journal, pubdate, article_type, keyterms Quotations! play_text, match_text, similarity, match_size
- 10. WHERE DO WE GO FROM HERE? • Apply Matchmaker to other texts - Understanding the US Constitution App - Understanding Dante - and more! • Matchmaker API - Run Matchmaker on any text you can upload or point to - Incorporate Matchmaker links into other sites - Apply Matchmaker to other corpora • What do you suggest?
- 11. THANK YOU Alex Humphreys Director, JSTOR Labs ITHAKA http://labs.jstor.org @abhumphreys alex.humphreys@ithaka.org
- 12. APPENDIX (OPEN IN CASE OF NO INTERNET CONNECTION)