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What are We Thinking?: Using Faceted Classification and Tagging to Enhance Subject Access to the Public Mind Elise Dunham The Roper Center for Public Opinion.

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Presentation on theme: "What are We Thinking?: Using Faceted Classification and Tagging to Enhance Subject Access to the Public Mind Elise Dunham The Roper Center for Public Opinion."— Presentation transcript:

1 What are We Thinking?: Using Faceted Classification and Tagging to Enhance Subject Access to the Public Mind Elise Dunham The Roper Center for Public Opinion Research University of Connecticut SAA MDOR Meeting August 13, 2014 @elisedunham #saa14 #mdor14

2 Roper Center Services

3 Datasets

4 Question Text, Response Categories, & Marginals

5 The Power of iPOLL This day in history… Current events Clinton’s visit to UConn=Women in Politics MH17=Air Safety in Wake of Disaster Nixon resignation, August 8, 1974 Civil Rights Act of 1964, July 2, 1964

6 The Power of iPOLL Topics: FAMILY EQUALITY SEX GROUPS

7 Goals Develop system for concept-based classification of manageable content Implement workflows for identifying conceptual links between content at point of acquisition/creation

8 Benefits of Faceted Classification & Tagging Flexible & agile Indexer friendly End user friendly “Quick” startup

9 Iterative Project Steps Read & learn – The Accidental Taxonomist, Heather Hedden – Simmons GSLIS Taxonomy & Controlled Vocabulary course, Heather Hedden – ICPSR & NYT vocabularies – Concepts: FRSAR, LC FAST, Syntactic Indexing Develop aboutness model to identify facets

10 Iterative Project Steps cont’d Develop controlled set of tags after analyzing: – Current iPOLL Topics – Topics at a Glance – User searches Develop backward- and forward- compatible infrastructure Assign tags to content

11 Study Survey Samples Variables Power of iPOLL briefs Primary source Survey questions Topics Sample Description Methodology Types Secondary source Press releases

12 Challenges Public opinion=inherently controversial Tensions between theoretical purity & implementation Survey questions are sometimes shorter than a tweet

13 Ideas Moving Forward Tag-a-thon Outside review Formal user testing/analysis Linked data: be ready

14 Thank you! Elise Dunham elise.dunham@uconn.edu @elisedunham The Roper Center for Public Opinion Research www.ropercenter.uconn.edu @ropercenter

15 Resources GESIS, “Improving precision and recall in study retrieval: a concept for thesaurus-based syntactic indexing,” IASSIST Conference, 2014, http://www.library.yorku.ca/binaries/iassist2014/2F/- 2014_2F_Siegers.pptxhttp://www.library.yorku.ca/binaries/iassist2014/2F/- 2014_2F_Siegers.pptx Heather Hedden, The Accidental Taxonomist, 2010. Alexis C. Madrigal, “How Netflix Reverse Engineered Hollywood,” 2014-01-02, http://www.theatlantic.com/technology/archive/2014/01/how-netflix-reverse-engineered- hollywood/282679/ http://www.theatlantic.com/technology/archive/2014/01/how-netflix-reverse-engineered- hollywood/282679/ OCLC Research, FAST, http://www.oclc.org/research/activities/fast.html?urlm=159754http://www.oclc.org/research/activities/fast.html?urlm=159754 Maja Zumer, Athena Salaba, and Marcia Lei Zeng, “Functional Requirements for Subject Authority Records (FRSAR): A Conceptual Model of Aboutness,” from Asian Digital Libraries: Looking Back 10 Years and Forging New Frontiers, Lecture Notes in Computer Science, Volume 4822, 2007, pp 487-492, http://link.springer.com/chapter/10.1007%2F978-3-540-77094-7_62#page-1http://link.springer.com/chapter/10.1007%2F978-3-540-77094-7_62#page-1


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