1. DIGGING INTO DATA A presentation to the NSF Cascades, Islands, or Streams? Time, Topic and Scholarly Activities in Humanities and Social Science Research

2. DIGGING INTO DATA Who is LARIVIÈRE MILOJEVIĆSUGIMOTODING THELWALLHOLMBERG

3. DIGGING INTO DATA What

4. DIGGING INTO DATA What Time: 1743-2011 Dissertations: 2,307,555 Subjects: 166 Schools: 1,490 Countries: 66

5. DIGGING INTO DATA What Time: 1900-2011 Medicine Articles: 14,698,810 Medicine References: 380,058,817 Social Science Articles: 4,228,702 Social Science References: 77,908,552 Arts & Humanities Articles: 3,151,986 Arts & Humanities References: 26,180,296 Natural Science Articles: 14,853,029 Natural Science References: 335,144,498

6. DIGGING INTO DATA What Time: 2007-2012 Articles: 744,584 Broad Subject areas: 7 Matching ISI records: ~50%

7. DIGGING INTO DATA What Time: 2010-current Tweets: 100,000 per month Subjects: 11 Generalist journals: 4 Scientists and science journalists: 350

8. DIGGING INTO DATA What Time: 2006-2012 Videos: 1,202 Views on TED: 620,406,446 Views on YouTube: 111,681,275 Comments on YouTube: 414,311

9. DIGGING INTO DATA Why are we Integrate several datasets representing a broad range of scholarly activities Use methodological and data triangulation to explore the lifecycle of topics within and across a range of scholarly activities Develop transparent tools and techniques to enable future predictive analyses

10. DIGGING INTO DATA Show me the Domain# PapersAver. Delay Earth and Space524380.40 Physics1765570.57 Biomedical Research31190.57 Chemistry16640.61 Engineering and Technology80201.04 Biology2851.18 Mathematics445351.44 Social Sciences3671.61 Professional Fields3821.77 Clinical Medicine5661.93 Psychology802.26 Humanities1113.88 Health374.54 Arts364.69 All disciplines2882000.69

11. DIGGING INTO DATA Show me the

12. DIGGING INTO DATA Show me the

13. DIGGING INTO DATA Show me the H=Hedges: lowered certainty (“perhaps”) B=Boosters: heightened certainty (“absolutely”) SM=Self-mentions: self-references (“the author”) AM=Attitude markers: author-text positions (“admitedly”) EM=Engagement markers: reader positions (“should”)

14. DIGGING INTO DATA Show me the MetricMinimumMedianMeanMaximumTotalValid TED web site views44,441338,969517,4379,946,996620,406,4461,199 YouTube views46243,31199,1843,991,983111,681,2751,126 Blog citations03,1209,073441,00010,905,3761,202 YouTube Likes248590026,5911,013,2311,126 YouTube Favorite count329976738,139863,4581,126 YouTube comments019536821,703414,3111,126 TED web site comments81171875,921224,6291,199 YouTube Dislikes034691,45678,0531,126 Academic syllabi012502,0701,202 PDF and Word documents000495921,202 Google Scholar citations000755051,202 Google Books citations000184341,202 PowerPoint presentations0002383921,202 Mendeley readers000302311,202 Web of Knowledge citations0005471,202 YouTube Like proportion0.2600.9410.9001.000-1,126

15. DIGGING INTO DATA Show me the MetricAcademicNon-academics TED web site views327,904321,320 YouTube views49,66045,414 Blog citations2,3402,246 YouTube comments223190 TED web site comments111112 Online mentions related to academic syllabi11 Online mentions in PDF and Word documents (acad. higher)00* Google Scholar citations00 Google Books citations00 Online mentions in PowerPoint presentations00 Mendeley readers00 Web of Knowledge citations00 YouTube Like proportion0.95740.9271**

16. DIGGING INTO DATA Keep on

17. DIGGING INTO DATA Keep on

18. DIGGING INTO DATA Comments

19. DIGGING INTO DATA Analyzing sentiment We are developing sentiment analysis software SentiStrength for the texts in the project The program will classify the sentiment of texts based upon lexicons of words – e.g., good, bad – plus special rules for negation, booster words (e.g., very) etc. The lexicon will be customised for different genres – e.g., flawed, incomplete for academic texts, dull, inspiring for videos

20. DIGGING INTO DATA Lead-lag analysis

21. DIGGING INTO DATA After Scott WeingartScott Weingart

22. DIGGING INTO DATA Towards a new model Draft Report Conf. paper Article Review Book Tweet Email Blog Slideshow Multimedia Curated DB Producer Consumer Prosumer

23. DIGGING INTO DATA Questions about Cassidy R. Sugimoto (PI) Assistant Professor School of Library and Information Science Indiana University Bloomington sugimoto@indiana.edu