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Cascades, Islands and Streams

Cascades, Islands and Streams. Indiana University Bloomington University of Wolverhampton University of Quebec at Montreal Presented by: Dr Kayvan Kousha (Wolverhampton). Project team. Indiana University Bloomington Cassidy Sugimoto (head) Ying Ding Staša Milojević

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Cascades, Islands and Streams

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  1. Cascades, Islands and Streams Indiana University Bloomington University of Wolverhampton University of Quebec at Montreal Presented by: Dr KayvanKousha (Wolverhampton)

  2. Project team • Indiana University Bloomington • Cassidy Sugimoto (head) • Ying Ding • StašaMilojević • University of Wolverhampton • Mike Thelwall • KayvanKousha (presenting) • University of Quebec at Montreal • Vincent Larivière

  3. http://mapofscience.com/nih.html Project idea • To correct the science bias in maps of science that rely upon journal citations

  4. Our proposal • Integrate several datasets representing a broad range of scholarly activities (not just journal publishing) • Use method 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

  5. Explore topic emergence differences • Occurs consistently in one type of activity, then cascades in a linear fashion to other areas • OR • Emerges in one area then flows into other areas (streams) • OREmerges in different places and remains in separate islands

  6. Research Questions • What is the nature of topic development in relation to core scholarly activities? • How does the type of activity in which a topic appears impact the lifecycle and duration of that topic?

  7. Datasets • ProQuest Dissertation and Theses database • National Science Foundation grant database • Social Science and Humanities Research Council of Canada grant database • Web of Science (Century of Science database) • Internet discussions • Blogs • Twitter • Mendeley

  8. Topics • Cognitive Science • Digital Humanities • History of Science • Social Network Analysis • We will analyse these four broad topic areas

  9. Methods • Word analysis • Words used as proxies for topics to investigate topic flows over time • Topic modelling • Identifying topics by statistical analysis of word co-occurrences • Burst detection • Identifying sub-topic emergence by detecting significant increases in word frequencies

  10. TEDTalks: Analysis of impact Example of findings:- Cassidy Sugimoto & Mike Thelwall Sugimoto, C.R. & Thelwall, M. (in press). Scholars on soap boxes: Science communication and dissemination via TED videos. Journal of the American Society for Information Science and Technology.

  11. Motivation • New popular genre • Public dissemination of science • Educational videos • Infotainment

  12. Research Questions • In which communication forms do TEDTalks have the greatest impact? • Which disciplinary types of TEDTalks have the greatest impact? • Do different communication forms have similar types of impact?

  13. Some Findings • There was a general consensus about the most popular videos as measured through views or comments on YouTube and the TED site. • Most videos were found in at least one online syllabus and videos in online syllabi tended to be more viewed, discussed and blogged. • Less liked videos generated more discussion. • Science and technology videos presented by academics were more liked than those by non‐academics • ->academics are not disadvantaged in TED

  14. Next step • Integrating web, citation and dissertation data into one huge analysis

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