haustein, s. (2016). analyzing, measuring and visualizing the success of interdisciplinarity

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Stefanie Haustein Analyzing, measuring and visualizing the success of interdisciplinarity

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Page 1: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Stefanie Haustein

Analyzing, measuringand visualizing the successof interdisciplinarity

Page 2: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Interdisciplinarity• Integration of data, methods and theories of disciplines• Expected to derive results greater than the sum of its

disciplinary parts• Central in science policy and research evaluation

Operationalization in bibliometrics• Measured by co-citations• Conflicting evidence regarding citation impact:

• lower citation impact

• higher citation impact

• no significant difference

Introduction

(e.g., Rinia, van Leeuwen & van Raan, 2002; Levitt & Thelwall, 2008; Larivière & Gingras, 2010)

(e.g., Adams, Jackson & Marshall, 2007)

(e.g., Larivière & Gingras, 2010; Uzzi et al., 2013; Yegros-Yegros, Rafols, & D’Este, 2015)

Page 3: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Are interdisciplinary long-distance relationships worth the effort?

• Does an interdisciplinary knowledge base increase the citation impact of an article?

• Which combinations of subdisciplines lead to the highest citation impact?

• How does the distance between co-cited subdisciplines influence citation impact?

Research Questions

Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.

Page 4: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

UCSD Map of Science

Dataset and Methods

Börner, K., Klavans, R., Patek, M., Zoss, A. M., Biberstine, J. R., Light, R. P., … Boyack, K. W. (2012). Design and Update of a Classification System: The UCSD Map of Science. PLoS ONE, 7(7), e39464.

• 14 disciplines• 544 subdisciplines

Page 5: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Dataset and Methods

Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.

11.1 million articles 2000-2012

Page 6: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Dataset and Methods

Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.

citing

co-cited

Molecular Ecology

Semiconducting Materials

9.2 millioninterdisciplinary articles

Data

set

citing

co-cited

Molecular Ecology

Molecular Ecology

1.9 milliondisciplinary articles

Page 7: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Dataset and Methods

Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.

≥30 articles

80,997 co-citedsubdiscipline pairs

distance onthe UCSD map

Page 8: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Dataset and Methods

Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.

5citations

4.0citations

7.5citations

5.0/4.0=1.25

5.0/7.5=0.67

Expected citation rate in Molecular Ecology

Expected citation rate in Semiconducting Material

win lose

Citation impact

Page 9: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Results

Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.

Percentage of pairs

win win70%

win lose27%

lose lose3%

Rela

tive

cita

tion

rate

Distance categorynear far

Citation impact and distance

Page 10: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Results

2,940 (5.19%) of 56,614 win-win edgesnode color: discipline │ edge color: mix of adjacent nodes │ labels: subdiscipline with highest number of win-win relationships per discipline (number and percentage of win-win relationships)

Number of papers citing win-win relationships (≥10,000 citing articles)

Page 11: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Results

943 (0.8%) of 113,228 win-win arcsnode color: discipline │ arc color: outgoing node (clock-wise) │ labels: strongest win-win relationships per discipline(mean relative citation rate)

Relative citation rate of win-win relationships (≥5.0 mean citations)

Page 12: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

• Co-citing articles from different subdisciplines leads to above average citation impact.

• The more diverse the knowledge base, the higher the citation impact.

Findings support assumption that interdisciplinary research leads to results greater than the sum of its disciplinary parts.

Conclusions

Page 13: Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity

Stefanie Haustein

Merci beaucoup!

[email protected] @stefhaustein crc.ebsi.umontreal.ca