Abstract
Several works have used traditional readability measures to investigate the readability of scientific texts and its association with scientific impact . However, these works are limited in terms of dataset size, range of domains, and examined readability and impact measures. Our study addresses these limitations, investigating the readability of paper abstracts on a very large multidisciplinary corpus, the association of expert judgments on abstract readability with traditional readability measures, and the association of abstract readability with the scientific impact of the corresponding publication.
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Notes
- 1.
http://opencitations.net/download (November 2018 Dump).
- 2.
- 3.
- 4.
This is a restriction imposed by the textstat library (see Sect. 3.2).
- 5.
- 6.
- 7.
For each question, the interpretation of the extreme scale values (i.e., 1 and 5) were provided (actual wording is described in the dataset description page in Zenodo).
- 8.
- 9.
- 10.
Recall that FRE scores increase with readability, contrary to the other measures.
- 11.
Due to lack of space we omit \(\rho \) values, however the results were similar.
- 12.
For this measurement, we used all overlapping D2 abstracts for each expert pair.
- 13.
We omit \(\tau \) since it runs very slow on this dataset (\(\sim 12\)M papers).
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Acknowledgments
We acknowledge support of this work by the project “Moving from Big Data Management to Data Science” (MIS 5002437/3) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund).
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Vergoulis, T., Kanellos, I., Tzerefos, A., Chatzopoulos, S., Dalamagas, T., Skiadopoulos, S. (2019). A Study on the Readability of Scientific Publications. In: Doucet, A., Isaac, A., Golub, K., Aalberg, T., Jatowt, A. (eds) Digital Libraries for Open Knowledge. TPDL 2019. Lecture Notes in Computer Science(), vol 11799. Springer, Cham. https://doi.org/10.1007/978-3-030-30760-8_12
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