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Kudos dataset
Version 3 2017-05-05, 05:34
Version 2 2016-12-06, 03:45
Version 1 2016-12-06, 03:14
dataset
posted on 2017-05-05, 05:34 authored by Mojisola Helen ErdtMojisola Helen Erdt, Htet Htet Aung, Ashley Sara Aw, Charlie RappleCharlie Rapple, Yin-Leng ThengThe Kudos dataset (extracted from Kudos in February 2016) is analysed in the research article with the title "Analysing researchers' outreach efforts and the association with publication metrics: A case study of Kudos". This research paper is a result of a joint research collaboration between Kudos and CHESS, Nanyang Technological University, Singapore. Kudos made funds available to CHESS to perform the study and also provided the dataset used for the analysis.
In recent years, social media and scholarly collaboration networks have become increasingly accepted as effective tools for discovering and sharing research. Altmetrics are also becoming more common, as they reflect impact fast, are openly accessible and represent both academic and lay audiences, unlike traditional metrics such as citation counts. As a researcher, it still remains challenging to know whether the efforts to increase the visibility and outreach of your research on social media are associated with improved publication metrics.
In this paper, we analyse the effectiveness of common online channels used for sharing publications using Kudos (https://www.growkudos.com, launched in May 2014), a web-based service that aims to help researchers increase the outreach of their publications, as a case study. We extracted a dataset from Kudos of 20,775 unique publications that had been claimed by authors, and for which actions had been taken to explain or share via Kudos. For 4,867 of these, full text download data from publishers was available. Our findings show that researchers are most likely to share their work on Facebook, but links shared on Twitter are most likely to be clicked on. A Mann-Whitney U test revealed that a treatment group (publications having actions in Kudos) had a significantly higher median average of 149 full text downloads (23.1% more) per publication as compared to a control group (having no actions in Kudos) with a median average of 121 full text downloads per publication. These findings suggest that performing actions on publications, such as sharing, explaining, or enriching, could help to increase the number of full text downloads of a publication.
The DOIs of the publications in the dataset have been anonymised to protect the privacy of the users in Kudos.
A readme text file is provided describing the data fields of the four datasets.
All fields in the CSV file should be imported (e.g., into Excel) as text values.
