The increasing popularity of Twitter in both scholarly communication and public engagement with science has triggered widespread Twitter interactions around scientific information, thus giving rise... Show moreThe increasing popularity of Twitter in both scholarly communication and public engagement with science has triggered widespread Twitter interactions around scientific information, thus giving rise to the emergence of scholarly Twitter metrics which aim to measure and characterize Twitter interactions related to scholarly objects. For the sake of more advanced scholarly Twitter metrics, the overarching aim of this PhD dissertation is to characterize diverse forms of Twitter interactions around scientific papers to understand in greater-depth the Twitter reception of scientific information and improve scholarly Twitter metrics. To this end, this dissertation starts with large-scale analyses of how many and how fast scientific papers are mentioned on Twitter in comparison with other types of social media metric data sources, to unravel the broadness and speed of Twitter presence of scientific papers. Then, focusing on scholarly tweets of scientific papers per se, this dissertation investigates the characteristics of diverse user interaction behaviors around scholarly tweets, shedding light on their potential value in developing more advanced indicators for measuring deeper levels of Twitter reception of scientific information. Finally, based on the main findings, this dissertation further discusses the possibility to approach a more fine-grained indicator system of scholarly Twitter metrics. Show less
Altmetric’s mission is to help others understand the influence of research online.We collate what people are saying about published research in sources such as the mainstream media, policy... Show moreAltmetric’s mission is to help others understand the influence of research online.We collate what people are saying about published research in sources such as the mainstream media, policy documents, social networks, blogs, and other scholarly and non-scholarly forums to provide a more robust picture of the influence and reach of scholarly work. Altmetric works with some of the biggest publishers, funders, businesses and institutions around the world to deliver this data in an accessible and reliable format.ContentsAltmetrics, Ten Years Later, Euan Adie (Altmetric (founder) & Overton)Reflections on Altmetrics, Gemma Derrick (University of Lancaster), Fereshteh Didegah (Karolinska Institutet & Simon Fraser University), Paul Groth (University of Amsterdam), Cameron Neylon (Curtin University), Jason Priem (Our Research), Shenmeng Xu (University of North Carolina at Chapel Hill), Zohreh Zahedi (Leiden University)Worldwide Awareness and Use of Altmetrics, Yin-Leng Theng (Nanyang Technological University)Leveraging Machine Learning on Altmetrics Big Data, Saeed-Ul Hassan (Information Technology University), Naif R. Aljohani (King Abdulaziz University), Timothy D. Bowman (Wayne State University)Altmetrics as Social-Spatial Sensors, Vanash M. Patel (West Hertfordshire Hospitals NHS Trust), Robin Haunschild (Max Planck Institute for Solid State Research), Lutz Bornmann (Administrative Headquarters of the Max Planck Society)Altmetric’s Fable of the Hare and the Tortoise, Mike Taylor (Digital Science)The Future of Altmetrics: A Community Vision, Liesa Ross (Altmetric), Stacy Konkiel (Altmetric)https://digitalcommons.unl.edu/scholcom/170 Show less
This paper presents a fine-grained overview of the usage behavior and topics of interest of different types of users in Mendeley. The analysis is based on 1.2 million Web of Science indexed... Show moreThis paper presents a fine-grained overview of the usage behavior and topics of interest of different types of users in Mendeley. The analysis is based on 1.2 million Web of Science indexed publications published in 2012. The disciplinary differences in the reading (saving) patterns of different types of Mendeley users are identified and depicted using VOSviewer overlay visualizations. The findings show that compared to other fields, publications from Mathematics & Computer Science have the lowest coverage in Mendeley. Publications from the Social Sciences & Humanities receive on average the highest number of readers in Mendeley. The highest uptake of Mendeley is by students, but this differs across fields. Professors, students, and librarians are mainly active in the Social Sciences & Humanities, a field of science with a relatively low citation density in Web of Science. In contrast, researchers and other professionals are mainly active in fields with a relatively high citation density such as the Biomedical & Health Sciences and the Life & Earth Sciences. In addition, it seems that researchers and professionals are relatively more interested in practical, methodological, and technical oriented topics while professors and students are attracted by the more educational and theoretical oriented topics. These different usage patterns among user types possibly reflect the way in which scholarly publications are used for scientific, educational, or other professional purposes. This information could inform relevant stakeholders, such as researchers, librarians, publishers, funders, and policy makers of the scientific, educational, or professional values of publications. Show less
Costas, R.; Perianes-Rodriguez, A.; Ruiz-Castillo, J. 2017
PurposeThe introduction of “altmetrics” as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for... Show morePurposeThe introduction of “altmetrics” as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for measuring scientific impact. Mendeley readership has been identified as one of the most important altmetric sources, with several features that are similar to citations. The purpose of this paper is to perform an in-depth analysis of the differences and similarities between the distributions of Mendeley readership and citations across fields.Design/methodology/approachThe authors analyze two issues by using in each case a common analytical framework for both metrics: the shape of the distributions of readership and citations, and the field normalization problem generated by differences in citation and readership practices across fields. In the first issue the authors use the characteristic scores and scales method, and in the second the measurement framework introduced in Crespo et al. (2013).FindingsThere are three main results. First, the citations and Mendeley readership distributions exhibit a strikingly similar degree of skewness in all fields. Second, the results on “exchange rates (ERs)” for Mendeley readership empirically supports the possibility of comparing readership counts across fields, as well as the field normalization of readership distributions using ERs as normalization factors. Third, field normalization using field mean readerships as normalization factors leads to comparably good results.Originality/valueThese findings open up challenging new questions, particularly regarding the possibility of obtaining conflicting results from field normalized citation and Mendeley readership indicators; this suggests the need for better determining the role of the two metrics in capturing scientific recognition. Show less
All research at Dutch universities is assessed on a regular basis following the Standard Evaluation Protocol (SEP). From 2015 onwards, one of the protocol’s criteria for measuring research success... Show moreAll research at Dutch universities is assessed on a regular basis following the Standard Evaluation Protocol (SEP). From 2015 onwards, one of the protocol’s criteria for measuring research success is the societal impact of the research. As traditional metrics do not provide an indication of public reach and influence, the African Studies Centre in Leiden (ASCL) decided to experiment with the new suite of alternative metrics – altmetrics – that measure the number of times a research output is viewed, downloaded or mentioned online. I analyzed the presence of altmetric indicators in 148 publications using Altmetric.com and evaluated the content that Altmetric.com tracked. This paper describes the ASCL Altmetric experiment and reports on its results. Show less
The country of authors of 5,9 million Web of Science (WoS) publications with DOI from the years 2012 to 2015 have been compared with the country of Twitter users tweeting these WoS publications in... Show moreThe country of authors of 5,9 million Web of Science (WoS) publications with DOI from the years 2012 to 2015 have been compared with the country of Twitter users tweeting these WoS publications in order to study the main scholarly users of Twitter across 10 different countries. For this purpose, the visibility of country’s publications in the WoS and geographical distribution of Twitter users tweeting WoS publications have been analysed. The aim is to study how do they differ and what are their preference in tweeting their own vs. other country’s publication. The findings show that in general, US and UK with the highest proportion of outputs in the WoS, are among the main users of Twitter as well. Moreover, except for US, users tweet publications affiliated to other country more than those from their own country. Also, similar to WoS, it seems that altmetric providers are not free of international biases in their coverage and collection of metrics. Finally, various possible reasons on why publications from some countries attract more Twitter users than others have been discussed. Show less
The main focus of this paper is to investigate the impact of publications read (saved) by the different users in Mendeley in order to explore the extent to which their readership counts correlate... Show moreThe main focus of this paper is to investigate the impact of publications read (saved) by the different users in Mendeley in order to explore the extent to which their readership counts correlate with their citation indicators. The potential of filtering highly cited papers by Mendeley readerships and its different users have been also explored. For the analysis of the users, we have considered the information of the top three Mendeley ‘users’ reported by the Mendeley. Our results show that publications with Mendeley readerships tend to have higher citation and journal citation scores than publications without readerships. ‘Biomedical & health sciences’ and ‘Mathematics and computer science’ are the fields with respectively the most and the least readership activity in Mendeley. PhD students have the highest density of readerships per publication and Lecturers and Librarians have the lowest across all the different fields. Our precision-recall analysis indicates that in general, for publications with at least one reader in Mendeley, the capacity of readerships of filtering highly cited publications is better than (or at least as good as) Journal Citation Scores. We discuss the important limitation of Mendeley of only reporting the top three readers and not all of them in the potential development of indicators based on Mendeley and its users. Show less
