Do altmetrics correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective

An extensive analysis of the presence of different altmetric indicators provided by Altmetric.com across scientific fields is presented, particularly focusing on their relationship with citations. Our results confirm that the presence and density of social media altmetric counts are still very low and not very frequent among scientific publications, with 15%-24% of the publications presenting some altmetric activity and concentrating in the most recent publications, although their presence is increasing over time. Publications from the social sciences, humanities and the medical and life sciences show the highest presence of altmetrics, indicating their potential value and interest for these fields. The analysis of the relationships between altmetrics and citations confirms previous claims of positive correlations but relatively weak, thus supporting the idea that altmetrics do not reflect the same concept of impact as citations. Also, altmetric counts do not always present a better filtering of highly cited publications than journal citation scores. Altmetrics scores (particularly mentions in blogs) are able to identify highly cited publications with higher levels of precision than journal citation scores (JCS), but they have a lower level of recall. The value of altmetrics as a complementary tool of citation analysis is highlighted, although more research is suggested to disentangle the potential meaning and value of altmetric indicators for research evaluation

TWEETS OF AN ARTICLE AND ITS CITATION: AN ALTMETRIC STUDY OF MOST PROLIFIC AUTHORS

The present study was carried to find out the association between twitter and citation pattern for scholarly articles. This study was carried out with the most prolific authors of 2014 from the four subject domain “Clinical medicine, Microbiology, Molecular Biology, and Neuroscience” and 4886 papers were identified to studied their tweets and citation counts. From the study, it was found that the articles of the most prolific authors have a strong correlation with the citation and its value ρ =.518**. The linear relationship for individual subjects was between .386** to .559**, significant at .01 level

Dimensions: Re-discovering the Ecosystem of Scientific Information

[EN] The overarching aim of this work is to provide a detailed description of the free version of Dimensions (new bibliographic database produced by Digital Science and launched in January 2018). To do this, the work is divided into two differentiated blocks. First, its characteristics, operation, and features are described, focusing on its main strengths and weaknesses. Secondly, an analysis of its coverage is carried out (comparing it against Web of Science Core Collection, Scopus and Google Scholar) in order to determine whether the bibliometric indicators offered by Dimensions have an order of magnitude significant enough to be used. To this end, an analysis is carried out at three levels: journals (sample of 20 publications in `Library & Information Science¿), documents (276 articles published by the Journal of informetrics between 2013 and 2015), and authors (28 people awarded with the Derek de Solla Price prize). Preliminary results indicate that Dimensions has coverage of the recent literature superior to Scopus, although inferior to Google Scholar. With regard to the number of citations received, Dimensions offers slightly lower figures than Scopus. Despite this, the number of citations in Dimensions exhibits a strong correlation with Scopus and somewhat less (although still significant) with Google Scholar. For this reason, it is concluded that Dimensions is an alternative for carrying out citation studies, able to rival Scopus (greater coverage and free of charge) and Google Scholar (greater functionalities for the treatment and data export).Orduña Malea, E.; Delgado-López-Cózar, E. (2018). Dimensions: Re-discovering the Ecosystem of Scientific Information. El profesional de la información. 27(2):420-431. https://doi.org/10.3145/epi.2018.mar.21S42043127

Scholarly use of social media and altmetrics : a review of the literature

Social media has become integrated into the fabric of the scholarly communication system in fundamental ways: principally through scholarly use of social media platforms and the promotion of new indicators on the basis of interactions with these platforms. Research and scholarship in this area has accelerated since the coining and subsequent advocacy for altmetrics—that is, research indicators based on social media activity. This review provides an extensive account of the state-of-the art in both scholarly use of social media and altmetrics. The review consists of two main parts: the first examines the use of social media in academia, examining the various functions these platforms have in the scholarly communication process and the factors that affect this use. The second part reviews empirical studies of altmetrics, discussing the various interpretations of altmetrics, data collection and methodological limitations, and differences according to platform. The review ends with a critical discussion of the implications of this transformation in the scholarly communication system

Posted, Visited, Exported: Altmetrics in the Social Tagging System BibSonomy

In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points

Mining, Modeling, and Leveraging Multidimensional Web Metrics to Support Scholarly Communities

The significant proliferation of scholarly output and the emergence of multidisciplinary research areas are rendering the research environment increasingly complex. In addition, an increasing number of researchers are using academic social networks to discover and store scholarly content. The spread of scientific discourse and research activities across the web, especially on social media platforms, suggests that far-reaching changes are taking place in scholarly communication and the geography of science. This dissertation provides integrated techniques and methods designed to address the information overload problem facing scholarly environments and to enhance the research process. There are four main contributions in this dissertation. First, this study identifies, quantifies, and analyzes international researchers’ dynamic scholarly information behaviors, activities, and needs, especially after the emergence of social media platforms. The findings based on qualitative and quantitative analysis report new scholarly patterns and reveals differences between researchers according to academic status and discipline. Second, this study mines massive scholarly datasets, models diverse multidimensional non-traditional web-based indicators (altmetrics), and evaluates and predicts scholarly and societal impact at various levels. The results address some of the limitations of traditional citation-based metrics and broaden the understanding and utilization of altmetrics. Third, this study recommends scholarly venues semantically related to researchers’ current interests. The results provide important up-to-the-minute signals that represent a closer reflection of research interests than post-publication usage-based metrics. Finally, this study develops a new scholarly framework by supporting the construction of online scholarly communities and bibliographies through reputation-based social collaboration, through the introduction of a collaborative, self-promoting system for users to advance their participation through analysis of the quality, timeliness and quantity of contributions. The framework improves the precision and quality of social reference management systems. By analyzing and modeling digital footprints, this dissertation provides a basis for tracking and documenting the impact of scholarship using new models that are more akin to reading breaking news than to watching a historical documentary made several years after the events it describes

Study on open science: The general state of the play in Open Science principles and practices at European life sciences institutes

Nowadays, open science is a hot topic on all levels and also is one of the priorities of the European Research Area. Components that are commonly associated with open science are open access, open data, open methodology, open source, open peer review, open science policies and citizen science. Open science may a great potential to connect and influence the practices of researchers, funding institutions and the public. In this paper, we evaluate the level of openness based on public surveys at four European life sciences institute

Mining Scholarly Publications for Research Evaluation

Scientific research can lead to breakthroughs that revolutionise society by solving long-standing problems. However, investment of public funds into research requires the ability to clearly demonstrate beneficial returns, accountability, and good management. At the same time, with the amount of scholarly literature rapidly expanding, recognising key research that presents the most important contributions to science is becoming increasingly difficult and time-consuming. This creates a need for effective and appropriate research evaluation methods. However, the question of how to evaluate the quality of research outcomes is very difficult to answer and despite decades of research, there is still no standard solution to this problem. Given this growing need for research evaluation, it is increasingly important to understand how research should be evaluated, and whether the existing methods meet this need. However, the current solutions, which are predominantly based on counting the number of interactions in the scholarly communication network, are insufficient for a number of reasons. In particular, they struggle in capturing many aspects of the academic culture and often significantly lag behind current developments. This work focuses on the evaluation of research publications and aims at creating new methods which utilise publication content. It studies the concept of research publication quality, methods assessing the performance of new research publication evaluation methods, analyses and extends the existing methods, and, most importantly, presents a new class of metrics which are based on publication manuscripts. By bridging the fields of research evaluation and text- and data-mining, this work provides tools for analysing the outcomes of research, and for relieving information overload in scholarly publishing

Social media in scholarly communication : a review of the literature and empirical analysis of Twitter use by SSHRC doctoral award recipients

This report has been commissioned by the Social Sciences and Humanities Research Council (SSHRC) to analyze the role that social media currently plays in scholarly communication as well as to what extent metrics derived from social media activity related to scholarly content can be applied in an evaluation context. Scholarly communication has become more diverse and open with research being discussed, shared and evaluated online. Social media tools are increasingly being used in the research and scholarly communication context, as scholars connect on Facebook, LinkedIn and Twitter or specialized platforms such as ResearchGate, Academia.edu or Mendeley. Research is discussed on blogs or Twitter, while datasets, software code and presentations are shared on Dryad, Github, FigShare and similar websites for reproducibility and reuse. Literature is managed, annotated and shared with online tools such as Mendeley and Zotero, and peer review is starting to be more open and transparent. The changing landscape of scholarly communication has also brought about new possibilities regarding its evaluation. So-called altmetrics are based on scholarly social media activity and have been introduced to reflect scholarly output and impact beyond considering only peer-reviewed journal articles and citations within them to measure scientific success. This includes the measurement of more diverse types of scholarly work and various forms of impact including that on society. This report provides an overview of how various social media tools are used in the research context based on 1) an extensive review of the current literature as well as 2) an empirical analysis of the use of Twitter by the 2010 cohort of SSHRC Doctoral Award recipients was analyzed in depth. Twitter has been chosen as one of the most promising tools regarding interaction with the general public and scholarly communication beyond the scientific community. The report focuses on the opportunities and challenges of social media and derived metrics and attempts to provide SSHRC with information to develop guidelines regarding the use of social media by funded researchers as well support the informed used of social media metrics