Predicting publication long-term impact through a combination of early citations and journal impact factor (original) (raw)
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Journal of Informetrics, 2014
The findings of Bornmann, Leydesdorff, and Wang (in press) revealed that the consideration of journal impact improves the prediction of long-term citation impact. This paper further explores the possibility of improving citation impact measurements on the base of a short citation window by the consideration of journal impact and other variables, such as the number of authors, the number of cited references, and the number of pages. The dataset contains 475,391 journal papers published in 1980 and indexed in Web of Science (WoS, Thomson Reuters), and all annual citation counts (from 1980 to 2010) for these papers. As an indicator of citation impact, we used percentiles of citations calculated using the approach of . Our results show that citation impact measurement can really be improved: If factors generally influencing citation impact are considered in the statistical analysis, the explained variance in the long-term citation impact can be much increased. However, this increase is only visible when using the years shortly after publication but not when using later years.
Early Indicators of Scientific Impact: Predicting Citations with Altmetrics
Journal of Informetrics , 2021
Identifying important scholarly literature at an early stage is vital to the academic research community and other stakeholders such as technology companies and government bodies. Due to the sheer amount of research published and the growth of ever-changing interdisciplinary areas, researchers need an efficient way to identify important scholarly work. The number of citations a given research publication has accrued has been used for this purpose, but these take time to occur and longer to accumulate. In this article, we use altmetrics to predict the short-term and long-term citations that a scholarly publication could receive. We build various classification and regression models and evaluate their performance, finding neural networks and ensemble models to perform best for these tasks. We also find that Mendeley readership is the most important factor in predicting the early citations, followed by other factors such as the academic status of the readers (e.g., student, postdoc, professor), followers on Twitter, online post length, author count, and the number of mentions on Twitter, Wikipedia, and across different countries.
Analysis of Publications on Journal Impact Factor Over Time
Frontiers in Research Metrics and Analytics, 2017
In this article, we present the results of an analysis that describes the research centered on Journal Impact Factors (JIFs). The purpose of the analysis is to make a start of studying part of the field of quantitative science studies that relates to the most famous and classic bibliometric indicator around and to see what characteristics apply to the research on JIFs. In this article, we start with a general description of the research, from the perspective of the journals used, the fields in which research on JIFs appeared, and the countries that contributed to the research on JIF. Finally, the article presents a first attempt to describe the coherence of the field, which will form the basis for next steps in this line of research on JIFs.
An Altmetric As an Indicator of a Publication’s Scientific Impact
Herald of the Russian Academy of Sciences, 2018
The results of an empirical pilot project focused on the association between classical bibliometrics-publication, citation index, and journal cited half-life-and an altmetric-the assessment of an article's impact-are discussed. The analysis included an array of 37200 domestic articles indexed in SCI-E in 2015. Two altmetrics are used: usage counts for the last 180 days, U1, and usage counts since February 1, 2013, U2. A significant Kendall rank correlation has been identified between citation indices and article-level metrics. A stronger correlation has been observed for long usage counts, U2. The relationship between usage metrics and traditional journal-level metrics (cited half-life) has been analyzed. A rather weak negative correlation between cited half-life and U1 (U2) has been revealed, which is described by an inverse logarithmic dependence. In the authors' opinion, altmetrics should not be opposed to classical bibliometrics; they should be used as additional metrics to assess an article's impact.
Assessing Publication Impact Through Citation Data
SAA Archaeological Record, 2006
Within academia, there is a growing movement to document journal quality as a means of evaluat-ing research impact, particularly for the purpose of tenure and promotion evaluations. Indeed, this paper originates out of research I conducted for my tenure ...
Author Impact Factor: tracking the dynamics of individual scientific impact
Scientific reports, 2014
The impact factor (IF) of scientific journals has acquired a major role in the evaluations of the output of scholars, departments and whole institutions. Typically papers appearing in journals with large values of the IF receive a high weight in such evaluations. However, at the end of the day one is interested in assessing the impact of individuals, rather than papers. Here we introduce Author Impact Factor (AIF), which is the extension of the IF to authors. The AIF of an author A in year t is the average number of citations given by papers published in year t to papers published by A in a period of Δt years before year t. Due to its intrinsic dynamic character, AIF is capable to capture trends and variations of the impact of the scientific output of scholars in time, unlike the h-index, which is a growing measure taking into account the whole career path.
A Measure of Total Research Impact Independent of Time and Discipline
PLoS ONE, 2012
Authorship and citation practices evolve with time and differ by academic discipline. As such, indicators of research productivity based on citation records are naturally subject to historical and disciplinary effects. We observe these effects on a corpus of astronomer career data constructed from a database of refereed publications. We employ a simple mechanism to measure research output using author and reference counts available in bibliographic databases to develop a citation-based indicator of research productivity. The total research impact (tori) quantifies, for an individual, the total amount of scholarly work that others have devoted to his/her work, measured in the volume of research papers. A derived measure, the research impact quotient (riq), is an age independent measure of an individual's research ability. We demonstrate that these measures are substantially less vulnerable to temporal debasement and cross-disciplinary bias than the most popular current measures. The proposed measures of research impact, tori and riq, have been implemented in the Smithsonian/NASA Astrophysics Data System.
On the evolution and utility of annual citation indices
We study the statistics of citations made to the top ranked indexed journals for Science and Social Science databases in the Journal Citation Reports using different measures. Total annual citation and impact factor, as well as a third measure called the annual citation rate are used to make the detailed analysis. We observe that the distribution of the annual citation rate has an universal feature -it shows a maximum at the rate scaled by half the average, irrespective of how the journals are ranked, and even across Science and Social Science journals, and fits well to log-Gumbel distribution. Correlations between different quantities are studied and a comparative analysis of the three measures is presented. The newly introduced annual citation rate factor helps in understanding the effect of scaling the number of citation by the total number of publications. The effect of the impact factor on authors contributing to the journals as well as on editorial policies is also discussed.