The influence of journal self‐citations on journal impact factor and immediacy index

2012 ◽  
Vol 36 (5) ◽  
pp. 639-654 ◽  
Author(s):  
Mu‐Hsuan Huang ◽  
Wen‐Yau Cathy Lin
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Journal Impact ◽  
Immediacy Index

A Historical Review and Analysis of Impact Factors Across School Psychology Journals from 1977 to 2019

2021 ◽  
pp. 082957352110455
Author(s):  
Randy G. Floyd ◽  
Emily K. Lewis ◽  
Kelsey A. Walker ◽  
Patrick J. McNicholas ◽  
Kerry L. Jones
Keyword(s):  
School Psychology ◽  
Impact Factor ◽  
Journal Impact Factor ◽  
Historical Review ◽  
Impact Factors ◽  
Highly Correlated ◽  
The Impact ◽  
Journal Impact ◽  
Immediacy Index ◽  
Psychology Review

School psychology journals yield hundreds of articles each year. As these journals are often evaluated based on the impact factors they produce, the aim of this study was to provide a historically complete record of the five impact factor values for the generalist school psychology journals that yield them. This study identified impact factors beginning in 1977, 20 years earlier than previously reported, and ending in 2019. Across all years and journals, the average Journal Impact Factor (JIF) was about 1.0, the average Immediacy Index was less than 0.4, the average 5-year Impact Factor was about 2.3, the average original CiteScore was 1.8, and the average new CiteScore was about 3.0. Increases in values were evident across time, and the highest recorded values across journals are held by the Journal of School Psychology (for the JIF, 5-year Impact Factor, and both CiteScore metrics) and School Psychology Review (for the Immediacy Index). Most impact factors, with the exception of the Immediacy Index, were moderately to highly correlated. The new CiteScore values were always the highest, and Immediacy Index values were always the lowest. School psychology has added journals to the list of those indexed by major databases, and these journals have increased their impact over time.

Analysis of the journal impact factor and related bibliometric indicators in education and educational research category

2021 ◽  
pp. 1-22
Author(s):  
Metin Orbay ◽  
Orhan Karamustafaoğlu ◽  
Ruben Miranda
Keyword(s):  
Impact Factor ◽  
Educational Research ◽  
Journal Impact Factor ◽  
Impact Factors ◽  
Bibliometric Indicators ◽  
Strongly Correlated ◽  
Starting Point ◽  
Consistent Assessment ◽  
The Impact ◽  
Journal Impact

This study analyzes the journal impact factor and related bibliometric indicators in Education and Educational Research (E&ER) category, highlighting the main differences among journal quartiles, using Web of Science (Social Sciences Citation Index, SSCI) as the data source. High impact journals (Q1) publish only slightly more papers than expected, which is different to other areas. The papers published in Q1 journal have greater average citations and lower uncitedness rates compared to other quartiles, although the differences among quartiles are lower than in other areas. The impact factor is only weakly negative correlated (r=-0.184) with the journal self-citation but strongly correlated with the citedness of the median journal paper (r= 0.864). Although this strong correlation exists, the impact factor is still far to be the perfect indicator for expected citations of a paper due to the high skewness of the citations distribution. This skewness was moderately correlated with the citations received by the most cited paper of the journal (r= 0.649) and the number of papers published by the journal (r= 0.484), but no important differences by journal quartiles were observed. In the period 2013–2018, the average journal impact factor in the E&ER has increased largely from 0.908 to 1.638, which is justified by the field growth but also by the increase in international collaboration and the share of papers published in open access. Despite their inherent limitations, the use of impact factors and related indicators is a starting point for introducing the use of bibliometric tools for objective and consistent assessment of researcher.

The TOP factor: An indicator of quality to complement journal impact factor

2020 ◽  
Vol 13 (3) ◽  
pp. 328-333
Author(s):  
Sven Kepes ◽  
George C. Banks ◽  
Sheila K. Keener
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Journal Impact

Peer Review Metrics and their influence on the Journal Impact

2021 ◽  
pp. 016555152110597
Author(s):  
Sumeer Gul ◽  
Aasif Ahmad Mir ◽  
Sheikh Shueb ◽  
Nahida Tun Nisa ◽  
Salma Nisar
Keyword(s):  
Impact Factor ◽  
Peer Review ◽  
Research Performance ◽  
Early Access ◽  
Editorial Decision ◽  
Article Influence Score ◽  
Impact Data ◽  
Journal Impact ◽  
Immediacy Index ◽  
Article Influence

The manuscript processing timeline, a necessary facet of the publishing process, varies from journal to journal, and its influence on the journal impact needs to be studied. The current research looks into the correlation between the ‘Peer Review Metrics’ (submission to first editorial decision; submission to first post-review decision and submission to accept) and the ‘Journal Impact Data’ (2-year Impact Factor; 5-year Impact Factor; Immediacy Index; Eigenfactor Score and Article Influence Score). The data related to ‘Peer Review Metrics’ (submission to first editorial decision; submission to first post-review decision and submission to accept) and ‘Journal Impact Data’ (2-year Impact Factor; 5-year Impact Factor; Immediacy Index; Eigenfactor Score and Article Influence Score) were downloaded from the ‘Nature Research’ journals website https://www.nature.com/nature-portfolio/about/journal-metrics . Accordingly, correlations were drawn between the ‘Peer Review Metrics’ and the ‘Journal Impact Data’. If the time from ‘submission to first editorial decision’ decreases, the ‘Journal Impact Data’ increases and vice versa. However, an increase or decrease in the time from ‘submission to first editorial decision’ does not affect the ‘Eigenfactor Score’ of the journal and vice versa. An increase or decrease in the time from ‘submission to first post-review decision’ does not affect any ‘Journal Impact Data’ and vice versa. If the time from ‘submission to acceptance’ increases, the ‘Journal Impact Data’ (2-year Impact Factor, 5-year Impact Factor, Immediacy Index and Article Influence Score) also increases, and if the time from ‘submission to acceptance’ decreases, so will the ‘Journal Impact Data’. However, an increase or decrease in the time from ‘submission to acceptance’ does not affect the ‘Eigenfactor Score’ of the journal and vice versa. The study will act as a ready reference tool for the scholars to select the most appropriate submitting platforms for their scholarly endeavours. Furthermore, the performance and evaluative indicators responsible for a journal’s overall research performance can also be understood from a micro-analytical view, which will help the researchers select appropriate journals for their future scholarly submissions. Lengthy publication timelines are a big problem for the researchers because they are not able to get the credit for their research on time. Since the study validates a relationship between the ‘Peer Review Metrics’ and ‘Journal Impact Data’, the findings will be of great help in making an appropriate journal’s choice. The study can be an eye opener for the journal administrators who vocalise a speed-up publication process by enhancing certain areas of publication timeline. The study is the first of its kind that correlates the ‘Peer Review Metrics’ of the journals and the ‘Journal Impact Data’. The study’s findings are limited to the data retrieved from the ‘Nature Research’ journals and cannot be generalised to the full score of journals. The study can be extended across other publishers to generalise the findings. Even the articles’ early access availability concerning ‘Peer Review Metrics’ of the journals and the ‘Journal Impact Data’ can be studied.

scholarly journals Impact Factors Workgroup Report

2017 ◽  
Vol 1 ◽  
Author(s):  
Susie Allard ◽  
Ali Andalibi ◽  
Patty Baskin ◽  
Marilyn Billings ◽  
Eric Brown ◽  
...  
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Impact Factors ◽  
Journal Impact

Following up on recommendations from OSI 2016, this team will dig deeper into the question of developing and recommending new tools to repair or replace the journal impact factor (and/or how it is used), and propose actions the OSI community can take between now and the next meeting. What’s needed? What change is realistic and how will we get there from here?

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