Alternative bibliometrics from the web of knowledge surpasses the impact factor in a 2-year ahead annual citation calculation: Linear mixed-design models' analysis of neuroscience journals

2018 ◽  
Vol 66 (1) ◽  
pp. 96 ◽  
Author(s):  
Ernesto Roldan-Valadez ◽  
Araceli Diaz-Ruiz ◽  
Ulises Orbe-Arteaga ◽  
Camilo Rios
Keyword(s):  
Impact Factor ◽  
Mixed Design ◽  
Design Models ◽  
Web Of Knowledge ◽  
The Impact ◽  
The Web

scholarly journals Modeling and Prediction of the Impact Factor of Journals Using Open-Access Databases

2020 ◽  
Vol 49 (5) ◽  
pp. 35-58
Author(s):  
Matthias Templ
Keyword(s):  
Open Access ◽  
Impact Factor ◽  
Journal Impact Factor ◽  
Web Of Science ◽  
Functional Relationships ◽  
Modeling And Prediction ◽  
Novel Approach ◽  
The Impact ◽  
Journal Impact ◽  
The Web

This article is motivated by the work as editor-in-chief of the Austrian Journal of Statistics and contains detailed analyses about the impact of the Austrian Journal of Statistics. The impact of a journal is typically expressed by journal metrics indicators. One of the important ones, the journal impact factor is calculated from the Web of Science (WoS) database by Clarivate Analytics. It is known that newly established journals or journals without membership in big publishers often face difficulties to be included, e.g., in the Science Citation Index (SCI) and thus they do not receive a WoS journal impact factor, as it is the case for example, for the Austrian Journal of Statistics. In this study, a novel approach is pursued modeling and predicting the WoS impact factor of journals using open access or partly open-access databases, like Google Scholar, ResearchGate, and Scopus. I hypothesize a functional linear dependency between citation counts in these databases and the journal impact factor. These functional relationships enable the development of a model that may allow estimating the impact factor for new, small, and independent journals not listed in SCI. However, only good results could be achieved with robust linear regression and well-chosen models. In addition, this study demonstrates that the WoS impact factor of SCI listed journals can be successfully estimated without using the Web of Science database and therefore the dependency of researchers and institutions to this popular database can be minimized. These results suggest that the statistical model developed here can be well applied to predict the WoS impact factor using alternative open-access databases. 

scholarly journals Effect of Number of Versions on Receiving High Citations

2020 ◽  
Author(s):  
Nader Ale Ebrahim ◽  
Hadi Salehi
Keyword(s):  
Impact Factor ◽  
Google Scholar ◽  
H Index ◽  
Journal Quality ◽  
Scopus Database ◽  
Number Of Citations ◽  
The Impact ◽  
The Web

Nowadays, the h-index is an index that attempts to measure both the productivity and impact of the published work of a scientist or scholar. The index is based upon the set of the scientist's most cited papers and the number of citations that they have received in other publications. Besides, the most commonly used measure of journal quality is Impact Factor. This is a number which attempts to measure the impact of a journal in terms of the average number of citations to recent articles published in the journal. So, receiving more citation is very important for authors and journals to get high h-index and impact factor. In this paper, we tried to analyses the effect of the number of available version from the web on receive more citations. We analyzed 10162 papers which are published in Scopus database in year 2010. Then we developed a software to collect the number of citations and versions of each paper from Google Scholar automatically.

scholarly journals Nova fórmula revisada para o cálculo do fator de impacto web (FIW) │ New revised formula for calculating Web Impact Factor

2013 ◽  
Vol 9 (1) ◽  
Author(s):  
Nadia Vanti
Keyword(s):  
Impact Factor ◽  
Scientific Production ◽  
Natural Logarithm ◽  
Webometric Indicators ◽  
De Se ◽  
History Of ◽  
New Formula ◽  
The Impact ◽  
Original Formula ◽  
The Web

Resumo Apresenta um histórico da medição do impacto da produção científica e mostra a necessidade de estender tal avaliação à web.  Descreve como vem sendo calculado o fator de impacto em sítios web e propõe uma mudança na fórmula original, com a inclusão de um logaritmo natural ao seu denominador, a fim de se obter resultados mais acurados.  A nova fórmula é aplicada aos sítios web das universidades federais da região sudeste do Brasil, obtendo-se resultados mais acurados.Palavras-chave Impacto da produção científica, Indicadores webométricos, Fator de Impacto Web, Fórmula do FIW, Logaritmo natural. Abtsract Displays a history of measuring the impact of scientific articles and shows the need to extend this assessment to the web. Describes how the impact factor on websites has been calculated and proposes a change in the original formula, with the inclusion of a natural logarithm in its denominator in order to obtain more accurate results. The new formula is applied to websites of federal universities in Southeastern Brazil.Keywords Impact of scientific production, Webometric indicators, Web Impact Factor Formula FIW, Natural logarithm.

scholarly journals Curve Estimation Models for Estimation and Prediction of Impact Factor and CiteScore Using the Journal Percentiles: A Case Study of Telecommunication Journals

2019 ◽  
Vol 15 (14) ◽  
pp. 31 ◽  
Author(s):  
Hilary I Okagbue ◽  
Patience I Adamu ◽  
Sheila A Bishop ◽  
Emmanuela C M Obasi ◽  
Adedotun O Akinola
Keyword(s):  
Impact Factor ◽  
Web Of Science ◽  
Manuscript Submission ◽  
Curve Estimation ◽  
Subject Classifications ◽  
Positive Correlations ◽  
The Impact ◽  
The Web ◽  
Estimation Models

<p class="0abstract">The impact factor  and CiteScore of journals are known to be positively correlated with journal percentile but the use of the later to predict the formers are scarcely discussed, especially for journals in a specific subject classifications based on the web of science. This paper proposed different curve estimation models for predicting the impact factor and CiteScore of 89 telecommunication journals using their corresponding percentiles. Out of the 11 models, only Logistic, exponential, Growth and Compound models are the best models for predicting the impact factor and CiteScore using their corresponding journal percentiles. The models were chosen because of their high values of R Square and Adjusted R Square and low values of the standard error of the estimates. In addition, strong significant positive correlations were obtained between impact factor and the CiteScore of the journals. The findings will help authors and editors in decision making as regards to manuscript submission and planning.</p>

scholarly journals Effect of Number of Versions on Receiving High Citations

2020 ◽  
Author(s):  
Nader Ale Ebrahim ◽  
Hadi Salehi
Keyword(s):  
Impact Factor ◽  
Google Scholar ◽  
H Index ◽  
Journal Quality ◽  
Scopus Database ◽  
Number Of Citations ◽  
The Impact ◽  
The Web

Nowadays, the h-index is an index that attempts to measure both the productivity and impact of the published work of a scientist or scholar. The index is based upon the set of the scientist's most cited papers and the number of citations that they have received in other publications. Besides, the most commonly used measure of journal quality is Impact Factor. This is a number which attempts to measure the impact of a journal in terms of the average number of citations to recent articles published in the journal. So, receiving more citation is very important for authors and journals to get high h-index and impact factor. In this paper, we tried to analyses the effect of the number of available version from the web on receive more citations. We analyzed 10162 papers which are published in Scopus database in year 2010. Then we developed a software to collect the number of citations and versions of each paper from Google Scholar automatically.

The More Control, the Better?

2014 ◽  
Vol 26 (2) ◽  
pp. 81-91 ◽  
Author(s):  
Jeeyun Oh ◽  
Mun-Young Chung ◽  
Sangyong Han
Keyword(s):  
Mixed Design ◽  
Negative Effects ◽  
Story Structure ◽  
Content Type ◽  
High User ◽  
User Control ◽  
Rigorous Research ◽  
Control Versus ◽  
The Media ◽  
The Impact

Despite of the popularity of interactive movie trailers, rigorous research on one of the most apparent features of these interfaces – the level of user control – has been scarce. This study explored the effects of user control on users’ immersion and enjoyment of the movie trailers, moderated by the content type. We conducted a 2 (high user control versus low user control) × 2 (drama film trailer versus documentary film trailer) mixed-design factorial experiment. The results showed that the level of user control over movie trailer interfaces decreased users’ immersion when the trailer had an element of traditional story structure, such as a drama film trailer. Participants in the high user control condition answered that they were less fascinated with, absorbed in, focused on, mentally involved with, and emotionally affected by the movie trailer than participants in the low user control condition only with the drama movie trailer. The negative effects of user control on the level of immersion for the drama trailer translated into users’ enjoyment. The impact of user control over interfaces on immersion and enjoyment varies depending on the nature of the media content, which suggests a possible trade-off between the level of user control and entertainment outcomes.

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