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Author Impact Factor: tracking the dynamics of individual scientific impact.

Pan RK, Fortunato S - Sci Rep (2014)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering and Computational Science, Aalto University School of Science, P.O. Box 12200, FI-00076, Finland.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

The distribution of the difference between the publication year of the citing article and the publication year of the cited article, for different subjects.This suggests proper aggregation periods to compute the author impact factor. The distribution is generated from papers published between 1980–2010. The red dashed line indicates the 5 years period we choose to compute the AIF: the probability of having laps longer than 5 years is exponentially suppressed.
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f2: The distribution of the difference between the publication year of the citing article and the publication year of the cited article, for different subjects.This suggests proper aggregation periods to compute the author impact factor. The distribution is generated from papers published between 1980–2010. The red dashed line indicates the 5 years period we choose to compute the AIF: the probability of having laps longer than 5 years is exponentially suppressed.

Mentions: Furthermore, papers usually cite recent publications, so few years after publication the number of cites received by a paper in a year decreases. In Fig. 2 we plot the distribution of the difference in the publication year of the citing article and the cited article. The distribution varies with the discipline. However, we can see that large gaps are suppressed. Hence, the aggregation period should not be very large, as in that case papers published in the initial part of the period would be hardly cited after that. During the period 1980–2010 for Physics about 44% of the citations go to articles published during the immediate past 5 years. For Medicine, Chemistry and Mathematics the respective fractions are 47%, 41% and 30%. As these fractions are considerable, we limit our aggregation period to 5 years. Another reason for choosing the 5 years time window is to make the AIF congruent to the 5-years journal impact factor provided by Thomson Reuters. In the Supplementary Information we also show the AIF computed in a 2 years period (like the 2 year journal impact factor), which shows relatively more fluctuations.


Author Impact Factor: tracking the dynamics of individual scientific impact.

Pan RK, Fortunato S - Sci Rep (2014)

The distribution of the difference between the publication year of the citing article and the publication year of the cited article, for different subjects.This suggests proper aggregation periods to compute the author impact factor. The distribution is generated from papers published between 1980–2010. The red dashed line indicates the 5 years period we choose to compute the AIF: the probability of having laps longer than 5 years is exponentially suppressed.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4017244&req=5

f2: The distribution of the difference between the publication year of the citing article and the publication year of the cited article, for different subjects.This suggests proper aggregation periods to compute the author impact factor. The distribution is generated from papers published between 1980–2010. The red dashed line indicates the 5 years period we choose to compute the AIF: the probability of having laps longer than 5 years is exponentially suppressed.
Mentions: Furthermore, papers usually cite recent publications, so few years after publication the number of cites received by a paper in a year decreases. In Fig. 2 we plot the distribution of the difference in the publication year of the citing article and the cited article. The distribution varies with the discipline. However, we can see that large gaps are suppressed. Hence, the aggregation period should not be very large, as in that case papers published in the initial part of the period would be hardly cited after that. During the period 1980–2010 for Physics about 44% of the citations go to articles published during the immediate past 5 years. For Medicine, Chemistry and Mathematics the respective fractions are 47%, 41% and 30%. As these fractions are considerable, we limit our aggregation period to 5 years. Another reason for choosing the 5 years time window is to make the AIF congruent to the 5-years journal impact factor provided by Thomson Reuters. In the Supplementary Information we also show the AIF computed in a 2 years period (like the 2 year journal impact factor), which shows relatively more fluctuations.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering and Computational Science, Aalto University School of Science, P.O. Box 12200, FI-00076, Finland.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus