Conference paper Open Access

# A Neuro-Fuzzy System to Calculate a Journal Internationality Index

Perakakis, Pandelis; Taylor, Michael; Buela-Casal, Gualberto; Checa, Purificacion

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{
"publisher": "Zenodo",
"DOI": "10.5281/zenodo.45541",
"title": "A Neuro-Fuzzy System to Calculate a Journal Internationality Index",
"issued": {
"date-parts": [
[
2005,
9,
13
]
]
},
"abstract": "<p>Internationality as a concept is being applied ambiguously and erroneously, particularly in the world of academic journal publication where it is often used as a quality indicator. Although different qualitative criteria have been used by scientometrists in order to attempt a measure of internationality in various contexts, it is now clear that the literal definition of internationality is a minimal one while other proposed measures based on individual criteria fail to provide a complete and accurate assessment. As such, internationality remains to be defined2.</p>\n\n<p>Here, we present a holistic approach to the problem based on fuzzy logic. We surveyed, critically-assessed and pruned the set of internationality criteria in the context of academic publishing, selecting those that are semantically precise and amenable to <em>quantitative </em>measure. We have tested the ability of each criterion to measure internationality by applying them to four thematically-connected journals from the field of Health and Clinical Psychology, using descriptive</p>\n\n<p>statistics and the Gini Coefficient. The results of this case study revealed that, in the absence of a method of numerically weighting the criteria, any measurement of internationality remains ambiguous and incorrect.</p>\n\n<p>We propose that internationality is best represented by a neuro-fuzzy system of fuzzy sets of the weighted criteria linked by fuzzy rules in a multi-layer perceptron, whose output defuzzification gives a new measure &ndash; a <em>Journal Internationality Index </em>akin to the Impact Factor for citations. Viewing internationality in this way as an approximated fuzzy function means a quantitative measure can be found while keeping intact its semantic rule origins and meaning.&nbsp;</p>",
"author": [
{
"given": "Pandelis",
"family": "Perakakis"
},
{
"given": "Michael",
"family": "Taylor"
},
{
"given": "Gualberto",
"family": "Buela-Casal"
},
{
"given": "Purificacion",
"family": "Checa"
}
],
"type": "paper-conference",
"id": "45541"
}
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