September 13, 2005 Conference paper Open Access

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"
}