Performance Analysis of IES Journals using Text Processing Robots in PERL

Abstract

In the past, many approaches to measure the quality of journals are developed, e.g. 2-year Impact Factor (IF), 5-year IF, Eigenfactor Score, etc. Most of them are related to the number of citations of published papers. Unfortunately, the citation analysis is no easy task and almost impossible using manual examination of references. [1] This must be done by developing special computer tools for extracting data from various locations. Also, if only citations are of interest then this information is already preprocessed on different web sites such as GoogleScholar, PublishOrPerish, or WebOfKnowlege. However, if for example, someone wants to analyze the performance of editors, associate editors, and reviewers, then the problem is much more complicated than to treat the journal as a whole. These would require development of specialized computer tools for automatic data processing. The method proposed in this thesis is targeted at answering advanced performance analysis as listed before. A text processing robot is developed here using PERL, with the aid of its powerful regular expressions and Excel processing packages. In conjunction with the Internet Robot developed by [2], a large amount of valuable information can be extracted about performance of editors, associate editors, and reviewers.