Analytical evaluation of emerging scientific trends in business intelligence through the utilisation of burst detection algorithm | Zendy

Iman Raeesi Vanani | Zendy; Seyed Mohammad Jafar Jalali | Zendy

Open Access

Analytical evaluation of emerging scientific trends in business intelligence through the utilisation of burst detection algorithm

Author(s) -

Iman Raeesi Vanani,

Seyed Mohammad Jafar Jalali

Publication year - 2017

Publication title -

international journal of bibliometrics in business and management

Language(s) - English

Resource type - Journals

eISSN - 2057-0546

pISSN - 2057-0538

DOI - 10.1504/ijbbm.2017.10003443

Subject(s) - business intelligence , computer science , data science , business , data mining

Business intelligence has become mainstream in recent scientific research trends. The purpose of this research is to study the emerging and fading themes of the business intelligence domain through an analytical overview of keywords, titles and abstracts. Among scientometrics methods for representing the emergent and disappearing trends, the 'burst detection' algorithm has been chosen and applied to the current dataset of high-ranked international papers which can help scholars and practitioners to understand a better overview of business intelligence field by visualising the changes in a recent time period. For this purpose, the data related to business intelligence has been gathered from Web of Science (WoS) core collection dataset between the years 1980-2014 and the burst detection algorithm has been applied on the 'abstract', 'title' and 'keywords' of the dataset which has shown interesting informative results for the future researchers to concentrate on.

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