Business Decision Support System based on Sentiment Analysis

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Stephen Opoku Oppong 1,* Dominic Asamoah 2 Emmanuel Ofori Oppong 2 Derrick Lamptey 1

1. Faculty of Computing and Information Systems Ghana Technology University College, Ghana

2. Department of Computer Science Kwame Nkrumah University of Science and Technology, Ghana

* Corresponding author.


Received: 13 Aug. 2018 / Revised: 16 Sep. 2018 / Accepted: 18 Oct. 2018 / Published: 8 Jan. 2019

Index Terms

Emotion, Sentiment analysis, Classification, Annotation, Business intelligence


Since organizational decisions are vital to organizational development, customers’ views and feedback are equally important to inform good decisions. Given this relevance, this paper seeks to automate a sentiment analysis system - SentDesk- that can aid tracking sentiments in customers’ reviews and feedback. The study was contextualised in some business organisations in Ghana. Three business organizational marketers were made to annotate emotions and as well tag sentiments to each instance in the corpora. Kappa and Krippendoff coefficients were computed to obtain the annotation agreement in the corpora. The SentDesk system was evaluated in the environment alongside comparing the output to that of the average sentiments tagged by the marketers. Also, the SentDesk system was evaluated in the environment by the selected marketers after they had tested the platform. By finding the average kappa value from the corpora (CFR + ISEAR), the average kappa coefficient was found to be 0.40 (40%). The results of evaluating the SentDesk system with humans shows that the system performed as better as humans. The study also revealed that, while annotating emotions and sentiments in the datasets, counsellor’s own emotions influences their perception of emotions.

Cite This Paper

Stephen Opoku Oppong, Dominic Asamoah, Emmanuel Ofori Oppong, Derrick Lamptey, "Business Decision Support System based on Sentiment Analysis", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.11, No.1, pp. 36-49, 2019. DOI:10.5815/ijieeb.2019.01.05


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