Improving sentiment scoring mechanism: a case study on airline services
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 23 August 2018
Issue publication date: 28 September 2018
Abstract
Purpose
The purpose of this paper is to investigate the effect of including letter repetition commonly found within social media text and its impact in determining the sentiment scores for two major airlines in Malaysia.
Design/methodology/approach
A Sentiment Intensity Calculator (SentI-Cal) was developed by assigning individual weights to each letter repetition, and tested it using data collected from official Facebook pages of the airlines.
Findings
Evaluation metrics indicate that SentI-Cal outperforms the baseline tool Semantic Orientation Calculator (SO-CAL), with an accuracy of 90.7 percent compared to 58.33 percent for SO-CAL.
Practical implications
A more accurate sentiment score allows airline services to easily obtain a better understanding of the sentiments of their customers, hence providing opportunities in improving their airline services.
Originality/value
Proposed mechanism calculates sentiment intensity of social media text by assigning individual weightage to each repeated letter and exclamation mark thus producing a more accurate sentiment score.
Keywords
Acknowledgements
The authors would like to thank University of Malaya for supporting this study (RP028A-14AET) and Rayven Visvalingam for his contribution in the development of SentI-Cal.
Citation
Kaur, W. and Balakrishnan, V. (2018), "Improving sentiment scoring mechanism: a case study on airline services", Industrial Management & Data Systems, Vol. 118 No. 8, pp. 1578-1596. https://doi.org/10.1108/IMDS-07-2017-0300
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited