Improving sentiment scoring mechanism: a case study on airline services

Kaur, Wandeep and Balakrishnan, Vimala (2018) Improving sentiment scoring mechanism: a case study on airline services. Industrial Management & Data Systems, 118 (8). pp. 1578-1596. ISSN 0263-5577, DOI

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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.

Item Type: Article
Uncontrolled Keywords: Airline services; Scoring mechanism; Sentiment analysis; Social media; Text mining
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 19 Jul 2019 08:34
Last Modified: 19 Jul 2019 08:34

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