{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T15:05:18Z","timestamp":1779203118079,"version":"3.51.4"},"reference-count":62,"publisher":"Emerald","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,9,28]]},"abstract":"<jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Design\/methodology\/approach<\/jats:title>\n                  <jats:p>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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Findings<\/jats:title>\n                  <jats:p>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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Practical implications<\/jats:title>\n                  <jats:p>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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Originality\/value<\/jats:title>\n                  <jats:p>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.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1108\/imds-07-2017-0300","type":"journal-article","created":{"date-parts":[[2018,8,23]],"date-time":"2018-08-23T08:14:56Z","timestamp":1535012096000},"page":"1578-1596","source":"Crossref","is-referenced-by-count":12,"title":["Improving sentiment scoring mechanism: a case study on airline services"],"prefix":"10.1108","volume":"118","author":[{"given":"Wandeep","family":"Kaur","sequence":"first","affiliation":[{"name":"University of Malaya Department of Information Systems, Faculty of Computer Science and Information Technology, , Kuala Lumpur,","place":["Malaysia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vimala","family":"Balakrishnan","sequence":"additional","affiliation":[{"name":"University of Malaya Department of Information Systems, Faculty of Computer Science and Information Technology, , Kuala Lumpur,","place":["Malaysia"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2018,8,23]]},"reference":[{"key":"2025072819441067100_ref001","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1016\/j.eswa.2016.02.028","article-title":"A rule dynamics approach to event detection in Twitter with its application to sports and politics","volume":"55","author":"Adedoyin-Olowe","year":"2016","journal-title":"Expert Systems with Applications"},{"key":"2025072819441067100_ref002","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/978-3-319-25343-5_3","volume-title":"Prominent Feature Extraction for Sentiment Analysis","author":"Agarwal","year":"2016"},{"key":"2025072819441067100_ref003","article-title":"A survey of sentiment lexicons","author":"Ahire","year":"2014"},{"key":"2025072819441067100_ref004","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.procs.2016.04.019","article-title":"Towards a disease outbreak notification framework using Twitter mining for smart home dashboards","volume":"82","author":"Almazidy","year":"2016","journal-title":"Procedia Computer Science"},{"key":"2025072819441067100_ref005","doi-asserted-by":"crossref","unstructured":"Ameur, H. and Jamoussi, S. 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(2011), \u201cCooooooooooooooollllllllllllll!!!!!!!!!!!!!!: using word lengthening to detect sentiment in microblogs\u201d, Proceedings of the Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, July 27, pp. 562-570."},{"key":"2025072819441067100_ref012","unstructured":"Delmonte, R., Tripodi, R. and G\u00cefu, D. (2013), \u201cOpinion and factivity analysis of Italian political discourse\u201d, IIR, pp. 88-99."},{"key":"2025072819441067100_ref013","first-page":"579","article-title":"Arabic sentiment analysis using supervised classification","author":"Duwairi","year":"2014"},{"key":"2025072819441067100_ref014","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/978-3-319-10873-5_98","volume-title":"The Sustainable Global Marketplace","author":"Ford","year":"2015"},{"key":"2025072819441067100_ref015","unstructured":"Gezici, G., Yanikoglu, B., Tapucu, D. and Saygin, Y. 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(2014), \u201cAutomatic creation of stock market lexicons for sentiment analysis using StockTwits data\u201d, Proceedings of the 18th International Database Engineering & Applications Symposium, ACM, July 7, pp. 115-123.","DOI":"10.1145\/2628194.2628235"},{"key":"2025072819441067100_ref041","article-title":"The development and psychometric properties of LIWC2015","author":"Pennebaker","year":"2015"},{"key":"2025072819441067100_ref042","unstructured":"Pugsee, P., Chongvisuit, T. and Nakorn, K.N. (2015), \u201cOpinion mining on Twitter data for airline services\u201d, Proceeding of the 5th International Workshop on Computer Science and Engineering: Information Processing and Control Engineering (WCSE), April 15, pp. 639-644."},{"key":"2025072819441067100_ref043","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.knosys.2016.12.018","article-title":"A novel automatic satire and irony detection using ensembled feature selection and data mining","volume":"120","author":"Ravi","year":"2017","journal-title":"Knowledge-Based Systems"},{"issue":"1","key":"2025072819441067100_ref044","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.ijmedinf.2015.09.007","article-title":"SentiHealth-Cancer: a sentiment analysis tool to help detecting mood of patients in online social networks","volume":"85","author":"Rodrigues","year":"2016","journal-title":"International Journal of Medical Informatics"},{"key":"2025072819441067100_ref045","doi-asserted-by":"crossref","unstructured":"Rosenthal, S., Nakov, P., Kiritchenko, S., Mohammad, S., Ritter, A. and Stoyanov, V. 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