Automatic Labelling of Malay Cyberbullying Twitter Corpus using Combinations of Sentiment, Emotion and Toxicity Polarities

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Automatic Labelling of Malay Cyberbullying Twitter Corpus using Combinations of Sentiment, Emotion and Toxicity Polarities

Automatic labelling is essential in large corpuses. Engaging in human experts to label can be challenging. Semantic understanding can differ from one labeler to another based on individual's language ability. Platforms such as AmazonTurk are not able to ensure the quality of annotations in ever...

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Bibliographic Details
Published in:	ACM International Conference Proceeding Series
Main Author:	Maskat R.; Faizzuddin Zainal M.; Ismail N.; Ardi N.; Ahmad A.; Daud N.
Format:	Conference paper
Language:	English
Published:	Association for Computing Machinery 2020
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102973769&doi=10.1145%2f3446132.3446412&partnerID=40&md5=5c668651d4c77ca8be2f2761336f508e

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