Hate Speech Patterns in Social Media: A Methodological Framework and Fat Stigma Investigation Incorporating Sentiment Analysis, Topic Modelling and Discourse Analysis

Simple item page
dc.citation.volume27
dc.contributor.authorWanniarachchi V
dc.contributor.authorScogings C
dc.contributor.authorSusnjak T
dc.contributor.authorMathrani A
dc.date.available8/02/2023
dc.date.issued8/02/2023
dc.description© 2023 The Author/s
dc.description.abstractSocial media offers users an online platform to freely express themselves; however, when users post opinionated and offensive comments that target certain individuals or communities, this could instigate animosity towards them. Widespread condemnation of obesity (fatness) has led to much fat stigmatizing content being posted online. A methodological framework that uses a novel mixed-method approach for unearthing hate speech patterns from large text-based corpora gathered from social media is proposed. We explain the use of computer-mediated quantitative methods comprising natural language processing techniques such as sentiment analysis, emotion analysis and topic modelling, along with qualitative discourse analysis. Next, we have applied the framework to a corpus of texts on gendered and weight-based data that have been extracted from Twitter and Reddit. This assisted in the detection of different emotions being expressed, the composition of word frequency patterns and the broader fat-based themes underpinning the hateful content posted online. The framework has provided a synthesis of quantitative and qualitative methods that draw on social science and data mining techniques to build real-world knowledge in hate speech detection. Current information systems research is limited in its use of mixed analytic approaches for studying hate speech in social media. Our study therefore contributes to future research by establishing a roadmap for conducting mixed-method analyses for better comprehension and understanding of hate speech patterns.
dc.description.confidentialFALSE
dc.format.extent1 - 29 (29)
dc.identifier.citationAustralasian Journal of Information Systems, 2023, 27 pp. 1 - 29 (29)
dc.identifier.doi10.3127/ajis.v27i0.3929
dc.identifier.elements-id459575
dc.identifier.harvestedMassey_Dark
dc.identifier.issn1039-7841
dc.identifier.urihttps://hdl.handle.net/10179/18013
dc.publisherAustralasian Association for Information Systems and Australian Computer Society
dc.relation.isPartOfAustralasian Journal of Information Systems
dc.relation.urihttps://journal.acs.org.au/index.php/ajis/article/view/3929/1307
dc.subjectsocial media
dc.subjecthate speech
dc.subjectsentiment analysis
dc.subjecttopic modelling
dc.subjectdiscourse analysis
dc.subjectfat stigma
dc.subject.anzsrc0806 Information Systems
dc.subject.anzsrc1503 Business and Management
dc.titleHate Speech Patterns in Social Media: A Methodological Framework and Fat Stigma Investigation Incorporating Sentiment Analysis, Topic Modelling and Discourse Analysis
dc.typeJournal article
pubs.notesNot known
pubs.organisational-group/Massey University
pubs.organisational-group/Massey University/College of Sciences
pubs.organisational-group/Massey University/College of Sciences/PVC's Office - College of Sciences
pubs.organisational-group/Massey University/College of Sciences/School of Mathematical and Computational Sciences
Files
Collections
Journal Articles