A word embedding technique for sentiment analysis of social media to understand the relationship between Islamophobic incidents and media portrayal of Muslim communities
Islamophobia is a sentiment against the Muslim community; recently, atrocities towards Muslim communities witnessed this sentiment globally. This research investigates the correlation between how news stories covered by mainstream news channels impede the hate speech/Islamophobic sentiment. To exami...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2022-01-01
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| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-838.pdf |
| _version_ | 1798024571614396416 |
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| author | Ishfaq Ali Muhammad Asif Isma Hamid Muhammad Umer Sarwar Fakhri Alam Khan Yazeed Ghadi |
| author_facet | Ishfaq Ali Muhammad Asif Isma Hamid Muhammad Umer Sarwar Fakhri Alam Khan Yazeed Ghadi |
| author_sort | Ishfaq Ali |
| collection | DOAJ |
| description | Islamophobia is a sentiment against the Muslim community; recently, atrocities towards Muslim communities witnessed this sentiment globally. This research investigates the correlation between how news stories covered by mainstream news channels impede the hate speech/Islamophobic sentiment. To examine the objective mentioned above, we shortlisted thirteen mainstream news channels and the ten most widely reported Islamophobic incidents across the globe for experimentation. Transcripts of the news stories are scraped along with their comments, likes, dislikes, and recommended videos as the users’ responses. We used a word embedding technique for sentiment analysis, e.g., Islamophobic or not, three textual variables, video titles, video transcripts, and comments. This sentiment analysis helped to compute metric variables. The I-score represents the extent of portrayals of Muslims in a particular news story. The next step is to calculate the canonical correlation between video transcripts and their respective responses, explaining the relationship between news portrayal and hate speech. This study provides empirical evidence of how news stories can promote Islamophobic sentiments and eventually atrocities towards Muslim communities. It also provides the implicit impact of reporting news stories that may impact hate speech and crime against specific communities. |
| first_indexed | 2024-04-11T18:04:47Z |
| format | Article |
| id | doaj.art-ee2ad40c22344235b951ae02a7614e44 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-04-11T18:04:47Z |
| publishDate | 2022-01-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-ee2ad40c22344235b951ae02a7614e442022-12-22T04:10:22ZengPeerJ Inc.PeerJ Computer Science2376-59922022-01-018e83810.7717/peerj-cs.838A word embedding technique for sentiment analysis of social media to understand the relationship between Islamophobic incidents and media portrayal of Muslim communitiesIshfaq Ali0Muhammad Asif1Isma Hamid2Muhammad Umer Sarwar3Fakhri Alam Khan4Yazeed Ghadi5Department of Computer Science, National Textile University, Faisalabad, Punjab, PakistanDepartment of Computer Science, National Textile University, Faisalabad, Punjab, PakistanDepartment of Computer Science, National Textile University, Faisalabad, Punjab, PakistanDepartment of Computer Science, Government College University, Faisalabad, Punjab, PakistanDepartment of Information and Computer Science, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaDepartment of Software Engineering/Computer Science, Al Ain University, Al Ain, UAEIslamophobia is a sentiment against the Muslim community; recently, atrocities towards Muslim communities witnessed this sentiment globally. This research investigates the correlation between how news stories covered by mainstream news channels impede the hate speech/Islamophobic sentiment. To examine the objective mentioned above, we shortlisted thirteen mainstream news channels and the ten most widely reported Islamophobic incidents across the globe for experimentation. Transcripts of the news stories are scraped along with their comments, likes, dislikes, and recommended videos as the users’ responses. We used a word embedding technique for sentiment analysis, e.g., Islamophobic or not, three textual variables, video titles, video transcripts, and comments. This sentiment analysis helped to compute metric variables. The I-score represents the extent of portrayals of Muslims in a particular news story. The next step is to calculate the canonical correlation between video transcripts and their respective responses, explaining the relationship between news portrayal and hate speech. This study provides empirical evidence of how news stories can promote Islamophobic sentiments and eventually atrocities towards Muslim communities. It also provides the implicit impact of reporting news stories that may impact hate speech and crime against specific communities.https://peerj.com/articles/cs-838.pdfComputer aided designMobile and ubiquitous computingIslamophobicNews storiesSentiment analysisNatural language processing |
| spellingShingle | Ishfaq Ali Muhammad Asif Isma Hamid Muhammad Umer Sarwar Fakhri Alam Khan Yazeed Ghadi A word embedding technique for sentiment analysis of social media to understand the relationship between Islamophobic incidents and media portrayal of Muslim communities PeerJ Computer Science Computer aided design Mobile and ubiquitous computing Islamophobic News stories Sentiment analysis Natural language processing |
| title | A word embedding technique for sentiment analysis of social media to understand the relationship between Islamophobic incidents and media portrayal of Muslim communities |
| title_full | A word embedding technique for sentiment analysis of social media to understand the relationship between Islamophobic incidents and media portrayal of Muslim communities |
| title_fullStr | A word embedding technique for sentiment analysis of social media to understand the relationship between Islamophobic incidents and media portrayal of Muslim communities |
| title_full_unstemmed | A word embedding technique for sentiment analysis of social media to understand the relationship between Islamophobic incidents and media portrayal of Muslim communities |
| title_short | A word embedding technique for sentiment analysis of social media to understand the relationship between Islamophobic incidents and media portrayal of Muslim communities |
| title_sort | word embedding technique for sentiment analysis of social media to understand the relationship between islamophobic incidents and media portrayal of muslim communities |
| topic | Computer aided design Mobile and ubiquitous computing Islamophobic News stories Sentiment analysis Natural language processing |
| url | https://peerj.com/articles/cs-838.pdf |
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