Analysing Hate Speech against Migrants and Women through Tweets Using Ensembled Deep Learning Model

• Published in: Computational intelligence and neuroscience Vol. 2022; pp. 1 - 8
• Main Authors: Hasan, Asif, Sharma, Tripti, Khan, Azizuddin, Hasan Ali Al-Abyadh, Mohammed
• Format: Journal Article
• Language: English
• Published: United States Hindawi 10.04.2022; John Wiley & Sons, Inc
• Subjects: Abused women; Algorithms; Analysis; COVID-19; Data mining; Datasets; Deep Learning; Embedding; Female; Forecasts and trends; Hate; Hate speech; Humans; Machine learning; Male; Misogyny; Neural networks; Sentiment analysis; Social Media; Social networks; Social organization; Speech; Women; Xenophobia; United Kingdom; Spain; Europe; Montenegro
• ISSN: 1687-5265; 1687-5273; 1687-5273
• DOI: 10.1155/2022/8153791

Twitter’s popularity has exploded in the previous few years, making it one of the most widely used social media sites. As a result of this development, the strategies described in this study are now more beneficial. Additionally, there has been an increase in the number of people who express their v...