Journal of Intelligent Learning Systems and Applications最新文献

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Harnessing AI to Foster Equity in Education: Opportunities, Challenges, and Emerging Strategies 利用人工智能促进教育公平:机遇、挑战和新兴战略

Journal of Intelligent Learning Systems and Applications Pub Date : 2023-01-01 DOI: 10.4236/jilsa.2023.154009

Maryam Roshanaei, Hanna Olivares, Rafael Rangel Lopez

引用次数: 0

Social Media Cyberbullying Detection on Political Violence from Bangla Texts Using Machine Learning Algorithm 基于机器学习算法的孟加拉语文本政治暴力社交媒体网络欺凌检测

Journal of Intelligent Learning Systems and Applications Pub Date : 2023-01-01 DOI: 10.4236/jilsa.2023.154008

Md. Tofael Ahmed, Almas Hossain Antar, Maqsudur Rahman, Abu Zafor Muhammad Touhidul Islam, Dipankar Das, Md. Golam Rashed

{"title":"Social Media Cyberbullying Detection on Political Violence from Bangla Texts Using Machine Learning Algorithm","authors":"Md. Tofael Ahmed, Almas Hossain Antar, Maqsudur Rahman, Abu Zafor Muhammad Touhidul Islam, Dipankar Das, Md. Golam Rashed","doi":"10.4236/jilsa.2023.154008","DOIUrl":"https://doi.org/10.4236/jilsa.2023.154008","url":null,"abstract":"When someone threatens or humiliates another person online by sending those unpleasant messages or comments, this is known as Cyberbullying. Recently, Bangla text has been used much more often on social media. People communicate with others on social media through messages and comments. So bullies use social media as a rich environment to bully others, especially on political issues. Fights over Cyberbullying on political and social media posts are common today. Most of the time, it does a lot of damage. However, few works have been done for monitoring Bangla text on social media & no work has been done yet for detecting the bullying Bangla text on political issues due to the lack of annotated corpora and morphologic analyzers. In this work, we used several machine learning classifiers & a model. That will help to detect the Bangla bullying texts on social media. For this work, 11,000 Bangla texts have been collected from the comments section of political Facebook posts to make a new dataset and labelled the data as either bullied or not. This dataset has been used to train the machine learning classifier. The results indicate that Random Forest achieves superior accuracy of 91.08%.","PeriodicalId":152996,"journal":{"name":"Journal of Intelligent Learning Systems and Applications","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134982303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Camera Independent Motion Deblurring in Videos Using Machine Learning 使用机器学习的视频中的相机独立运动去模糊

Journal of Intelligent Learning Systems and Applications Pub Date : 2023-01-01 DOI: 10.4236/jilsa.2023.154007

Tyler Welander, Ronald Marsh, Bryce Gruber

引用次数: 0