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29 articles for “Twitter”

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Research ArticleOpen accessIn the abstractScalable and Advanced Framework for Hate Speech Detection on Social Media Using BERT and GPT-2 through Encoder and Decoder ArchitecturesUsman, Nabeela Hasan, Syed Mohammad Khurshid QuadriHate speech is a major problem on social media platforms. Every day, numerous instances of hateful behavior based on race, ethnicity, religion, or gender are witnessed on social media. Most of the leading social media platforms like Instagram, Facebook, Twitter Reddit, etc., have strong community guidelines that condemn and restrict the exchange of hateful language/content in any form. Despite the … …Journal of Computer Science, Vol. 21, Issue 3 · 7 Feb 2025 · 7,325 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved SVM with Hyperparameter Tuning for Fake News DetectionAtcharaporn Nachaithong, Kittipol WisaengIn today’s digital age, accessing information has become effortless. An abundance of resources is available online, from trustworthy news outlets providing factual information to unverified opinions shared by anonymous individuals. With the advent of modern technology, social media platforms have revolutionized interaction and staying informed, providing instant access to news and information related to a wide range of topics. They … …Journal of Computer Science, Vol. 20, Issue 10 · 28 Aug 2024 · 5,636 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrompt-Based Data Augmentation with Large Language Models for Indonesian Gender-Based Hate Speech DetectionMuhammad Amien Ibrahim, Faisal, Zefanya Delvin Sulistiya, Tora Sangputra Yopie WinartoThe increasing amount of content on social media content makes the use of automatic moderation crucial for preserving a healthy online community and reducing the spread of offensive and abusive content, such as hate speech based on gender. Developing automated social media moderation using machine learning demands a large and balanced dataset. However, difficulties such as data scarcity and class … …Journal of Computer Science, Vol. 20, Issue 8 · 27 May 2024 · 5,881 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring Data Augmentation for Gender-Based Hate Speech DetectionMuhammad Amien Ibrahim, Samsul Arifin, Eko Setyo PurwantoSocial media moderation is a crucial component to establish healthy online communities and ensuring online safety from hate speech and offensive language. In many cases, hate speech may be targeted at specific gender which could be expressed in many different languages on social media platforms such as Indonesian Twitter. However, difficulties such as data scarcity and the imbalanced gender-based hate … …Journal of Computer Science, Vol. 19, Issue 10 · 29 Sep 2023 · 5,550 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Identification on Tweets to Forecast Cryptocurrency’s VolatilityRafael Calixto Ferreira de Araújo, Alex Sandro Roschildt Pinto, Mauri FerrandinCryptocurrencies have had a huge presence on social media since their creation. In current days, the constant increase of the mass of data produced by this environment has attracted several researchers to try to identify patterns with the potential to allow identification of the volatility in the crypto market before it happens. This approach involves the concept of the wisdom … …Journal of Computer Science, Vol. 19, Issue 5 · 3 May 2023 · 5,503 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmotion Recognition from Microblog Managing Emoticon with Text and Classifying using 1D CNNMd. Ahsan Habib, M. A. H. Akhand, Md. Abdus Samad KamalMicroblog, an online-based broadcast medium, is a widely used forum for people to share their thoughts and opinions. Recently, Emotion Recognition (ER) from microblogs is an inspiring research topic in diverse areas. In the machine learning domain, automatic emotion recognition from microblogs is a challenging task, especially, for better outcomes considering diverse content. Emoticon becomes very common in the text … …Journal of Computer Science, Vol. 18, Issue 12 · 7 Dec 2022 · 6,921 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Survey on Event Detection Models for Text Data StreamsWafa Zubair AL-Dyani, Farzana Kabir Ahmad, Siti Sakira KamaruddinEvent Detection (ED) is a study area that attracts the attention of decision-makers from various disciplines in order to help them in taking the right decision. ED has been examined on various text streams like Twitter, Facebook, Emails, Blogs, Web Forums and newswires. Many ED models have been proposed in literature. In general, ED model consists of six main phases: … …Journal of Computer Science, Vol. 16, Issue 7 · 14 Jul 2020 · 7,038 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Warehouse Design to Support Social Media Analysis in a Big Data EnvironmentCarlos Roberto Valêncio, Luis Marcello Moraes Silva, William Tenório et al.The volume of generated and stored data from social media has increased in the last decade. Therefore, analyzing and understanding this kind of data can offer relevant information in different contexts and can assist researchers and companies in the decision-making process. However, the data are scattered in a large volume, come from different sources, with different formats and are rapidly … …Journal of Computer Science, Vol. 16, Issue 2 · 20 Feb 2020 · 8,223 accessesView PDFCite
Research ArticleOpen accessIn the abstractEthnicity and Ethnic Perception of IndiansRavichandran Moorthy, Novel Lyndon, Er A. Choy et al.Problem statement: The discourse of ethnicity, race dominance and Islamization has dominated Malaysian politics since 1957, after several centuries of colonial rule. Although the country has achieved admirable socio-economic progress, the ethnic Indians situation has somewhat remained backward compared to the Malay and Chinese communities. The objective of this article is to examine how ethnic Indians recognize their ethnic identity … …Journal of Social Sciences, Vol. 7, Issue 4 · 16 Sep 2011 · 7,790 accessesView PDFCite