The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
IJACSA research on sentiment analysis — including literature reviews, social media and news sentiment, and applications such as stock price prediction.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed August 2026
This study presents an integrated framework containing sentiment and network analysis for social media modernization to mitigate the spread of harmful viral posts. The research focuses on detecting harmful content, ident…
Interest in multimodal sentiment analysis has grown significantly due to the widespread sharing of text and images on social platforms. Existing approaches often emphasize either sentiment features within textual–visual…
Floating markets in South Kalimantan are culturally significant heritage destinations whose contemporary reputation is increasingly shaped by user-generated content on digital platforms. This study analyzes public percep…
Cross-lingual sentiment analysis (CLSA) has become increasingly important in natural language processing and machine learning, enabling the understanding of opinions across diverse linguistic communities, particularly in…
Sentiment and emotion recognition in dynamic English communication require intelligent systems capable of reasoning beyond surface correlations among linguistic, acoustic, and visual cues. Traditional multimodal approach…
The massive growth in user reviews on the online travel agent (OTA) website can be automatically processed using sentiment analysis to understand consumer satisfaction or feedback. Sentiment analysis is commonly implemen…
In China's retail-focused stock market, the influence of social media sentiment during off-hours on the next day's opening price has received limited attention. This paper takes Kweichow Moutai—a leading Chinese company…
Sentiment analysis is a fundamental task in natural language processing with wide-ranging applications, from customer feedback monitoring to healthcare and social media analytics. While recent research has mainly emphasi…
Sentiment classification is a core task in natural language processing (NLP), enabling automated interpretation of opinionated text across domains, such as social media, e-commerce, and healthcare. While numerous models…
Tokenization is a foundational step in the NLP pipeline, and its design strongly influences the performance of transformer-based models, particularly for morphologically rich and low-resource languages such as Assamese.…
