Sentiment Analysis On Indian Indigenous Languages: A Review On Multilingual Opinion Mining
원문 초록
An increase in the use of smartphones has laid to the use of the internet and social media platforms. The most commonly used social media platforms are Twitter, Facebook, WhatsApp and Instagram. People are sharing their personal experiences, reviews, feedbacks on the web. The information which is available on the web is unstructured and enormous. Hence, there is a huge scope of research on understanding the sentiment of the data available on the web. Sentiment Analysis (SA) can be carried out on the reviews, feedbacks, discussions available on the web. There has been extensive research carried out on SA in the English language, but data on the web also contains different other languages which should be analyzed. This paper aims to analyze, review and discuss the approaches, algorithms, challenges faced by the researchers while carrying out the SA on Indigenous languages.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Enhancing Rhetorical Figure Annotation: An Ontology-Based Web Application with RAG Integration
PL-FGSA: A Prompt Learning Framework for Fine-Grained Sentiment Analysis Based on MindSpore
Analysing Public Transport User Sentiment on Low Resource Multilingual Data
Understanding and Tackling Label Errors in Individual-Level Nature Language Understanding
DCR: Quantifying Data Contamination in LLMs Evaluation
AI Wizards at CheckThat! 2025: Enhancing Transformer-Based Embeddings with Sentiment for Subjectivity Detection in News Articles
토론
이 논문과 연결된 포럼 글이 아직 없습니다.