Results 11 to 20 of about 22,491,724 (165)
A Survey of Sentiment Analysis: Approaches, Datasets, and Future Research
Applied Sciences, 2023 Sentiment analysis is a critical subfield of natural language processing that focuses on categorizing text into three primary sentiments: positive, negative, and neutral.
Kian Long Tan, C. Lee, K. Lim
semanticscholar +1 more source
Survey on sentiment analysis: evolution of research methods and topics
Artificial Intelligence Review, 2023 Sentiment analysis, one of the research hotspots in the natural language processing field, has attracted the attention of researchers, and research papers on the field are increasingly published.
Jing Cui +3 more
semanticscholar +1 more source
MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis [PDF]
ACM Multimedia, 2020 Multimodal Sentiment Analysis is an active area of research that leverages multimodal signals for affective understanding of user-generated videos.
Devamanyu Hazarika +2 more
semanticscholar +1 more source
Social Network Analysis and Mining, 2023 Social media platform such as Twitter provides a space where users share their thoughts and opinion as well as connect, communicate, and contribute to certain topics using short, 140 characters posts, known as tweets.
Yuxing Qi, Zahratu Shabrina
semanticscholar +1 more source
Relational Graph Attention Network for Aspect-based Sentiment Analysis [PDF]
Annual Meeting of the Association for Computational Linguistics, 2020 Aspect-based sentiment analysis aims to determine the sentiment polarity towards a specific aspect in online reviews. Most recent efforts adopt attention-based neural network models to implicitly connect aspects with opinion words.
Kai Wang +4 more
semanticscholar +1 more source
Sentiment analysis: A survey on design framework, applications and future scopes
Artificial Intelligence Review, 2023 Sentiment analysis is a solution that enables the extraction of a summarized opinion or minute sentimental details regarding any topic or context from a voluminous source of data.
Monali Bordoloi, S. Biswas
semanticscholar +1 more source
Artificial Intelligence and Sentiment Analysis: A Review in Competitive Research
De Computis, 2023 As part of a business strategy, effective competitive research helps businesses outperform their competitors and attract loyal consumers. To perform competitive research, sentiment analysis may be used to assess interest in certain themes, uncover market
Hamed Taherdoost, Mitra Madanchian
semanticscholar +1 more source
VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text
International Conference on Web and Social Media, 2014 The inherent nature of social media content poses serious challenges to practical applications of sentiment analysis. We present VADER, a simple rule-based model for general sentiment analysis, and compare its effectiveness to eleven typical state-of-
C. J. Hutto, Eric Gilbert
semanticscholar +1 more source
Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis
Annual Meeting of the Association for Computational Linguistics, 2021 Aspect-based sentiment analysis is a fine-grained sentiment classification task. Recently, graph neural networks over dependency trees have been explored to explicitly model connections between aspects and opinion words.
Ruifan Li +5 more
semanticscholar +1 more source
Robust Image Sentiment Analysis Using Progressively Trained and Domain Transferred Deep Networks [PDF]
, 2015 Sentiment analysis of online user generated content is important for many social media analytics tasks. Researchers have largely relied on textual sentiment analysis to develop systems to predict political elections, measure economic indicators, and so ...
Jin, Hailin +3 more
core +1 more source