Results 61 to 70 of about 22,264,370 (303)
Knowledge-Guided Sentiment Analysis Via Learning From Natural Language Explanations
IEEE Access, 2021 Sentiment analysis is crucial for studying public opinion since it can provide us with valuable information. Existing sentiment analysis methods rely on finding the sentiment element from the content of user-generated.
Zunwang Ke +4 more
doaj +1 more source
A Perspective on Sentiment Analysis
CoRR, 2016 Opinion;Feature Engineering; Sentiment;Subjective Sentence;Objective;Contextual Polarity;Sentiment Lexicon;Classification;Machine ...
K. Paramesha, K. C. Ravishankar
openaire +2 more sources
A Training-Optimization-Based Method for Constructing Domain-Specific Sentiment Lexicon
Complexity, 2021 Sentiment analysis has been widely used in text mining of social media to discover valuable information from user reviews. Sentiment lexicon is an essential tool for sentiment analysis.
Maokang Du, Xiaoguang Li, Longyan Luo
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background and Aims Infant bone and soft tissue neoplasms present distinct clinical challenges and lack large‐scale data to inform treatment decisions. This study aims to characterize bone and soft tissue neoplasms in infants in Canada and to compare their outcomes with those of older pediatric patients.
Samuel Sassine +21 more
wiley +1 more source
Sentiment Analysis in the News
Proceedings of the Language Resources and Evaluation Conference, 2010 Recent years have brought a significant growth in the volume of research in sentiment analysis, mostly on highly subjective text types (movie or product reviews). The main difference these texts have with news articles is that their target is clearly defined and unique across the text.
Alexandra Balahur +7 more
openaire +3 more sources
A hybrid approach to sentiment analysis [PDF]
2016 IEEE Congress on Evolutionary Computation (CEC), 2016 This contribution presents a hybrid approach to Sentiment Analysis (SA) encompassing the use of semantic rules, fuzzy sets, unsupervised machine learning techniques and a sentiment lexicon improved with the support of Senti-WordNet. A Hybrid Standard Classification is first carried out, which is further enhanced into a Hybrid Advanced approach ...
Orestes Appel +3 more
openaire +2 more sources
Exploring Sentiment Analysis on Twitter: Investigating Public Opinion on Migration in Brazil from 2015 to 2020 [PDF]
, 2023 openTechnology has reshaped societal interaction and the expression of opinions. Migration is a prominent trend, and analysing social media discussions provides insights into societal perspectives.
BASELICE PELICIONI, ANA BEATRIZ
core
Refined Global Word Embeddings Based on Sentiment Concept for Sentiment Analysis
IEEE Access, 2021 Sentiment Analysis is an important research direction of natural language processing, and it is widely used in politics, news and other fields. Word embeddings play a significant role in sentiment analysis.
Yabing Wang +5 more
doaj +1 more source
FEBS Letters, EarlyView.Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley +1 more source
Evaluating Icelandic sentiment analysis models trained on translated data
, 2023 In this paper, we experiment with sentiment classification models for Icelandic that leverage machine-translated data for training. We machine translated 50,000 English IMDb reviews, that have been labeled positive and negative, into Icelandic.
Birkir Finnbogi H Arndal 2001- +2 more
core +2 more sources