Results 51 to 60 of about 633,534 (237)
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
Sentiment analysis: Bayesian Ensemble Learning
Decision Support Systems, 2014 AbstractThe huge amount of textual data on the Web has grown in the last few years rapidly creating unique contents of massive dimension. In a decision making context, one of the most relevant tasks is polarity classification of a text source, which is usually performed through supervised learning methods.
FERSINI, ELISABETTA +2 more
openaire +4 more sources
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
Molecular Oncology, EarlyView.PARP inhibitors are used to treat a small subset of prostate cancer patients. These studies reveal that PARP1 activity and expression are different between European American and African American prostate cancer tissue samples. Additionally, different PARP inhibitors cause unique and overlapping transcriptional changes, notably, p53 pathway upregulation.
Moriah L. Cunningham +21 more
wiley +1 more source
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
Analyzing Disproportionate Reaction via Comparative Multilingual Targeted Sentiment in Twitter [PDF]
, 2017 Global events such as terrorist attacks are commented upon in social media, such as Twitter, in different languages and from different parts of the world.
Agarwal A. +6 more
core +1 more source
Usefulness of Sentiment Analysis
, 2012 What can text sentiment analysis technology be used for, and does a more usage-informed view on sentiment analysis pose new requirements on technology development?
Karlgren, Jussi +4 more
openaire +4 more sources
Sentiment Analysis Is Not Solved! Assessing and Probing Sentiment Classification [PDF]
Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019 Accepted to BlackBoxNLP Workshop at ACL ...
Barnes, Jeremy Claude +2 more
openaire +4 more sources
Bridging the gap: Multi‐stakeholder perspectives of molecular diagnostics in oncology
Molecular Oncology, EarlyView.Although molecular diagnostics is transforming cancer care, implementing novel technologies remains challenging. This study identifies unmet needs and technology requirements through a two‐step stakeholder involvement. Liquid biopsies for monitoring applications and predictive biomarker testing emerge as key unmet needs. Technology requirements vary by
Jorine Arnouts +8 more
wiley +1 more source
Evaluation datasets for Twitter sentiment analysis: a survey and a new dataset, the STS-Gold [PDF]
, 2013 Sentiment analysis over Twitter offers organisations and individuals a fast and effective way to monitor the publics' feelings towards them and their competitors.
Alani, Harith +3 more
core +1 more source