Topic-dependent sentiment analysis of financial blogs [PDF]
, 2009 While most work in sentiment analysis in the financial domain has focused on the use of content from traditional finance news, in this work we concentrate on more subjective sources of information, blogs.
Bermingham, Adam +6 more
core +2 more sources
Text sentiment visual analysis technology and its application in humanities
大数据, 2022 Sentiment analysis is the mining of information sentiment tendency, which is mainly used for public opinion monitoring, commodity review analysis, and information retrieval.With the rapid development of social media, the volume of text data has shown ...
Lingli ZHANG +6 more
doaj
A Survey on Feature Extraction Techniques, Classification Methods and Applications of Sentiment Analysis [PDF]
Brazilian Archives of Biology and Technology, 2023 Rapid developments in the era of IoT technologies, coupled with the espousal of social media tools and applications, have promoted the use of data analytics as a means to gain significant insights from unstructured data. Sentiment analysis is an approach
Yadav Meenakshi Muthukrishnan Seethalakshmi +2 more
doaj +1 more source
Challenges and Issues in Sentiment Analysis: A Comprehensive Survey
IEEE Access, 2023 Sentiment analysis, a specialization of natural language processing (NLP), has witnessed significant progress since its emergence in the late 1990s, owing to the swift advances in deep learning techniques and the abundance of vast digital datasets ...
Nilaa Raghunathan +1 more
doaj +1 more source
Better Document-level Sentiment Analysis from RST Discourse Parsing [PDF]
, 2015 Discourse structure is the hidden link between surface features and document-level properties, such as sentiment polarity. We show that the discourse analyses produced by Rhetorical Structure Theory (RST) parsers can improve document-level sentiment ...
Bhatia, Parminder +2 more
core +1 more source
Improving the performance of lexicon-based review sentiment analysis method by reducing additional introduced sentiment bias. [PDF]
PLoS ONE, 2018 Sentiment analysis is widely studied to extract opinions from user generated content (UGC), and various methods have been proposed in recent literature. However, these methods are likely to introduce sentiment bias, and the classification results tend to
Hongyu Han +4 more
doaj +1 more source
Sentiment Lexicon Adaptation with Context and Semantics for the Social Web [PDF]
, 2017 Sentiment analysis over social streams offers governments and organisations a fast and effective way to monitor the publics' feelings towards policies, brands, business, etc.
Bollen +7 more
core +1 more source
A Barrage Sentiment Analysis Scheme Based on Expression and Tone
IEEE Access, 2019 Most of existing methods do not consider the influence of expression and tone on barrage sentiment analysis. This decreases the effect and accuracy of barrage sentiment analysis.
Zongmin Cui +5 more
doaj +1 more source
Combining Sentiment Lexica with a Multi-View Variational Autoencoder [PDF]
, 2019 When assigning quantitative labels to a dataset, different methodologies may rely on different scales. In particular, when assigning polarities to words in a sentiment lexicon, annotators may use binary, categorical, or continuous labels.
Augenstein, Isabelle +4 more
core +2 more sources
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