Sentiment Analysis With Sarcasm Detection On Politician’s Instagram
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2021 Sarcasm is one of the problem that affect the result of sentiment analysis. According to Maynard and Greenwood (2014), performance of sentiment analysis can be improved when sarcasm also identified. Some research used Naïve Bayes and Random Forest method
Aisyah Muhaddisi +2 more
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HMTL: Heterogeneous Modality Transfer Learning for Audio-Visual Sentiment Analysis
IEEE Access, 2020 Multimodal sentiment analysis is an extended approach to traditional language-based sentiment analysis, which uses other relevant modality data. Multimodal sentiment analysis usually applies visual, textual, and acoustic representations for sentiment ...
Sanghyun Seo, Sanghyuck Na, Juntae Kim
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A global optimization approach to multi-polarity sentiment analysis. [PDF]
PLoS ONE, 2015 Following the rapid development of social media, sentiment analysis has become an important social media mining technique. The performance of automatic sentiment analysis primarily depends on feature selection and sentiment classification.
Xinmiao Li, Jing Li, Yukeng Wu
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Sentiment analysis method of comment text based on word vector with sentiment information
Journal of Hebei University of Science and Technology, 2021 In order to solve the problem of low accuracy of sentiment classification caused by neglecting the sentiment information of words in distributed word representation method,an improved sentiment analysis method incorporating weighted word vectors of ...
Meiyuan LYU +3 more
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Human-Centric Intelligent Systems, 2023 This research paper presents a novel approach for recommending products to customers based on their cared aspects by performing sentiment analysis on customer feedback.
Nimesh Bali Yadav
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Using sentiment analysis in tourism research: A systematic, bibliometric, and integrative review [PDF]
Journal of Tourism, Heritage & Services Marketing, 2021 Purpose: Sentiment analysis is built from the information provided through text (reviews) to help understand the social sentiment toward their brand, product, or service.
Franciele Cristina Manosso +1 more
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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
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DOES GOOGLE TRANSLATE AFFECT LEXICON-BASED SENTIMENT ANALYSIS OF MALAY SOCIAL MEDIA TEXT? [PDF]
Malaysian Journal of Computing, 2022 There are a lot of sentiment resources for English, however, there are limited resources in a resource-poor language like the Malay language. One approach to improving sentiment analysis is to translate the focus-language text to a resource-rich language
Vanessa Enjop +5 more
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Chinese Text Sentiment Analysis Based on Extended Sentiment Dictionary
IEEE Access, 2019 The method of text sentiment analysis based on sentiment dictionary often has the problems that the sentiment dictionary doesn't contain enough sentiment words or omits some field sentiment words.
Guixian Xu +5 more
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Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages [PDF]
, 2018 Sentiment analysis in low-resource languages suffers from a lack of annotated corpora to estimate high-performing models. Machine translation and bilingual word embeddings provide some relief through cross-lingual sentiment approaches.
Barnes, Jeremy +2 more
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