Results 141 to 150 of about 265,995 (181)

Word sense disambiguation based sentiment lexicons for sentiment classification

Knowledge-Based Systems, 2016
Sentiment analysis has attracted much attention from both researchers and practitioners as word-of-mouth (WOM) has a significant influence on consumer behavior. One core task of sentiment analysis is the discovery of sentimental words. This can be done efficiently when an accurate and large-scale sentiment lexicon is used.
Chihli Hung, Shiuan-Jeng Chen
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Unsupervised Sentiment Classification

2016
This chapter describes the design and implementation of the unsupervised sentiment classification procedure. The classification procedure consisted of two core components: a bespoke sentiment analysis system developed by the author and the SenticNet sentiment lexicon. The sentiment lexicon acted as the source of sentiment information, and the sentiment
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Chinese Sentence-Level Sentiment Classification Based on Sentiment Morphemes

2010 International Conference on Asian Language Processing, 2010
In this paper, we take morphemes as the basic tokens and present a fine-to-coarse strategy for Chinese sentence-level sentiment classification. This study involves three parts. First, we employ morphological productivity to extract sentiment morphemes from a sentiment dictionary and to calculate their polarity intensity at the same time. Then, we apply
Xin Wang, Guohong Fu
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Unsupervised Sentiment Classification: A Hybrid Sentiment-Topic Model Approach

2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI), 2017
With the large volume of text available online it is becoming impractical to use supervised machine learning methods that require a sizeable training set of labelled data. In this paper we introduced a new sentiment-topic model called the hybrid sentiment-topic model (HST). The HST model is a completely unsupervised sentiment classification method that
Stuart J. Blair, Yaxin Bi, Maurice D. Mulvenna   +2 more
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Sentiment Classification Using Neural Networks with Sentiment Centroids

2018
Neural networks (NN) have demonstrated powerful ability to extract text features automatically for sentiment classification in recent years. Although semantic and syntactic features are well studied, global category information has been mostly ignored within the NN based framework. Samples with the same sentiment category should have similar vectors in
Maoquan Wang, Shiyun Chen, Liang He
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Sentiment Classification of Movie Reviews Using Korean Sentiment Dictionary

Advanced Science and Technology Letters, 2014
While there exists a large volume of research on sentiment classification of English customer reviews using English sentiment dictionaries, there are few researches on classifying sentiment of Korean customer reviews using Korean sentiment dictionaries.
Heeryon Cho, Sang-Hyun Choi
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Sentiment Commonsense Induced Sequential Neural Networks for Sentiment Classification

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019
Although neural networks achieve promising performance in sentence level sentiment classification, most of them are not aware of sentiment commonsense, such as sentiment polarity tags (Positive or Negative) for words, which explicitly determine the sentiment of the sentence in most cases. In this paper, we propose an auxiliary tagging task to integrate
Chen Shiyun, Lin Xin, Xiao Yanghua, He Liang   +3 more
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MODALITY-DEPENDENT SENTIMENTS EXPLORING FOR MULTI-MODAL SENTIMENT CLASSIFICATION

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Recognizing human feelings from image and text is a core challenge of multi-modal data analysis, often applied in personalized advertising. Previous works aim at exploring the shared features, which are the matched contents between images and texts. However, the modality-dependent sentiment information (private features) in each modality is usually ...
Jingzhe Li, Chengji Wang, Zhiming Luo, Yuxian Wu, Xingpeng Jiang   +4 more
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Aspect sentiment learning for Aspect-Level Sentiment Classification

Neural Networks, 2023
Zhongquan Jian, Jiajian Li, Meihong Wang, Junfeng Yao, Qingqiang Wu   +4 more
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Domain Adaptation in Sentiment Classification

2010 Ninth International Conference on Machine Learning and Applications, 2010
In this paper we analyse one of the most challenging problems in natural language processing: domain adaptation in sentiment classification. In particular, we look for generic features by making use of linguistic patterns as an alternative to the commonly feature vectors based on ngrams.
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