Results 41 to 50 of about 265,995 (181)
Engineering Proceedings, 2023 Students’ after-class self-evaluated comments are useful for understanding students’ learning and reflecting teacher’s teaching. Researchers and engineers have attempted to apply educational data mining techniques, such as text analysis, sentiment ...
Chih-Yueh Chou, Tzu-Yi Chuang
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Automatic domain ontology extraction for context-sensitive opinion mining [PDF]
, 2009 Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping.
Lai, Chapmann C.L. +3 more
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Sentiment Classification across Domains [PDF]
, 2009 In this paper we consider the problem of building models that have high sentiment classification accuracy without the aid of a labeled dataset from the target domain. For that purpose, we present and evaluate a novel method based on level of abstraction of nouns. By comparing high-level features (e.g.
Dinko Lambov, Gaël Dias, Veska Noncheva
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IEEE Access, 2020 With the rapid growth of user-generated content, unsupervised methods that do not require label training data have gradually become a research focus in the field of sentiment classification and natural language processing.
Bingkun Wang +3 more
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On stopwords, filtering and data sparsity for sentiment analysis of Twitter [PDF]
, 2014 Sentiment classification over Twitter is usually affected by the noisy nature (abbreviations, irregular forms) of tweets data. A popular procedure to reduce the noise of textual data is to remove stopwords by using pre-compiled stopword lists or more ...
Alani, Harith +3 more
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Sentiment Classification Using Negative and Intensive Sentiment Supplement Information [PDF]
Data Science and Engineering, 2019 Abstract Traditional methods of annotating the sentiment of an unlabeled document are based on sentiment lexicons or machine learning algorithms, which have shown low computational cost or competitive performance. However, these methods ignore the semantic composition problem displaying in several ways such as negative reversing and intensification. In
Xingming Chen +5 more
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Multi-grained Sentiment Analysis of Comments Based on Text Generation [PDF]
Jisuanji kexueWith the rise of social media and online review platforms,automated sentiment analysis has become a key tool for understanding public emotions,consumer preferences,and market trends.Traditional sentiment analysis methods often use classification models ...
ZHANG Jiawei, WANG Zhongqing, CHEN Jiali
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Attentional Encoder Network for Targeted Sentiment Classification
, 2019 Targeted sentiment classification aims at determining the sentimental tendency towards specific targets. Most of the previous approaches model context and target words with RNN and attention.
Jiang, Tao +4 more
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Applied SciencesDomain information plays a crucial role in sentiment analysis. Neural networks that treat domain information as attention can further extract domain-related sentiment features from a shared feature pool, significantly enhancing the accuracy of sentiment ...
Chunyi Yue +4 more
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Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015, 2015 Sentiment classification has become a ubiquitous enabling technology in the Twittersphere, since classifying tweets according to the sentiment they convey towards a given entity (be it a product, a person, a political party, or a policy) has many applications in political science, social science, market research, and many others.
Gao W, Sebastiani F
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