CT-SPA: Text sentiment polarity prediction model using semi-automatically expanded sentiment lexicon
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Opinion MiningSentiment AnalysisSingle Particle AnalysisSimilar Papers 제목 키워드 기반
Using Data Mining Techniques for Sentiment Shifter Identification
Sentiment shifters, i.e., words and expressions that can affect text polarity, play an important role in opinion mining. However, the limited ability of current automated opinion mining systems to handle shifters represe…
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When performing Polarity Detection for different words in a sentence, we need to look at the words around to understand the sentiment. Massively pretrained language models like BERT can encode not only just the words in …
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Sentiment analysis is the Natural Language Processing (NLP) task dealing with the detection and classification of sentiments in texts. While some tasks deal with identifying the presence of sentiment in the text (Subject…
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Sarcasm is an advanced linguistic expression often found on various online platforms. Sarcasm detection is challenging in natural language processing tasks that affect sentiment analysis. This article presents the invent…
Sarcasm DetectionSentiment AnalysisBuilding a robust sentiment lexicon with (almost) no resource
Creating sentiment polarity lexicons is labor intensive. Automatically translating them from resourceful languages requires in-domain machine translation systems, which rely on large quantities of bi-texts. In this paper…
General ClassificationMachine TranslationTranslationWord Embeddings