مقایسهٔ روشها
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| تحلیل احساسات× | تشخیص ذهنیت× | |
|---|---|---|
| حوزه | متنکاوی | متنکاوی |
| خانواده | Process / pipeline | Process / pipeline |
| سال پیدایش | — | — |
| پدیدآور | — | — |
| نوع | NLP text-classification task | NLP text-classification task |
| منبع بنیادین≠ | Pang, B. & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135. DOI ↗ | Wiebe, J., Wilson, T. & Cardie, C. (2005). Annotating Expressions of Opinions and Emotions in Language. Language Resources and Evaluation, 39(2-3), 165-210. DOI ↗ |
| نامهای دیگر | opinion mining, polarity detection, duygu analizi | subjective vs objective classification, subjectivity classification, Öznellik Tespiti (Subjectivity Detection) |
| مرتبط | 3 | 3 |
| خلاصه≠ | Sentiment analysis, also called opinion mining, is a natural-language-processing task that detects the emotional tone of text — typically classifying it as positive, negative, or neutral. It turns unstructured opinion text into structured, quantifiable polarity signals using one of three families of approaches: sentiment lexicons, trained machine-learning classifiers, or pretrained transformer models. | Subjectivity detection is a natural-language-processing task that classifies whether a sentence or document conveys objective (neutral information) or subjective (personal opinion, emotion) content. Grounded in the opinion-annotation work of Wiebe and colleagues (2005) and Pang and Lee (2004), it is most often used as a preliminary step before sentiment analysis. |
| ScholarGateمجموعهداده ↗ |
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