Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Regrese textu× | Analýza sentimentu× | |
|---|---|---|
| Obor | Dolování textu | Dolování textu |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku | — | — |
| Tvůrce | — | — |
| Typ≠ | Supervised regression on text features | NLP text-classification task |
| Původní zdroj≠ | Gentzkow, M., Kelly, B. & Taddy, M. (2019). Text as Data. Journal of Economic Literature, 57(3), 535-574. DOI ↗ | Pang, B. & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135. DOI ↗ |
| Další názvy | text-as-data regression, predicting numeric outcomes from text, Metin Tabanlı Regresyon | opinion mining, polarity detection, duygu analizi |
| Příbuzné≠ | 4 | 3 |
| Shrnutí≠ | Text-based regression predicts a continuous target variable using features extracted from text — TF-IDF scores, embeddings, or n-grams — as the independent variables. Building on the text-as-data programme consolidated by Gentzkow, Kelly and Taddy (2019), it lets a numeric outcome such as a price, a rating, or a sentiment score be estimated directly from documents, and is widely used in social-science, economics, and finance applications. | 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. |
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