Learn about sentiment analysis with supervised learning in R with data from the Economic News Article Tone dataset (2016) / Feng Shi and Odum Institute.
This dataset is designed for teaching sentiment analysis of text data with supervised learning. The dataset is a subset of the 2016 Economic News Article Tone dataset, and the example investigates the change over time of sentiment on the U.S. Economy from the news articles. The dataset file is accom...
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| Format: | Electronic eBook |
| Language: | English |
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London :
SAGE Publications, Ltd.,
2019.
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| Subjects: |
MARC
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| 100 | 1 | |a Shi, Feng, |d active 2019, |e author. | |
| 245 | 1 | 0 | |a Learn about sentiment analysis with supervised learning in R with data from the Economic News Article Tone dataset (2016) / |c Feng Shi and Odum Institute. |
| 264 | 1 | |a London : |b SAGE Publications, Ltd., |c 2019. | |
| 300 | |a 1 online resource : |b illustrations | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 520 | 8 | |a This dataset is designed for teaching sentiment analysis of text data with supervised learning. The dataset is a subset of the 2016 Economic News Article Tone dataset, and the example investigates the change over time of sentiment on the U.S. Economy from the news articles. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for R. | |
| 588 | |a Description based on XML content. | ||
| 650 | 0 | |a Supervised learning (Machine learning) | |
| 650 | 0 | |a Emotive (Linguistics) | |
| 651 | 0 | |a United States |x Economic conditions. | |
| 650 | 7 | |a Economic history |2 fast | |
| 650 | 7 | |a Emotive (Linguistics) |2 fast | |
| 650 | 7 | |a Supervised learning (Machine learning) |2 fast | |
| 651 | 7 | |a United States |2 fast | |
| 710 | 1 | |a Odum Institute, |e author. | |
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