Webis Tripad Sentiment Corpus 2013 (Webis-Tripad-13-Sentiment)
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zipUpdated Aug 29, 2022+ more versions
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EmailClick to copy linkLink copiedCiteHenning Wachsmuth; Henning Wachsmuth; Martin Trenkmann; Tsvetomira Palakarska; Joachim Köhring; Benno Stein; Benno Stein; Dora Spensberger; Martin Trenkmann; Tsvetomira Palakarska; Joachim Köhring; Dora Spensberger (2022). Webis Tripad Sentiment Corpus 2013 (Webis-Tripad-13-Sentiment) [Dataset]. http://doi.org/10.5281/zenodo.3266053zipAvailable download formatsUnique identifierhttps://doi.org/10.5281/zenodo.3266053Dataset updatedAug 29, 2022AuthorsHenning Wachsmuth; Henning Wachsmuth; Martin Trenkmann; Tsvetomira Palakarska; Joachim Köhring; Benno Stein; Benno Stein; Dora Spensberger; Martin Trenkmann; Tsvetomira Palakarska; Joachim Köhring; Dora SpensbergerLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionThe Webis Tripad 2013 Sentiment Corpus is a English text corpus of 2100 hotel reviews for the development and evaluation of approaches to sentiment flow analysis. Each document in this corpus is assigned an overall rating score, some metadata, and two kinds of annotations. First, each statement of a review's text has been classified with respect to its sentiment polarity (positive, negative, objective) by Amazon Mechanical Turk (AMT) workers. Second, hotel aspects mentioned in the texts were tagged by in-house domain experts.
To give an example, the sentence "The service was perfect and the rooms were clean." consists of two statements "The service was perfect" and "the rooms were clean", both with positive sentiment classification. The aspect in the first statement is "service" and "rooms" in the second, respectively.
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FacebookTwitterEmailAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Webis Tripad 2013 Sentiment Corpus is a English text corpus of 2100 hotel reviews for the development and evaluation of approaches to sentiment flow analysis. Each document in this corpus is assigned an overall rating score, some metadata, and two kinds of annotations. First, each statement of a review's text has been classified with respect to its sentiment polarity (positive, negative, objective) by Amazon Mechanical Turk (AMT) workers. Second, hotel aspects mentioned in the texts were tagged by in-house domain experts.
To give an example, the sentence "The service was perfect and the rooms were clean." consists of two statements "The service was perfect" and "the rooms were clean", both with positive sentiment classification. The aspect in the first statement is "service" and "rooms" in the second, respectively.