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Drug Review Dataset (Drugs.com) Data Set
Download: Data Folder, Data Set Description
Abstract: The dataset provides patient reviews on specific drugs along with related conditions and a 10 star patient rating reflecting overall patient satisfaction.
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Data Set Characteristics: |
Multivariate, Text |
Number of Instances: |
215063 |
Area: |
Life |
Attribute Characteristics: |
Integer |
Number of Attributes: |
6 |
Date Donated |
2018-10-04 |
Associated Tasks: |
Classification, Regression, Clustering |
Missing Values? |
N/A |
Number of Web Hits: |
66276 |
Source:
Surya Kallumadi
Kansas State University
Manhattan, Kansas, USA
surya '@' ksu.edu
Felix Gräßer
Institut für Biomedizinische Technik
Technische Universität Dresden
Dresden, Germany
felix.graesser '@' tu-dresden.de
Data Set Information:
The dataset provides patient reviews on specific drugs along with related conditions and a 10 star patient rating reflecting overall patient satisfaction. The data was obtained by crawling online pharmaceutical review sites. The intention was to study
(1) sentiment analysis of drug experience over multiple facets, i.e. sentiments learned on specific aspects such as effectiveness and side effects,
(2) the transferability of models among domains, i.e. conditions, and
(3) the transferability of models among different data sources (see 'Drug Review Dataset (Druglib.com)').
The data is split into a train (75%) a test (25%) partition (see publication) and stored in two .tsv (tab-separated-values) files, respectively.
Important notes:
When using this dataset, you agree that you
1) only use the data for research purposes
2) don't use the data for any commerical purposes
3) don't distribute the data to anyone else
4) cite us
Attribute Information:
1. drugName (categorical): name of drug
2. condition (categorical): name of condition
3. review (text): patient review
4. rating (numerical): 10 star patient rating
5. date (date): date of review entry
6. usefulCount (numerical): number of users who found review useful
Relevant Papers:
Felix Gräßer, Surya Kallumadi, Hagen Malberg, and Sebastian Zaunseder. 2018. Aspect-Based Sentiment Analysis of Drug Reviews Applying Cross-Domain and Cross-Data Learning. In Proceedings of the 2018 International Conference on Digital Health (DH '18). ACM, New York, NY, USA, 121-125. DOI: [Web Link]
Citation Request:
Felix Gräßer, Surya Kallumadi, Hagen Malberg, and Sebastian Zaunseder. 2018. Aspect-Based Sentiment Analysis of Drug Reviews Applying Cross-Domain and Cross-Data Learning. In Proceedings of the 2018 International Conference on Digital Health (DH '18). ACM, New York, NY, USA, 121-125. DOI: [Web Link]
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