Center for Machine Learning and Intelligent Systems
About  Citation Policy  Donate a Data Set  Contact


Repository Web            Google
View ALL Data Sets

Drug Review Dataset (Druglib.com) Data Set
Download: Data Folder, Data Set Description

Abstract: The dataset provides patient reviews on specific drugs along with related conditions. Reviews and ratings are grouped into reports on the three aspects benefits, side effects and overall comment.

Data Set Characteristics:  

Multivariate, Text

Number of Instances:

4143

Area:

N/A

Attribute Characteristics:

Integer

Number of Attributes:

8

Date Donated

2018-10-02

Associated Tasks:

Classification, Regression, Clustering

Missing Values?

N/A

Number of Web Hits:

6347


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. Furthermore, reviews are grouped into reports on the three aspects benefits, side effects and overall comment. Additionally, ratings are available concerning overall satisfaction as well as a 5 step side effect rating and a 5 step effectiveness rating. 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 (Drugs.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. urlDrugName (categorical): name of drug
2. condition (categorical): name of condition
3. benefitsReview (text): patient on benefits
4. sideEffectsReview (text): patient on side effects
5. commentsReview (text): overall patient comment
6. rating (numerical): 10 star patient rating
7. sideEffects (categorical): 5 step side effect rating
8. effectiveness (categorical): 5 step effectiveness rating


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]


Supported By:

 In Collaboration With:

About  ||  Citation Policy  ||  Donation Policy  ||  Contact  ||  CML