Datasets:

Modalities:
Text
Formats:
parquet
Languages:
English
Libraries:
Datasets
pandas
License:
Sharathhebbar24 commited on
Commit
098bd76
1 Parent(s): 0ca2627

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +11 -11
README.md CHANGED
@@ -74,16 +74,16 @@ dataset_info:
74
 
75
  ### Dataset Summary
76
 
77
- It is a large dataset of Android applications belonging to 23 differentapps categories, which provides an overview of the types of feedback users report on the apps and documents the evolution of the related code metrics. The dataset contains about 395 applications of the F-Droid repository, including around 600 versions, 280,000 user reviews (extracted with specific text mining approaches)
78
 
79
  ### Supported Tasks and Leaderboards
80
 
81
- The dataset we provide comprises 395 different apps from F-Droid repository, including code quality indicators of 629 versions of these
82
  apps. It also encloses app reviews related to each of these versions, which have been automatically categorized classifying types of user feedback from a software maintenance and evolution perspective.
83
 
84
  ### Languages
85
 
86
- The dataset is a monolingual dataset which has the messages English.
87
 
88
  ## Dataset Structure
89
 
@@ -98,14 +98,14 @@ The dataset consists of a message in English.
98
 
99
  ### Data Fields
100
 
101
- * package_name : Name of the Software Application Package
102
- * review : Message of the user
103
- * date : date when the user posted the review
104
- * star : rating provied by the user for the application
105
 
106
  ### Data Splits
107
 
108
- There is training data, with a total of : 288065
109
 
110
  ## Dataset Creation
111
 
@@ -141,11 +141,11 @@ There is training data, with a total of : 288065
141
 
142
  ### Social Impact of Dataset
143
 
144
- With the help of this dataset one can try to understand more about software applications and what are the views and opinions of the users about them. This helps to understand more about which type of software applications are prefeered by the users and how do these applications facilitate the user to help them solve their problems and issues.
145
 
146
  ### Discussion of Biases
147
 
148
- The reviews are only for applications which are in the open-source software applications, the other sectors have not been considered here
149
 
150
  ### Other Known Limitations
151
 
@@ -164,7 +164,7 @@ Giovanni Grano - (University of Zurich), Sebastiano Panichella - (University of
164
  ### Citation Information
165
 
166
  @InProceedings{Zurich Open Repository and
167
- Archive:dataset,
168
  title = {Software Applications User Reviews},
169
  authors={Grano, Giovanni; Di Sorbo, Andrea; Mercaldo, Francesco; Visaggio, Corrado A; Canfora, Gerardo;
170
  Panichella, Sebastiano},
 
74
 
75
  ### Dataset Summary
76
 
77
+ It is a large dataset of Android applications belonging to 23 different app categories, which provides an overview of the types of feedback users report on the apps and documents the evolution of the related code metrics. The dataset contains about 395 applications of the F-Droid repository, including around 600 versions, 280,000 user reviews (extracted with specific text mining approaches)
78
 
79
  ### Supported Tasks and Leaderboards
80
 
81
+ The dataset we provide comprises 395 different apps from the F-Droid repository, including code quality indicators of 629 versions of these
82
  apps. It also encloses app reviews related to each of these versions, which have been automatically categorized classifying types of user feedback from a software maintenance and evolution perspective.
83
 
84
  ### Languages
85
 
86
+ The dataset is a monolingual dataset that has the messages in English.
87
 
88
  ## Dataset Structure
89
 
 
98
 
99
  ### Data Fields
100
 
101
+ * package_name: Name of the Software Application Package
102
+ * Review : Message of the user
103
+ * date: the date when the user posted the review
104
+ * star: rating provided by the user for the application
105
 
106
  ### Data Splits
107
 
108
+ There is training data, with a total of 288065
109
 
110
  ## Dataset Creation
111
 
 
141
 
142
  ### Social Impact of Dataset
143
 
144
+ With the help of this dataset, one can try to understand more about software applications and what are the views and opinions of the users about them. This helps to understand more about which type of software applications are prefeered by the users and how do these applications facilitate the user to help them solve their problems and issues.
145
 
146
  ### Discussion of Biases
147
 
148
+ The reviews are only for applications that are in open-source software applications, the other sectors have not been considered here
149
 
150
  ### Other Known Limitations
151
 
 
164
  ### Citation Information
165
 
166
  @InProceedings{Zurich Open Repository and
167
+ Archive: dataset,
168
  title = {Software Applications User Reviews},
169
  authors={Grano, Giovanni; Di Sorbo, Andrea; Mercaldo, Francesco; Visaggio, Corrado A; Canfora, Gerardo;
170
  Panichella, Sebastiano},