Data
Google-Play-Store-Reviews

Google-Play-Store-Reviews

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Onur Yildirim
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Google Play Store Google Play, formerly Android Market, is a digital distribution service operated and developed by Google. It serves as the official app store for certified devices running on the Android operating system, allowing users to browse and download applications developed with the Android software development kit (SDK) and published through Google. It has crossed over 82 billion app downloads with over 3.5 million published apps making it the largest app store in the world. Content The data contains over 12000 reviews of different app store applications by real users. The data also contains the rating that was given by them so it can be classified into positive or negative reviews. This is a real good place to perform sentiment analysis tasks. Some of the apps whose data has been collected can be seen below. Acknowledgements I have used the Google Play Store Scrapper Library for this task which made the scrapping really easy. You can also check out the data collection process here. Motivation This is a really good place to start learning about sentiment analysis. These reviews and ratings can provide beginners with annotated real-world data. I have uploaded a BERT sentiment analysis model which has been trained on Colab but the code can be reused to run on Kaggle as well. You can also mine some other insights regarding the best and the worst reviews.

12 features

reviewIdstring12495 unique values
0 missing
userNamestring11882 unique values
19 missing
userImagestring12037 unique values
0 missing
contentstring11738 unique values
43 missing
scorenumeric5 unique values
0 missing
thumbsUpCountnumeric139 unique values
0 missing
reviewCreatedVersionstring497 unique values
2162 missing
atstring12491 unique values
0 missing
replyContentstring4770 unique values
6701 missing
repliedAtstring5818 unique values
6677 missing
sortOrderstring1 unique values
0 missing
appIdstring15 unique values
0 missing

19 properties

12495
Number of instances (rows) of the dataset.
12
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
15602
Number of missing values in the dataset.
7893
Number of instances with at least one value missing.
2
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
16.67
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
63.17
Percentage of instances having missing values.
Average class difference between consecutive instances.
10.41
Percentage of missing values.

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