Google Play Store Sentiment Analysis using Python

Sentiment analysis is the classification of a customer’s reviews or comments as positive, negative, and sometimes neutral also. Most businesses analyze their customers’ feelings about their products or services to find out what their customers want from them. Google play store has millions of apps with their reviews, so it will be a good use case of sentiment analysis to analyze the sentiment of apps available on the google play store. So, in this article, I will walk you through the task of Google Play Store sentiment analysis using Python.

Google Play Store Sentiment Analysis

Google Play Store can be found on all Android smartphones and tablets. This is the official Google app store for the Android operating system. It has millions of apps with their reviews so that we can use such an amount of data for any data science task. Analyzing a customer’s reviews and comments is what we do in the Sentiment Analysis task. Having said that, in the section below, I will walk you through the Google Play Store Sentiment Analysis task using Python. The dataset I am using in this task can be downloaded from here.

Google Play Store Sentiment Analysis using Python

I’ll start this task by reading the dataset. The dataset I am using here is downloaded from Kaggle which was collected from the Google Play Store. So let’s start this task by reading the dataset:

                     App  ... Sentiment_Subjectivity
0  10 Best Foods for You  ...               0.533333
1  10 Best Foods for You  ...               0.288462
2  10 Best Foods for You  ...                    NaN
3  10 Best Foods for You  ...               0.875000
4  10 Best Foods for You  ...               0.300000

Before moving forward, let’s have a look at whether this dataset contains any missing values or not:

print(data.isnull().sum())
App                           0
Translated_Review         26868
Sentiment                 26863
Sentiment_Polarity        26863
Sentiment_Subjectivity    26863
dtype: int64

So it has some null values, I will create a new dataset by dropping the null values:

data = data.dropna()
print(data.isnull().sum())
App                       0
Translated_Review         0
Sentiment                 0
Sentiment_Polarity        0
Sentiment_Subjectivity    0
dtype: int64

Now to analyze the sentiments of the google play store reviews, I will add three new columns in the dataset by understanding the sentiments of each customer review as Positive, Negative, and Neutral:

                     App                                  Translated_Review  ... Negative  Neutral
0  10 Best Foods for You  I like eat delicious food. That's I'm cooking ...  ...      0.0    0.466   
3  10 Best Foods for You         Works great especially going grocery store  ...      0.0    0.549   
4  10 Best Foods for You                                       Best idea us  ...      0.0    0.323
5  10 Best Foods for You                                           Best way  ...      0.0    0.192

So now as a final step let’s have a look at the sentiments of customers about the applications available at the Google play store by using a scatter plot:

Summary

So this is how we can analyze the sentiments of google play store reviews. Sentiment analysis is the classification of a customer’s reviews or comments as positive, negative, and neutral. I hope you liked this article on the task of analyzing the sentiments of the Google play store using Python. Feel free to ask your valuable questions in the comments section below.

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Aman Kharwal

Coder with the ♥️ of a Writer || Data Scientist | Solopreneur | Founder

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