A Systematic Literature Review: Opinion Mining Studies From Mobile App Store User Reviews

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In today’s digital era, mobile applications have become an integral part of our lives. From ordering food to booking cabs, we rely on mobile apps for almost everything. As a result, mobile app stores like Google Play Store and Apple App Store have millions of apps catering to various needs. But with so many options available, it becomes difficult for users to choose the right app. Therefore, users often rely on the reviews and ratings of other users before downloading an app.

With the increasing importance of user reviews, researchers have started exploring the field of sentiment analysis or opinion mining. Sentiment analysis is a way of extracting the emotions expressed in a piece of text. Opinion mining is the application of sentiment analysis to online reviews to determine the overall opinion of users towards a product or service.

What is a systematic literature review?

A systematic literature review is a method of identifying, evaluating, and interpreting all available research relevant to a particular research question. It involves a comprehensive search of multiple databases and other sources to identify relevant studies that meet specified inclusion criteria. The studies are then assessed for quality, and the results are synthesized and summarized into a single report.

In the context of opinion mining studies from mobile app store user reviews, a systematic literature review can help in identifying the trends and patterns in user opinions across different apps and categories. It can also help in identifying the gaps in existing research and suggest future directions for research.

What are the key findings of the systematic literature review?

A recent systematic literature review on opinion mining studies from mobile app store user reviews identified several key findings:

  • The majority of studies focus on sentiment analysis of user reviews, with only a few studies exploring other aspects like feature extraction and opinion summarization.
  • The most commonly used machine learning algorithms for sentiment analysis are Support Vector Machines (SVM), Naive Bayes, and Maximum Entropy.
  • The accuracy of sentiment analysis varies across studies, with some studies reporting over 90% accuracy and others reporting less than 70% accuracy.
  • The majority of studies focus on English-language reviews, with only a few studies exploring other languages.
  • The most commonly analyzed app categories are social networking, gaming, and e-commerce.
  • Positive reviews are more common than negative reviews, with the ratio of positive to negative reviews ranging from 2:1 to 10:1.

What are the implications of the key findings?

The key findings of the systematic literature review have several implications for researchers, app developers, and users:

  • Researchers can use the findings to identify the gaps in existing research and suggest future directions for research. For example, there is a need for more research on non-English-language reviews and on other aspects of opinion mining like feature extraction and opinion summarization.
  • App developers can use the findings to improve their apps and increase user satisfaction. For example, they can analyze the common complaints and suggestions in negative reviews and make necessary changes to their apps.
  • Users can use the findings to make informed decisions while downloading apps. For example, they can look at the ratio of positive to negative reviews to get an idea of the overall opinion of users towards an app.

What are the limitations of the systematic literature review?

Like any other research method, a systematic literature review has its limitations:

  • The quality of the review depends on the quality of the included studies. If the included studies are of poor quality, the review findings may not be reliable.
  • The review may miss some relevant studies if they are not indexed in the searched databases or are not written in English.
  • The review can only provide a summary of the findings of the included studies and cannot provide detailed insights into individual studies.

Conclusion

A systematic literature review on opinion mining studies from mobile app store user reviews has identified several key findings that have important implications for researchers, app developers, and users. The findings suggest the need for more research on non-English-language reviews and on other aspects of opinion mining like feature extraction and opinion summarization. App developers can use the findings to improve their apps and increase user satisfaction, while users can use the findings to make informed decisions while downloading apps.

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