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Sökning: onr:"swepub:oai:DiVA.org:bth-26183" > Python Data Odyssey :

Python Data Odyssey : Mining User feedback from Google Play store

Yasin, Affan (författare)
Northwestern Polytechnical University, China
Fatima, Rubia (författare)
Emerson University, Pakistan
Ghazi, Ahmad Nauman, 1983- (författare)
Blekinge Tekniska Högskola,Institutionen för programvaruteknik
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Wei, Ziqi (författare)
Chinese Academy of Sciences, China
visa färre...
 (creator_code:org_t)
Elsevier, 2024
2024
Engelska.
Ingår i: Data in Brief. - : Elsevier. - 2352-3409. ; 54
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • ContextThe Google Play Store is widely recognized as one of the largest platforms for downloading applications, both free and paid1. On a daily basis, millions of users avail themselves of this marketplace, sharing their thoughts through various means such as star ratings, user comments, suggestions, and feedback. These insights, in the form of comments and feedback, constitute a valuable resource for organizations, competitors, and emerging companies seeking to expand their market presence. These comments provide insights into app deficiencies, suggestions for new features, identified issues, and potential enhancements. Unlocking the potential of this repository of suggestions holds significant value.ObjectiveThis study sought to gather and analyze user reviews from the Google Play store for leading game apps. The primary aim was to construct a dataset for subsequent analysis utilizing requirements engineering, machine learning, and competitive assessment.MethodologyThe authors employed a Python-based web scraping method to extract a comprehensive set of over 429,000+ reviews from the Google Play pages of selected apps. The scraped data encompassed reviewer names (removed due to privacy), ratings, and the textual content of the reviews.ResultsThe outcome was a dataset comprising the extracted user reviews, ratings, and associated metadata. A total of 429,000+ reviews were acquired through the scraping process for popular apps like Subway Surfers, Candy Crush Saga, PUBG Mobile, among others. This dataset not only serves as a valuable educational resource for instructors, aiding in the training of students in data analysis, but also offers practitioners the opportunity for in-depth examination and insights (in the past data of top apps).

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

App reviews
Crowd-source data
Data mining
NLP
User reviews

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Yasin, Affan
Fatima, Rubia
Ghazi, Ahmad Nau ...
Wei, Ziqi
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Data in Brief
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Blekinge Tekniska Högskola

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