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App Review Mining and Summarization

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Rabeya Sultana, Sujan Sarker

Rabeya Sultana and Sujan Sarker. App Review Mining and Summarization. International Journal of Computer Applications 179(38):45-52, April 2018. BibTeX

	author = {Rabeya Sultana and Sujan Sarker},
	title = {App Review Mining and Summarization},
	journal = {International Journal of Computer Applications},
	issue_date = {April 2018},
	volume = {179},
	number = {38},
	month = {Apr},
	year = {2018},
	issn = {0975-8887},
	pages = {45-52},
	numpages = {8},
	url = {},
	doi = {10.5120/ijca2018916918},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


With the development of the web, online reviews are more important and essential information resource for people. Opinion mining and summarizing aims at extracting features and opinions and classify them as positive or negative. In this work, we develop a review mining and summarization technique and apply it to summarize the reviews of apps from Google Play App Store. Different from traditional text summarization, the features of apps are extracted based on customers opinions, classified them as positive or negative and ranked the apps based on the ranking of each feature. We propose two approaches, SentiWordNet 3.0 based and Naïve Bayes algorithm to classify opinions and find scores. The result of two approaches is quite similar. The experimental results show the effectiveness of the proposed approach in app review mining and summarizing.


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Opinion Mining, Sentiment Analysis, Summarization, App Review Analysis.