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App Review Mining and Summarization
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 179 - Number 38 |
| Year of Publication: 2018 |
| Authors: Rabeya Sultana, Sujan Sarker |
10.5120/ijca2018916918
|
Rabeya Sultana, Sujan Sarker . App Review Mining and Summarization. International Journal of Computer Applications. 179, 38 ( Apr 2018), 45-52. DOI=10.5120/ijca2018916918
Abstract
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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