Feature selection using binary particle swarm optimization algorithm to predict repurchase intention from customer reviews
Keywords:Binary Particle Swarm Optimization, Feature selection, online customer reviews, repurchase intention
Indonesia has the largest digital economy in Southeast Asia and has a promising market for e-commerce companies to compete and dominate the online market share. This also gave rise to an increment in the number of customer reviews of a product or service provided. Online customer reviews can be utilized to analyze repurchase intention of e-commerce customers. However, a large number of features that appears in customer reviews increased the repurchase intention predictive model complexity. A process to choose a subset of features and reduces the number of features in data is called feature selection. This paper proposed a method on feature selection to pre-process the predictive model by reducing features that appears in the model using Binary Particle Swarm Optimization combined with Sentiment Orientation-Pointwise Mutual Information to reduce the complexity. The results shows that the proposed method reduces and selects the best features to construct a predictive model of repurchase intention from online customer reviews on two datasets that are written both in Indonesian and English. Compared to the baseline model before performing feature selection, the accuracy of the predictive models evaluated using k-Nearest Neighbors on both datasets are increased 5.4% and 8.5%, respectively.
LicenseCopyright in a work is a bundle of rights. IJoSI's, copyright covers what may be done with the work in terms of making copies, making derivative works, abstracting parts of it for citation or quotation elsewhere and so on. IJoSI requires authors to sign over rights when their article is ready for publication so that the publisher from then on owns the work. Until that point, all rights belong to the creator(s) of the work. The format of IJoSI copy right form can be found at the IJoSI web site.
The issues of International Journal of Systematic Innovation (IJoSI) are published in electronic format and in print. Our website, journal papers, and manuscripts etc. are stored on one server. Readers can have free online access to our journal papers. Authors transfer copyright to the publisher as part of a journal publishing agreement, but have the right to:
1. Share their article for personal use, internal institutional use and scholarly sharing purposes, with a DOI link to the version of record on our server.
2. Retain patent, trademark and other intellectual property rights (including research data).
3. Proper attribution and credit for the published work.