Text Pre-Processing For The Frequently Mentioned Criteria From Online Community Homebuyer Dataset

Abstract

<p>Due to the competitive Malaysian residential market with a large number of residential projects that offered almost similar features lead to difficulties of residential purchasing among homebuyers. These days, homebuyers are very selective, careful, and required more time in deciding due to the high numbers of abundant, and problem residential projects in Malaysia. As a result, a high number of unsold residential projects were reported. Therefore, understanding homebuyer criteria in a residential purchase is crucially important towards successful Malasia residential projects in the long term. This paper identifies and prioritizing homebuyers criteria in mainland Penang, Malaysia from user-generated data in online property forums. 6000 data was extracted through RapidMiner software. Once data were processes, statistic analysis is used to determined and prioritize the homebuyer's criteria. The classification of criteria is made by the real estate experts. The result of the study provides fresh insight into homebuyers' criteria. The findings should offer developers, government, potential homebuyers, and real estate agents a better understanding of homebuyers criteria in Penang, Malaysia. </p>

Hybrid Approach for User Reviews' Text Analysis and Visualization: A Case Study of Amazon User Reviews

“…In this phase, data will be clean and formatted through several processes such as removing unnecessary data punctuation and processing other data, such as reducing the vocabulary size of the textual data, and lemmatization which converts a word to its root form. [22]…”