Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158092
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dc.contributor.authorBhayangkara, Andhika Satriyaen_US
dc.date.accessioned2022-05-29T11:42:59Z-
dc.date.available2022-05-29T11:42:59Z-
dc.date.issued2022-
dc.identifier.citationBhayangkara, A. S. (2022). Temporal analysis of consumer preferences through natural language processing. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158092en_US
dc.identifier.urihttps://hdl.handle.net/10356/158092-
dc.description.abstractData availability has increased significantly in many shapes and forms, including online customer reviews. This review data has great potential to be a source of information for manufacturers to understand consumer needs and preferences. Nonetheless, customer reviews are still heavily underutilized by manufacturers due to the unstructured nature of the data. Additionally, it is challenging to quantify customer preferences as they are rarely static and evolve rapidly. This study proposes a framework to track and analyze how customer preferences evolve with respect to time through big data analytics with Natural Language Processing. The framework leverages on word frequency analysis and sentiment analysis to derive product feature importance and performance. The following results will be aggregated in a sentiment-based importance-performance analysis model to understand which product features are most in need of improvement. Based on this knowledge, a product improvement strategy can be derived by also considering the most satisfactory product specifications in the market. A case study was performed on smartphone reviews from amazon.com to demonstrate the framework. The proposed framework can be utilized for companies to understand customer preferences which may facilitate companies' decision-making process. Through clear customer insight metrics, more informed product development-related decisions can be made.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relationB052en_US
dc.subjectEngineering::Industrial engineering::Engineering managementen_US
dc.titleTemporal analysis of consumer preferences through natural language processingen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorChen Songlinen_US
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.description.degreeBachelor of Engineering (Mechanical Engineering)en_US
dc.contributor.supervisoremailSonglin@ntu.edu.sgen_US
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Appears in Collections:MAE Student Reports (FYP/IA/PA/PI)
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