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Deriving Business Value From Online Data Sources Using Natural Language Processing Techniques

Deriving Business Value From Online Data Sources Using Natural Language Processing Techniques

Stephen Camilleri
Copyright: © 2021 |Pages: 23
ISBN13: 9781799842408|ISBN10: 1799842401|ISBN13 Softcover: 9781799851349|EISBN13: 9781799842415
DOI: 10.4018/978-1-7998-4240-8.ch002
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MLA

Camilleri, Stephen. "Deriving Business Value From Online Data Sources Using Natural Language Processing Techniques." Natural Language Processing for Global and Local Business, edited by Fatih Pinarbasi and M. Nurdan Taskiran, IGI Global, 2021, pp. 17-39. https://doi.org/10.4018/978-1-7998-4240-8.ch002

APA

Camilleri, S. (2021). Deriving Business Value From Online Data Sources Using Natural Language Processing Techniques. In F. Pinarbasi & M. Taskiran (Eds.), Natural Language Processing for Global and Local Business (pp. 17-39). IGI Global. https://doi.org/10.4018/978-1-7998-4240-8.ch002

Chicago

Camilleri, Stephen. "Deriving Business Value From Online Data Sources Using Natural Language Processing Techniques." In Natural Language Processing for Global and Local Business, edited by Fatih Pinarbasi and M. Nurdan Taskiran, 17-39. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-4240-8.ch002

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Abstract

The wealth of information produced over the internet empowers businesses to become data-driven organizations, increasing their ability to predict consumer behavior, take more informed strategic decisions, and remain competitive on the market. However, past research did not identify which online data sources companies should choose to achieve such an objective. This chapter aims to analyse how online news articles, social media messages, and user reviews can be exploited by businesses using natural language processing (NLP) techniques to build business intelligence. NLP techniques assist computers to understand and derive a valuable meaning from human (natural) languages. Following a brief introduction to NLP and a description of how these three text streams differ from each other, the chapter discusses six main factors that can assist businesses in choosing one data source from another. The chapter concludes with future directions towards improving business applications involving NLP techniques.

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