Proposing A Method For Analyzing User Comments On Twitter Social Media Platform For Business Model Innovation

Document Type : Original Article

Authors
Monireh Hosseini 1
Tina Akhlaghi Meskin 2
1 Associate Prof., Department of Information Technology Engineering, Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
2 MSc. Student, Department of Information Technology Engineering ,Faculty of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
10.22034/aimj.2023.197450
Abstract
In our current era, with the advancements in the use of Internet, a large amount of textual data is being rapidly created. Words are an inseparable part of online transactions in E-commerce. Online comments, news, marketing and other types of communication along with the digitalization of data creates a huge amount of textual data that businesses would like to use. Textual data gets created by people, organizations and communities. In the past, researchers and businesses employed manual methods to gain insights about their customers, which required significant human effort, financial resources, and processing time. Due to human intervention in analysis, these methods were susceptible to analyst and respondent biases. By using text mining we can analyze the necessary information for companies in an automatic and cost-effective way in real time, enabling the use of the results for business model innovation. This research examines customer tweets directed at the Apple company and the company's responses using sentiment analysis methods and Latent Dirichlet Allocation. Furthermore, a new method has been suggested to combine the results of these two methods in order to gain deeper insights into the data and use the results to give recommendations for enhancing Apple company’s business model.

Keywords

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  • Receive Date 31 August 2023
  • Revise Date 02 March 2024
  • Accept Date 19 May 2024