Analyzing Sentiment and Topic Modelling of iPhone Xs Post Launch Event through Twitter Data
Muhammad Ishla Fakhri (a*), Herry Irawan, S.T., M.M., M.T. (a)

a) Faculty of Economics and Business, Telkom University, Jl. Telekomunikasi Terusan Buah Batu 1, Bandung 40257, Indonesia *muhammadishlafakhri[at]student.telkomuniversity.ac.id

Abstract

In this globalization era, people can interact and gain information globally with ease. Therefore, the consumer perception of the product can quickly be gathered after the product launching, i.e. through social media. Furthermore, the company can understand the consumers perceptions and sentiments after a new product is launched, and quickly response the problems that arises proactively. The purpose of this research is to crawl the iPhone X series customer perception after its launched through social media Twitter. Data collection began at October 1st until October 29th 2018, with a total of 264,955 tweets data and analyzed using topic modelling and sentiment analysis. The result is a pattern of dynamic sentiment per day and dynamic topics per week related to those products. With this result, the company is expected to gain valuable information to solve the problems and took as preventive strategy for next launching to avoid making the same mistake.

Keywords: Sentiment Analysis; Topic Modeling; Latent Dirichlet Allocation; Big Data; Content Analysis.

Topic: Industry Engineering