Title: The influence of text classification on Facebook with AISAS method

Authors: Pornpimon Kachamas; Achara Chandrachai; Sukree Sinthupinyo

Addresses: Chulalongkorn University, Bangkok, 10330, Thailand ' Chulalongkorn University, Bangkok, 10330, Thailand ' Chulalongkorn University, Bangkok, 10330, Thailand

Abstract: Social media marketing has never been closely tied like it is now. Online marketing managers thus need to actively analyse and understand this fact beyond sentiments of the visitors of their webs. The objective is to comprehend emotions, feelings towards their threads and participation. This research aims to study the text classification that is used to analyse Dentsu's AISAS patterns of posts in order to understand clients' thinking. The study applies naïve Bayesian as a component in text mining technique together with adoption of Dentsu's AISAS model as a framework. Naïve Bayesian methodology is also used to classify attention, interest, search, action and share for analysis understanding. We hope that this study will help online marketers in responding and adjusting each online campaign with the proper strategy.

Keywords: machine learning; social media; AISAS; social media analytics; naïve Bayes classification.

DOI: 10.1504/IJBIS.2020.111419

International Journal of Business Information Systems, 2020 Vol.35 No.3, pp.401 - 414

Received: 21 May 2018
Accepted: 25 Nov 2018
Published online: 26 Nov 2020 *

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