Predicting consumers engagement on Facebook based on what and how companies write

Engaged customers are a very import part of current social media marketing. Public figures and brands have to be very careful about what they post online. That is why the need for accurate strategies for anticipating the impact of a post written for an online audience is critical to any public brand...

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Bibliographic Details
Published in:Journal of intelligent & fuzzy systems 2020-01, Vol.39 (2), p.2365-2377
Main Authors: Rosas-Quezada, Érika S., Ramírez-de-la-Rosa, Gabriela, Villatoro-Tello, Esaú
Format: Article
Language:English
Subjects:
Digital media
Prediction models
Social networks
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Summary:Engaged customers are a very import part of current social media marketing. Public figures and brands have to be very careful about what they post online. That is why the need for accurate strategies for anticipating the impact of a post written for an online audience is critical to any public brand. Therefore, in this paper, we propose a method to predict the impact of a given post by accounting for the content, style, and behavioral attributes as well as metadata information. For validating our method we collected Facebook posts from 10 public pages, we performed experiments with almost 14000 posts and found that the content and the behavioral attributes from posts provide relevant information to our prediction model.
ISSN:1064-1246
1875-8967
DOI:10.3233/JIFS-179897