Deep LSTM for Generating Brand Personalities Using Social Media: A Case Study from Higher Education Institutions

Abstract

: This paper introduces a novel technique to generate brand personalities for organizations from social media text data using a deep bi - directional Long Short - Term Memory (BiLSTM) neural network model in combination with an accepted brand personality scale model. Brand Personality has evolved into an indispensable element in modern business organizations. Currently brand personality of an organization is generated using traditional techniques such as stakeholder interviews, questionnaires, which are time and resource intensive and limited in efficacy. However, the rise of the internet and social media have provided a platform for stakeholders to frequently and freely express their opinions and experiences related to organizations. Such social media data while now successfully being used for customer analytics have not yet been fully investigated and used to understand brand personalities. Our research investigated how this data can be effectively leveraged by organizations to generate and monitor their brand in near real time. Our technique has been successfully demonstrated on Higher Education Institutes, as Higher Education is an industry that is increasingly being exposed to business competition over the last few decades.