An NLP-SEM approach to examine the gratifications affecting user’s choice of different e-learning providers from user tweets

ABSTRACT

In this digital era, it is important for service providers to gain insights from the customer-generated data and act accordingly for gaining a competitive advantage over competitors. However, there are few studies that have attempted at utilising the online user-reviews in structural-models for examining the factors affecting user-behaviour. Additionally, there is a paucity of studies that have utilised the sentiment and emotional aspects to understand the motives affecting usage intentions. This study attempts to address this gap by exploring various uses and gratifications valued by users for different e-learning providers in India, namely, Coursera, Lynda, Udemy, Udacity and Byjus, by analysing the tweets posted by users using various official handles. Utilising a Natural-Language-Processing (NLP)-based approach (sentiment and opinion-mining) and 5868 tweets, the customer motives were analysed and mapped to the various gratifications. Results of the natural language processing-based structural-equation-modelling (NLP-SEM) technique show that consumers of different companies value gratifications differently.

KEYWORDS:

• Elearning services
• structural equation modelling
• text mining
• twitter data
• uses and gratifications theory

Disclosure statement

No potential conflict of interest was reported by the authors.