Consumer engagement with a brand on Facebook

: linguistic category model analysis

Abstract

Over the past years, social media has changed the way organizations promote business online and the use of digital technologies, such as Facebook, Instagram or Twitter by brands to share product-related information, as well as to engage with consumer has grown significantly. Nowadays, the vast majority of brands have incorporated the several social media channels into their marketing strategies with the purpose to spread their business faster as well as to engage with customers more efficiently. Facebook has been identified as one of the most used social networking platform presenting valuable opportunities andbenefits for both consumers and marketers (Kallas, 2020; Smith, 2020). Although several are the brands that have been using Facebook to interact with consumers, there are still doubts regarding what is the best strategy and/or how the language type used by brands on the digital environment shapes the relationship between brands and costumers. Therefore, the purpose of this dissertation is to analyze the relationship between the type of language posted by brands on consumer engagement in Facebook users. Due to the heterogeneity ofthe several brands presented in this dissertation, brands were segmented according to their different number of followers. Language was categorized and analyzed based on the continuum pole of abstraction and concreteness provided by the Linguistic Category Model (LCM) proposed by Semin & Fiedler (1991) and consumer engagement was measured through several Facebook metrics, namely the number of comments and likes on posts and the number of likes for brands. Results showed that for companies between 50 and 579 followers a more abstract language increases the number of likes of the brand, while for companies between 580 and 3.138 followers, a more concrete language increases the number of likes on posts as well as of brand pages. In future studies, it would be useful to understand the nature of companies with different numbers of followers to understand what type of factors can influence the type of language used by them.

Date of Award	4 Dec 2020
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Cláudia Simão (Supervisor)