Variables of Twitter´s brand activity that influence audience spreading behaviour of branded content

Abstract

This paper investigates spreading behavior of branded content, within an online brand community. A total of 41.392 pieces of content were gathered to analyze the activity of 45 Twitter brands, in the Spanish food industry, during one-year period. The study uses an Exploratory Factor Analysis (EFA) to reveal the structure of that spreading behavior, addressing two key constructs: propagation and sharing. In addition, multiple regression analysis is conducted to identity the influence of the independent variables controlled by the company, which predict that spreading action on the proposed structural model. Findings indicate the significant effect of variables such as: mentions made by the brand, posting time or volume of tweets, in predicting audience spreading behavior. Controversially, results suggest that brand use of the retweet function generates a negative influence on audience response. The research also innovates exploring the impact of sentiment expressions used by the brand on audience spreading behavior.

The Efficiency of Social Network Services Management in Organizations. An In-Depth Analysis Applying Machine Learning Algorithms and Multiple Linear Regressions

“…This could lead us to think that the variables in the publication topics´category could also be considered as independent variables. However, this work, in line with previous studies on the efficiency of social media management in organizations, used as independent variables those commonly taken by the research community when evaluating the recognition of publications [9,16,28]. That is, the variables contained in the category (f), Retweeted Pubs.…”

“…Regarding the use of social media in the business context, several works can be highlighted [15][16][17][18][19]. Balan's research [15] explored the way in which the topics of the Instagram posts of a major sports equipment brand influenced the recognition received by its publications.…”

“…Matosas López [16] analyzed the aspects that condition the propagation of the content of companies in the food sector on Twitter. The author examined the way in which the interactivity of the content (links or mentions), the vividness of the publications (photos or hashtags), the sentiment of the emoticons, and the posting time influenced the dissemination of messages.…”

“…As soon as the user perceives that the need that had originated his or her connection with the organization has been satisfied, he or she reacts positively by resorting to the relevant functionalities enabled in the platform. According to some authors [9,16,28], the user manifests this recognition of the organization by sharing its content or marking it as a favorite.…”

“…2:00 to 4:00, Pub. 5:00 to 7:00 (e) Publication topic 16 Central topic discussed in the pub. (f) Recognition obtained by the publication 2 Retweeted Pubs.…”