Motivations to interact with brands on Facebook – Towards a typology of consumer–brand interactions

In recent years, Facebook and other social media have become key players in branding activities. However, empirical research on consumer–brand interactions on Facebook is still in its infancy. Therefore, the aim of this research is to provide additional insights to brand managers on how to adapt their approaches to increase consumers’ interactions with brands on Facebook. In this study, we apply the uses and gratification theory proposed by Katz (1959) to develop a new typology of consumers based on consumer motivations to interact with brands on Facebook, and explore the type and intensity of these interactions. We identify five main motivations that might influence consumers’ interactions with a brand on Facebook: (1) social influence, (2) search for information, (3) entertainment, (4) trust and (5) reward. Building on these five motivations, a classification using clustering techniques reveals four different groups of consumers: (1) “brand detached”, (2) “brand profiteers”, (3) “brand companions” and (4) “brand reliants”. Our results provide valuable and applicable insights for social media marketing activities, which will assist brand managers to develop strategies for effectively reaching and influencing the most desirable groups of consumers.

Analysis of COVID-related symptoms from a database of Italian tweets

Twitter is a highly popular social media which on one hand allows information transmission in real time and on the other hand represents a source of open access homogeneous text data. We propose an analysis of the most common self-reported COVID symptoms from a dataset of Italian tweets to investigate the evolution of the pandemic in Italy from the end of September 2020 to the end of January 2021. After manually filtering tweets actually describing COVID symptoms from the database - which contains words related to fever, cough and sore throat - we discuss usefulness of such filtering. We then compare our time series with the daily data of new hospitalisations in Italy, with the aim of building a simple linear regression model that accounts for the delay which is observed from the tweets mentioning individual symptoms to new hospitalisations. We discuss both the results and limitations of linear regression given that our data suggests that the relationship between time series of symptoms tweets and of new hospitalisations changes towards the end of the acquisition.

Labor Relations Information and News, October 2007

The purpose of this newsletter is to inform and update State agencies on relevant labor relations issues and employment law on a monthly basis, and to focus on topics or questions agencies would like more information about.

Labor Relations Information and News, July 2007

The purpose of this newsletter is to inform and update State agencies on relevant labor relations issues and employment law on a monthly basis, and to focus on topics or questions agencies would like more information about.

Labor Relations Information and News, August 2007

The purpose of this newsletter is to inform and update State agencies on relevant labor relations issues and employment law on a monthly basis, and to focus on topics or questions agencies would like more information about.

Labor Relations Information and News, September 2007

The purpose of this newsletter is to inform and update State agencies on relevant labor relations issues and employment law on a monthly basis, and to focus on topics or questions agencies would like more information about.

News and Information, Summer-Fall 2007

Newsletter produced by the Iowa Agricultural Development Authority.

News and Information, Spring 2009

Newsletter produced by the Iowa Agricultural Development Authority.