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Due to the size and importance of social media, user-generated content analysis is becoming a key factor for companies and brands across the world. By using Twitter messages’ content, the purpose of this paper is to identify which elements of the messages enable tweet diffusion and facilitate eWOM.

In total, 30,082 tweets collected from 10,120 Twitter users were classified based on four assorted brands. By comparing with multiple regression techniques high vs low purchase involvement and hedonic vs utilitarian products and using the theory of heuristic-systematic processing of information, the authors examine the causes of tweet diffusion.

The authors illustrate how the elements of a tweet (hashtags, mentions, links, sentiment or tweet length) influence its diffusion and popularity.

This study validated the use of information processing theories in the social media field. The study showed a picture on how different Twitter elements influence eWOM and message diffusion under several purchase involvement situations.

The results of this study can help social media brand community managers of all types of companies on how to write their Twitter messages to obtain greater dissemination and popularity.

The study offers a unique deep brand analysis which helps brands and companies to understand their social media popularity in detail. Depending on product category, companies can achieve maximum social impact on Twitter by focusing on the interactivity items that will work best for their products or brands.

The purpose of this study is to examine the different results and the level of success obtained with advertising campaigns developed on Facebook to promote postgraduate programs to create awareness and engagement.

This study combined the data envelopment analysis technique to measure advertising efficiency with multidimensional scaling (MDS) representation, thus offering alternatives for practitioners and organizations on how to evaluate social advertising performance.

Investments on social paid advertising are an affordable and effective way both to promote postgraduate programs and create engagement with prospective students. Facebook advertisements maximize visibility, which improves social and online positioning and encourages student recruitment.

Higher education institutions can efficiently promote their programs with a minimal social investment contributing to dissemination and engagement. Compared to other forms of traditional or digital advertising, social media ads can be efficient and affordable with wider segmentation and targeting options. Moreover, results are immediate and measurable and campaigns can be instantly modified to better suit the audience’s requirements.

This study is unique as it offers a new, alternative way of measuring efficiency, in addition to the classic ratios of payment models in digital advertising that combine clicks and impressions, on a sector where there are few empirical studies. Moreover, it can be easily applied to many other sectors in public and private organizations.

El objetivo de esta investigación es examinar los diferentes resultados y el nivel de éxito obtenido con las campañas publicitarias desarrolladas en Facebook para promover programas de postgrado que aumenten la notoriedad y la participación de los mismos.

Combinamos la técnica de análisis de envolvente de datos (DEA) para medir la eficiencia de la publicidad con la representación de escalado multidimensional (MDS), ofreciendo alternativas tanto a profesionales como a organizaciones sobre cómo evaluar el rendimiento de la publicidad social.

Las inversiones en publicidad social pagada son una forma asequible y efectiva tanto para promover programas de postgrado como para crear un compromiso con los posibles estudiantes. Los anuncios en Facebook maximizan la visibilidad, lo que también mejora el posicionamiento social y en línea, fomentando la captación de estudiantes.

Las instituciones de educación superior pueden promover eficazmente sus programas con una inversión social mínima que contribuya a la difusión y el engagement. En comparación con otras formas de publicidad tradicional o digital, los anuncios de los medios sociales pueden ser eficientes y asequibles, con una segmentación y opciones de orientación más amplias. Además, los resultados son inmediatos y cuantificables y las campañas pueden modificarse instantáneamente para adaptarse mejor a las necesidades del público objetivo.

Esta investigación es única ya que ofrece una nueva y alternativa forma de medir la eficiencia, además de los ratios clásicos de los modelos de pago en la publicidad digital que combinan clics e impresiones, en un sector en el que hay pocos estudios empíricos. Además, puede aplicarse fácilmente a muchos otros sectores en organizaciones públicas y privadas.

The aim of this study is first, to investigate the relative effect of user-generated content (UGC) and firm-generated content (FGC) on online brand advocacy, and second, to examine the mediation effect of customer engagement and the moderation effect of brand familiarity in the relationship between UGC and FGC and online brand advocacy. The differential impact of UGC and FGC on consumer behavior has yet to receive sufficient academic attention among hospitality scholars.

Based on social learning theory, cognitive consistency theory and schema theory, this study established an integrated research framework to explain the relationship between the constructs of the study. This study adopts a scenario-based experimental design in two separate studies within contexts to examine the proposed hypotheses.

The results revealed that UGC is a stronger predictor of online brand advocacy than FGC. A mediation analysis supported that the effect of digital content marketing types on online brand advocacy occurs because of customer engagement. Further, when the brand was familiar, participants showed a higher level of online brand advocacy than when they were exposed to FGC (vs. unfamiliar brand), whereas the effect of familiar and unfamiliar brands on online brand advocacy remains slightly close to each other when the participants were exposed to UGC. Brand familiarity positively enhanced participants’ engagement when they were exposed to UGC. Further, customer engagement is only a significant mediator when the brand is unfamiliar.

This paper presents significant managerial implications for hospitality companies about how they can effectively enhance brand advocacy in the online medium.

This research provides a novel contribution by examining the differential impact of UGC and FGC on online brand advocacy as well as uncovering the underlying mechanism of how and under what conditions user- and firm-generated content promotes online brand advocacy in the hospitality context.

The objective of this study is to investigate the differential impact of gain versus loss message framing on the effectiveness of corporate social responsibility (CSR) communications in eliciting online brand engagement within the hospitality industry. Furthermore, this research aims to examine the extent to which evoked happiness and message credibility mediate the relationship between CSR message framing and online brand engagement, as these mediating factors have not been thoroughly examined in the existing academic literature.

This study utilizes a between-subjects experimental design to test an integrative research framework, which is grounded in message framing theory and the elaboration likelihood model (ELM), in order to examine the interrelationships among the various constructs of the study within a coffee shop context on Facebook.

The findings of this study indicate that gain framing is a more powerful predictor of online brand engagement than loss framing. A mediation analysis supports the assertion that the effects of CSR framing communications on online brand engagement are mediated by evoked happiness and message credibility. Specifically, when the CSR message was framed in a positive (gain) manner, it was perceived as more credible and evoked more happiness, leading to increased online brand engagement. Additionally, the study’s results provide empirical evidence for the notion that the happiness elicited by brand messages enhances their credibility, leading to further online brand engagement.

This research makes a novel contribution to the literature by investigating the distinct effects of message framing on online brand advocacy and examining the complex interrelationships that modulate consumer engagement within the context of the hospitality industry.

This paper aims to explore the relationship between the characteristics of social media health information and its adoption. The purpose is to identify information characteristics that can be used to estimate the level of health information adoption in advance.

According to the Information Adoption Model (IAM), the study extracted ten information characteristics from the aspects of information quality and information source credibility. The sample data was collected from the top ten influential health accounts based on the Impact List of Sina Weibo to test the effectiveness of these characteristics in distinguishing information at different levels of adoption. The forecasting of information adoption level is regarded as a binary classification question in the study and support vector machine (SVM) is used to do the research.

The results indicate that ten information characteristics chosen in this study are related to information adoption. Based on these information characteristics, it is feasible to estimate the level of health information adoption, and the estimation accuracy is relatively high.

A lot of work has been done in previous researches to reveal the factors that influence information adoption. The theoretical contribution of this work is to further discuss how to use the influencing factors to do some predictive work for information adoption. In practice, it will help health information publishers to disseminate high-quality health information more effectively as well as promote the adoption of health information.