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When the spread of online health rumors on social media causes public concerns, the public is calling for action. However, little study has investigated how Facebook reaction icons (expressing feelings function) affect online users' behavioral intentions (intention to trust and share) toward online health rumor posts. The current study addresses this gap by focusing on the effect of Facebook reaction icons in two conditions: Facebook reaction icons' presence (versus absence), and Facebook reaction icons' emotional valence (positive versus negative versus neutral). Moreover, the authors also investigated the interaction between Facebook reaction icons' emotional valence and online health rumor posts' framing headlines (gain versus loss).

The authors used a 7 (Facebook reaction icons: Love, Like, Haha, Wow, Sad, Angry and no icon) × 2 (Facebook framing headlines: gain and loss) between-subjects design, analyzing 507 samples from online users with one-way ANOVA and MANOVA.

Results show that online health rumor posts without Facebook reaction icons are more likely to negatively change online users' behavioral intentions than the posts with Facebook reaction icons; negative reaction icons (Sad and Angry) lower online users' behavioral intentions than positive reaction icons (Love and Like). Further, the incongruency effect of interaction (i.e. positive reaction icons with a negative message) would have more negative effects on online users' behavioral intentions than the congruency effect (i.e. positive reaction icons with a positive message).

This study has rich contributions to theoretical and practical implications for the Facebook platform and Facebook users to apply Facebook reaction icons against online health rumor posts.

Social media allow for observing different aspects of human behaviour, in particular, those that can be evaluated from explicit user expressions. Based on a data set of posts with user opinions collected from social media, this paper aims to show an insight into how the readers of different news portals react to online content. The focus is on users’ emotions about the content, so the findings of the analysis provide a further understanding of how marketers should structure and deliver communication content such that it promotes positive engagement behaviour.

More than 5.5 million user comments to posted messages from 15 worldwide popular news portals were collected and analysed, where each post was evaluated based on a set of variables that represent either structural (e.g. embedded in intra- or inter-message structure) or behavioural (e.g. exhibiting a certain behavioural pattern that appeared in response to a posted message) component of expressions. The conclusions are based on a set of regression models and exploratory factor analysis.

The findings show and theorise the influence of social media content on emotional user engagement. This provides a more comprehensive understanding of the engagement attributed to social media content and, consequently, could be a better predictor of future behaviour.

This paper provides original data analysis of user comments and emotional reactions that appeared on social media news websites in 2018.

Mobile social network games (mSNGs) are gaining increasing popularity recently. Many of the games are marketed using the brand pages on social network services including Facebook. The purpose of this paper is to identify the characteristics of the posts on the brand pages that affect the reaction of users.

Four independent variables were tested for their influence on user reaction: informativeness, structure, call for action, and the type of reward. In total, 439 posts on the brand pages of two mobile game companies on Facebook were manually collected. The hypotheses were tested using multiple regression analysis.

The characteristics of the brand pages appeared to have significant impact on the users’ reaction. Overall, being informative, calling for action, and providing content-related (game-related) rewards have significant and positive impact on the reaction of users. Using only texts or embedding videos or hyperlinks in the posts has either negative or no significant impact on the reaction of users.

The literature review shows that not many empirical studies have been conducted so far about the brand pages of mSNGs. Therefore, this study contributes to the understanding of users’ reaction on the brand pages for mSNGs, and how companies should manage their communication effort on the pages.

This study investigates the Centers for Disease Control and Prevention (CDC) Facebook Page to examine what kinds of information is shared to public using Facebook and how Facebook users share and engage with information during a health crisis situation with a case of the COVID-19 pandemic.

Using Facebook Graph API, CDC's Facebook Page posts and users' engagement and reactions for six months from January to June 2020 were collected and analyzed. The posts were categorized into five categories. Users' engagement and reactions include share, comment, like, love, haha, wow, sad and angry.

The findings show that the type of posts have significant association with COVID-19 situation and the level of users' engagement and reactions differs significantly when COVID-19 related information is shared. The findings show that users become more active during health emergency situation. The results provided an insight into how different types of posts gain users' attention and motivation to interact.

This study investigates the use of social media during a national health crisis situation. While literature provides the use of social media during emergency and crisis cases, as health crisis situation is unique in that the boundary of time and location as well as people's daily life, the findings of this study provide an insight into how health authorities could communicate with the public during a health crisis situation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2020-0416

The main goal of this study is to employ unsupervised (lexicon-based) learning approaches to identify readers' emotional dimensions and thumbs-up empathy reactions to reviews of online travel agency apps based on appraisal and stimulus–organism–response (SOR) theories.

Using the Google Play Scraper, we gathered a total of 402,431 reviews from the Google Play Store for two travel agency apps, Tripadvisor and Booking.com. Following the filtering and cleaning of user reviews, we used lexicon-based unsupervised machine learning algorithms to investigate the associations between various emotional dimensions of reviews and review readers' thumbs-up reactions.

The study's findings reveal that the sentiment of different sorts of reviews has a substantial influence on review readers' emotional experiences, causing them to give the app a thumbs up review. Furthermore, readers' thumbs-up responses to the text reviews differed depending on the eight emotional aspects of the reviews.

The results of this research can be applied in the development of online travel agency apps. The findings suggest that app developers can enhance users' emotional experiences by considering the sentiment and emotional aspects of reviews in their design and implementation. Additionally, the results can be used by travel agencies to improve their online reputation and attract more customers by providing a positive user experience.

The findings of this research have the potential to have a significant impact on society by providing insights into the emotional experiences of users when they engage with online travel agency apps. The study highlights the importance of considering the emotional aspect of user reviews, which can help app developers to create more user-friendly and empathetic products.

The current study is the first to evaluate the impact of users' thumbs-up empathetic reactions on user evaluations of online travel agency applications using unsupervised (lexicon-based) learning methodologies.

This paper aims to look at the effects of different levels of involvement (high and low) on social media (Facebook) users' engagement (likes, shares and comments) with different types and formats of brand content.

The authors analyzed user reactions to 1,156 Facebook posts from eight business-to-consumer brands (goods and services). Based on a post hoc test, four product/services were identified as belonging to the group of high-involvement and the other four as low involvement.

The data suggest that, when involvement is low, users in general engage more with brand posts regardless their format (text, image and post) or type (hedonic and informative), or even the interaction of both. Moreover, low involvement leads users prefer to comment on brand content, whereas higher involvement is associated with to sharing it. Exceptions were observed for images (both hedonic and informative) and for hedonic image and video in both low and high involvement users.

The goal was not to measure users’ attention to each type of post. Moreover, the authors did not have access to information regarding which devices were used to access the online content and whether that aspect might have an impact on users’ reactions. Neither do they claim that engagement necessarily reflects positive reactions, as any content analysis of users’ reactions was beyond the scope of this project.

These findings are expected to help brand managers and social media strategists to better select content based on their marketing goals, as well as to provide a potential explanation for the success of campaigns.

As far as we are aware, no previous study has attempted to observe the mediated effect of consumer involvement on brand posts considering their type and format. We also believe that this is the first observation of how behavior differentiates according to the target audience’s level of involvement. This paper also proposes a convenient framework for categorizing social network sites content. Suggestions for future research are made at the end.

This study aims to understand if an online dating app is considered an acceptable channel to conduct advertising activities and understand the differences between Generations X, Y and Z for such acceptance.

A total of 411 Tinder users’ reactions were obtained and analyzed using text mining to compute the sentiment score of each response, and a Kruskal–Wallis H test to verify if there are statistical differences between each generation.

The results showed positive acceptability toward the marketing campaign on Tinder, especially Z Generation. Nevertheless, the statistical analysis revealed that the differences between each generation are not statistically significant.

The main limitation relates to the fact that the participants, during the data collection, revealed their identification, perhaps leading to acquiescence bias. In addition, the study mainly covered the male population. A balanced sample would be positive to examine any possible differences between gender.

Results provide an essential indication for companies regarding their marketing activities conducted on Tinder to fully exploit the possibility of using Tinder as an alternative and valuable channel to conduct marketing activities.

Up until now, no studies tried to understand the effect of a marketing activity online on an online dating app.

This paper aims to investigate user preferences for the information systems in order to achieve user satisfaction by using conjoint analysis.

Conjoint analysis is applied for the measurement of user preferences on information systems by seven properties and three levels for each property. To apply the approach, two surveys were designed: the first survey investigates the main properties affecting the end-users' satisfaction for using the current information systems based upon literature review and expert interview in Phase I. The second survey weighed the preferences by the virtual profiles of the information systems, which represent the ideal systems.

The results show that speed-related properties are critical to achieve the end-user satisfaction. The next important property group is related to the access control and system integration between various business modules. From the measurements, the best system file should be constructed with the highly weighed levels of the key attributes.

The virtual profiles are complex for respondents to understand the attributes and the compounds of the virtual products. Moreover, the respondents were overwhelmed by the number of virtual profiles. The attributes were required to enable communication between researchers and respondents.

Information system designers can achieve user satisfaction by combining the highest utility levels of all attributes. Nonetheless, the trade-offs between attributes and their levels should be considered in order to apply the results to the business, depending on the system environments and business practices, by updating the importance of the determinants regularly.

This study applied the conjoint analysis to information management systems in order to design and maintain user satisfaction for the targeted company. This paper will provide alternative ways for the system engineers and developers of the case company by considering the critical attributes, which will affect both user performance and satisfaction.

Augmented reality (AR) has become a trend, and the effects of Pokémon Go, the most popular online and mobile game, have been explored in many studies. However, few studies have developed questionnaires of fit to investigate the relationship between the fit and the integration of the game's virtual world and reality. The paper intends to integrate the models of stimulus-organism-response (S-O-R) and information systems success with cognitive fit theory to explore the fit and reactions of users in the integration of real and virtual worlds.

Following MacKenzie's scale development, two surveys were conducted. The first survey was conducted to perform a scale development of fit. The second survey was collected from 315 Pokémon Go players to validate the fit scale and it was analyzed via structural equation modeling.

The results show that scale development of fit has good reliability and validity. Furthermore, game information quality, game system quality and virtual (Pokémon) characteristics have significantly positive effects on cognitive and emotional fit. Cognitive and emotional fit have significant positive effects on user satisfaction, and user satisfaction has significant positive effects on continued intention to play. The results suggest that maintaining the quality of the game and improving the virtual interface will provide a better fit between the real and virtual worlds, enhancing user satisfaction with the fit as well as their intention for continued use.

Although fit has been widely studied in various contexts, the application of AR has been rarely discussed. This study develops a scale of fit and takes Pokémon Go as the subject to validate the fit measurement and discuss players' cognition and feelings regarding the game. The authors measure user reactions to different stimuli and explore cognitive and emotional fit as well as the integration of virtual worlds and reality. In sum, to the best of the authors’ knowledge, this is one of the earliest studies to explore and develop a cognitive and emotional fit scale for future researchers and practitioners.

The purpose of this study is to examine whether users’ perceived moral affect explains the effect of perceived intensity of emotional distress on responsibility judgment of a perpetrator and company, respectively, in an ill and good intention breach.

Participants completed a questionnaire containing items measuring their perceived intensity of emotional distress, perceived moral affect and responsibility judgment of a perpetrator and company, respectively.

The results support the mediating hypothesis on responsibility judgment of a perpetrator regardless of intention. The mediating hypothesis is also supported in an ill intention breach in responsibility judgment of a company. However, the mediating effect is not observed in a good intention breach when users assess a company’s responsibility.

The findings support the notion that users use the consequentialism approach when assessing a perpetrator’s responsibility because they focus on the victims’ emotional distress and discount a perpetrator’s intent, resulting in similar mediating effect of perceived moral affect in an ill and good intention breach. The results also indicate that perceived moral affect increases the negative effect of perceived intensity of emotional distress on responsibility judgment of a company, suggesting that users may exhibit empathetic feelings toward a company and perceive it as a victim of an ill intention breach. The lack of mediating effect in responsibility judgment of a company in a good intention breach may be attributed to the diminished effect of a perpetrator’s feelings of regret, sorrow, guilt and shame for causing emotional distress to the victims.