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Digital self-expression, recently one of the most important research themes, is currently under-researched. In this context, this study aims to propose a parsimonious research model of self-extension tendency, its drivers and its outcomes. The model is tested in the context of social media engagement intentions (liking, sharing and commenting) with focal brands and across individualist versus collectivist cultures.

The model is tested in two individualist cultures (N = 230 and 232) and two collectivist cultures (N = 232 and 237) by conducting surveys in four countries (Australia, USA, Qatar and India). Nike and Ray-Ban are the focal brands studied, with Facebook serving as the targeted social networking site (SNS) platform.

Self-monitoring and self-esteem are found to drive the self-extension tendency across cultures, with stronger effects in the individualist culture than in the collectivist culture. The self-extension tendency has a relatively stronger positive influence on social media engagement intentions in the individualist culture than in the collectivist culture. This tendency is also found to mediate the link between self-monitoring, self-extension and social media engagement intentions across both cultures, albeit in different ways. In collectivist culture, self-monitoring’s influence on the self-extension tendency is moderated by public self-consciousness. The study’s findings have important theoretical and practical implications. In individualist culture, self-monitoring’s influence on the self-extension tendency is moderated by public self-consciousness.

The present findings confirm that the tendency to incorporate the brand into one’s self-concept and to further extend the self is indeed contingent on one’s cultural background. The role of public self-consciousness may vary between individualist and collectivist cultures, something recommended by past research for empirical testing.

Managers can leverage this research model to entice pro-brand social media engagement by nurturing consumers’ digital selves in terms of maneuvering their self-extension tendency and its drivers, namely, self-monitoring and self-esteem. Second, promoting the self-extension tendency and its drivers varies across cultures, with this finding offering practical cultural nuances supporting marketing managers’ decisions.

This is one of the pioneering studies that tests a cross-cultural parsimonious model based on theories of self-extension, self-monitoring and self-esteem, especially within the context of brand engagement intentions on an SNS platform.

The present research aimed to identify the motivations, needs, wants, preferences and limitations of corporate professionals with regard to business social analytics.

Online interviews were conducted with 26 professionals the majority of whom work at the management level at 20 reputable corporations in Turkey. Both qualitative and quantitative data was collected during these interviews, which lasted an average of one hour.

The findings shed light on the motivations of corporate professionals for monitoring social media and other digital media, their perceived capability and limitations in doing so, the media that they monitor and wanted to monitor if possible, their criteria and processes for working with service providers in the field of business social analytics, their needs which are not fully met by service providers, their suggestions on service improvement and their reflections on how internal and external customer data can be analyzed with an integrated approach.

This research is an attempt to bridge the gap between the priorities of engineers who generate artificial intelligence for the purposes of social listening and analytics and the end users, e.g. corporate communication professionals. Only by doing so, this field, which is getting more and more important as people spend more time online, will reach its full potential and benefit corporations by providing fruitful insight upon which strategic steps can be taken.

During COVID-19, this study aims to evaluate the crisis communication strategies (CCS) of Fortune 500 medical device businesses. These companies’ CCS adoption is evaluated using data from the microblogging site Twitter.

A total of 11,569 tweets were collected over the course of a year, from 31 December 2019 to 31 December 2020, and analysed using COVID-19’s pre-crisis, crisis and new normal stages. The data acquired from Twitter is assessed using latent Dirichlet allocation-based topic modelling, valence aware dictionary for sentiment reasoning sentiment analysis and emotion recognition analysis and then further examined using fuzzy set qualitative comparative analysis to build a configurational model. The findings were compared to Cheng’s (2018, 2020) integrated strategy toolkit for organisational CCS, which included 28 strategies.

With positive sentiments across stages, companies chose “information providing”, “monitoring” and “good intentions” as the CCS. In the crisis and new normal stages of COVID, the emotion of “depression” was observed.

Researchers would be able to assess the CCS used through visual aids in the future by conducting a cross-industry examination using image analytics. Furthermore, by prolonging the study’s duration, long-term changes in the CCS can be investigated.

Companies should send real-time information to their stakeholders via social media during a pandemic, conveying good intentions and positive sentiments while remaining neutral.

To the best of the authors’ knowledge, this is one of the first studies to investigate the CCS patterns used by medical device businesses to communicate via social media during a pandemic.

The significance of social media in our lives is manifold. The tourism sector closely interacts with existing and potential tourists through social media, and therefore, social media analytics (SMA) play a critical role in the uplift of the sector. Hence, this review focus on the role of SMA in tourism as discussed in different studies over a period of time. The purpose of this paper to present the state of the art on social media analytics in tourism.

The review focuses on identifying different SMA techniques to explore the trends and approaches adopted in the tourism sector. The review is based on 83 papers and discuss the studies related to different social media platforms, the travelers' reactions to a particular place and how the tourism experience is enriched by the way of SMA.

Findings indicate different sentiments associated with tourism and provides a review of tourists’ use of social media for choosing a travel destination. The various analytical approaches, areas such as social network analysis, content analysis, sentiment analysis and trend analysis were found most prevalent. The theoretical and practical implications of SMA are discussed. The paper made an effort to bridge the gap between different studies in the field of tourism and SMA.

SMA facilitate both tourists and tourism companies to understand the trends, sentiments and desires of tourists. The use of SMA offers value to companies for designing quick and adequate services to tourists.

Based on a relationship marketing approach, this paper aims to study the influence of social media use on salesperson performance and its underlying mechanisms from the perspective of salespeople in B2B settings.

To test the proposed model, the authors used structural equation modeling with a sample of 196 French B2B salespeople. Moreover, to explore the moderating effect of emotional management between social media use and relationship quality, the authors used the Hayes macro PROCESS for SPSS and the Johnson–Newman’s floodlight method.

The authors confirm the direct role of social media use on salesperson performance, and its indirect role through the parallel mediation of social proximity and relationship quality. The empirical study provides evidence for the moderating effect of emotional management on the relationship between social media use and relationship quality.

Companies should promote the use of social media to increase both the sales and creative performance of salespeople. Moreover, salespeople with low to moderate abilities to manage other people’s emotions benefit strongly from the use of social media, as this directly increases their relationship with their customers.

The research complements the conceptualization of salesperson performance as a combination of sales performance and sales creativity and shows that emotional management is an asset for social media users to develop valuable business relationships.

The paper aims to construct a spatiotemporal situational awareness framework to sense the evolutionary situation of public opinion in social media, thus assisting relevant departments in formulating public opinion control measures for specific time and space contexts.

The spatiotemporal situational awareness framework comprises situational element extraction, situational understanding and situational projection. In situational element extraction, the data on the COVID-19 vaccine, including spatiotemporal tags and text contents, is extracted. In situational understanding, the bidirectional encoder representation from transformers – latent dirichlet allocation (BERT-LDA) and bidirectional encoder representation from transformers – bidirectional long short-term memory (BERT-BiLSTM) are used to discover the topics and emotional labels hidden in opinion texts. In situational projection, the situational evolution characteristics and patterns of online public opinion are uncovered from the perspective of time and space through multiple visualisation techniques.

From the temporal perspective, the evolution of online public opinion is closely related to the developmental dynamics of offline events. In comparison, public views and attitudes are more complex and diversified during the outbreak and diffusion periods. From the spatial perspective, the netizens in hotspot areas with higher discussion volume are more rational and prefer to track the whole process of event development, while the ones in coldspot areas with less discussion volume pay more attention to the expression of personal emotions. From the perspective of intertwined spatiotemporal, there are differences in the focus of attention and emotional state of netizens in different regions and time stages, caused by the specific situations they are in.

The situational awareness framework can shed light on the dynamic evolution of online public opinion from a multidimensional perspective, including temporal, spatial and spatiotemporal perspectives. It enables decision-makers to grasp the psychology and behavioural patterns of the public in different regions and time stages and provide targeted public opinion guidance measures and offline event governance strategies.

Consumers are increasingly choosing social media over other channels and mechanisms for grievance redressal. However, not all social media grievances elicit a response from businesses. Hence, in this research the authors aim to explore the effect of the complainant's social characteristics and the complaint's social and content characteristics on the likelihood of receiving a response to a grievance from the business on social media.

The authors build a conceptual model and then empirically test it to explore the effect of the complainant's characteristics and the complaint's characteristics on the likelihood of response from a business on social media. The authors use data of consumer grievances received by an Indian airline operator on Twitter during two time periods – the first corresponding to lockdown during Covid-19 pandemic, and the second corresponding to the resumption of business as usual following these lockdowns. The authors use logistic regression and the hazard rate model to model the likelihood of response and the response delay, respectively, for social media customer grievances.

Complainants with high social influence are not more likely to get a response for their grievances on social media. While tagging other individuals and business accounts in a social media complaint has negative effect on the likelihood of business response in both the time periods, the effect of tagging regulatory bodies on the likelihood of response was negative only in the Covid-19 lockdown period. The readability and valence of a complaint were found to positively affect the likelihood of response to a social media grievance. However, the effect of valence was significant only in lockdown period.

This research offers insights on what elicits responses from a service provider to consumers' grievances on social media platforms. The extant literature is a plenty on how firms should be engaging consumers on online media and how online communities should be built, but scanty on grievance redressal on social media. This research is, therefore, likely to be useful to service providers who are inclined to improve their grievance handling mechanisms, as well as, to regulatory authorities and ombudsmen.

While there has been a growing call for insights on algorithms given their impact on what people encounter on social media, it remains unknown how enhanced algorithmic knowledge serves as a countermeasure to problematic information flow. To fill this gap, this study aims to investigate how algorithmic knowledge predicts people's attitudes and behaviors regarding misinformation through the lens of the third-person effect.

Four national surveys in the USA (N = 1,415), the UK (N = 1,435), South Korea (N = 1,798) and Mexico (N = 784) were conducted between April and September 2021. The survey questionnaire measured algorithmic knowledge, perceived influence of misinformation on self and others, intention to take corrective actions, support for government regulation and content moderation. Collected data were analyzed using multigroup SEM.

Results indicate that algorithmic knowledge was associated with presumed influence of misinformation on self and others to different degrees. Presumed media influence on self was a strong predictor of intention to take actions to correct misinformation, while presumed media influence on others was a strong predictor of support for government-led platform regulation and platform-led content moderation. There were nuanced but noteworthy differences in the link between presumed media influence and behavioral responses across the four countries studied.

These findings are relevant for grasping the role of algorithmic knowledge in countering rampant misinformation on social media, as well as for expanding US-centered extant literature by elucidating the distinctive views regarding social media algorithms and misinformation in four countries.

This study aims to elucidate institutional analysis as an effective approach to investigating and designing the multilevel policymaking system of online social networks (OSN) for achieving a participatory model.

The institutional mapping approach has been used to analyze Iran’s OSN multilevel policymaking system. A combination of two matrices, including institutions-institutions and institutions-functions, was used to perform the institutional mapping. Two main steps were taken to draw the mentioned matrices. First, a review of related studies in Iran’s OSN policymaking system was conducted and the policy functions mentioned in these studies were identified and categorized using the meta-synthesis. Second, based on analyzing two policy documents of Iran’s OSN, institutions and their interactions were identified and policy functions were allocated to institutions.

Based on the results, the most important policy functions in the current OSN policymaking system in Iran are support, regulatory, monitoring and evaluation, business environment development, culture building and promotion, organizing licenses and permissions, policymaking and legislation. Also, the results show that there are shortcomings in this system, some of the most important of which are lack of transparency in regulatory, little work in culture building and promotion, neglect of the training of specialized human resources and research and development, slow development of the business environment and neglecting the role of nongovernmental organizations in policymaking.

By examining and analyzing how different institutions operate within a multilevel policymaking system, the policymaking process and its overall effectiveness can be enhanced. This analysis helps identify any inconsistencies, overlaps or conflicts in the roles and policies of these institutions, leading to a better understanding of how a multilevel policymaking system is organized.

Consumers are increasingly spending more time on social media platforms to cope with anxiety and loneliness resulting from the recent pandemic. The extraordinary times, characterised by isolation and lockdown, has placed increasing dependence on online technology as a coping mechanism in which social media influencers (SMIs) served as the human face of brands, helping both consumers and brands maintain human connection. How should practitioners navigate their social media campaigns in this changing environment?

To answer this question, the Source Connectedness Pyramid is proposed to help explain and compare the interactions between consumers and SMIs in ordinary and extraordinary times.

In their interactions with influencers during ordinary times, consumers are satiated with influencer source characteristics of attractiveness, trustworthiness and expertise. However, during extraordinary times, consumers substitute their usual preference to focus on connectedness, characterised by relatedness, belongingness and attachment.

The empirical study within this paper lends support to this proposition and offers additional insights. The proposed Source Connectedness Pyramid contributes to influencer communication theoretically and has strategic implications for practitioners when navigating their social media campaigns in these extraordinary times.