Social media research: Theories, constructs, and conceptual frameworks

Football team quality and fans' attachment: investigating the mediating role of emotional satisfaction in changchun yatai football club (CYFC) fans

BACKGROUND

Football, as a global phenomenon, intertwines team quality and fan attachment. This study, centered on Changchun Yatai Football Club (CYFC) fans, explores how emotional satisfaction acts as a mediator in this intricate relationship, providing nuanced perspectives crucial for understanding and optimizing the dynamics of fan-team connections in football culture.

OBJECTIVES

The primary objective of this research is to examine the influence of team quality on emotional satisfaction and fans' attachment. Additionally, it aims to investigate the mediating role of emotional satisfaction in the relationship between team quality and fans' attachment. By achieving these objectives, the study seeks to contribute valuable insights into the dynamics of fan-team relationships in the context of football.

METHODOLOGY

The research adopts an applied approach in terms of its purpose, aiming to provide practical implications for football clubs. The data collection method is descriptive, utilizing electronic questionnaires voluntarily completed by 396 fans of CYFC. The research tool comprises three questionnaires: the team quality questionnaire adapted from Zhan et al. (1997), the emotional satisfaction questionnaire developed by Reynold and Bettie (1999), and a researcher-made attachment questionnaire. Structural equation modeling is employed to analyze the gathered data.

RESULTS

The results obtained through structural equation modeling reveal a significant impact of team quality on both emotional satisfaction and fans' attachment. Furthermore, a positive and significant relationship is identified between emotional satisfaction and fans' attachment. The study also confirms the positive mediating role of emotional satisfaction in the connection between team quality and fans' attachment.

CONCLUSIONS

In conclusion, the research suggests that football clubs can influence fans' attachment by strategically enhancing team quality. This improvement can be achieved through measures such as acquiring high-quality players and stars. Understanding and addressing the mediating role of emotional satisfaction can be a key strategy for clubs looking to strengthen their connection with fans. The findings provide practical insights for football clubs seeking to optimize their strategies for fan engagement and attachment.

Hate speech detection in the Arabic language: corpus design, construction, and evaluation

Hate Speech Detection in Arabic presents a multifaceted challenge due to the broad and diverse linguistic terrain. With its multiple dialects and rich cultural subtleties, Arabic requires particular measures to address hate speech online successfully. To address this issue, academics and developers have used natural language processing (NLP) methods and machine learning algorithms adapted to the complexities of Arabic text. However, many proposed methods were hampered by a lack of a comprehensive dataset/corpus of Arabic hate speech. In this research, we propose a novel multi-class public Arabic dataset comprised of 403,688 annotated tweets categorized as extremely positive, positive, neutral, or negative based on the presence of hate speech. Using our developed dataset, we additionally characterize the performance of multiple machine learning models for Hate speech identification in Arabic Jordanian dialect tweets. Specifically, the Word2Vec, TF-IDF, and AraBert text representation models have been applied to produce word vectors. With the help of these models, we can provide classification models with vectors representing text. After that, seven machine learning classifiers have been evaluated: Support Vector Machine (SVM), Logistic Regression (LR), Naive Bays (NB), Random Forest (RF), AdaBoost (Ada), XGBoost (XGB), and CatBoost (CatB). In light of this, the experimental evaluation revealed that, in this challenging and unstructured setting, our gathered and annotated datasets were rather efficient and generated encouraging assessment outcomes. This will enable academics to delve further into this crucial field of study.

#nursing. What Nurses Do on Instagram- A Mixed Methods Study

Background

Social media use is increasing every year, and nurses use social media to connect with each other. As Instagram was the most downloaded application in 2022 worldwide, this study focused on nurses' use of Instagram in the context of the development of a professional identity and in support of the professionalization of nursing.

Objectives

The aim of the study was to find out how nurses use their Instagram profiles to influence their followers' professional identity and support the professionalization of nursing. Therefore, nurses' Instagram posts and the hashtags they used were analyzed.

Methods

A visual content analysis to analyze different Instagram posts using a hierarchical cluster analysis, an ANOVA, and a qualitative content analysis were conducted. The most frequently used nursing-related hashtags were analyzed to include different Instagram profiles (n = 15) in the study.

Results

This study identified three different clusters of Instagram profiles, which can be characterized as "Show me what you do," "Let's do education," and "The things we believe in." Consequently, it can be stated that nurses who display their values and beliefs in Instagram reels, half in nursing settings and half at home, have the highest number of followers and significantly more comments per post. The cluster that showed significantly more knowledge-based posts had the lowest number of followers and significantly the lowest number of comments. The content analysis of the hashtags used suggested that nurses who identify themselves as such want to attract attention from other nurses who use nursing-related hashtags.

Conclusions

The results reveal that there is a possible benefit of the use of social media in the development of the nursing profession and professional identity. Followers and interactions can be generated when Instagram users identify with the profile and wish to discuss professional beliefs and values.

Identifying self-disclosed anxiety on Twitter: A natural language processing approach

BACKGROUND

Text analyses of social media posts are a promising source of mental health information. This study used natural language processing to explore distinct language patterns on Twitter related to self-reported anxiety diagnosis.

METHODS

A total of 233.000 tweets made by 605 users (300 reporting anxiety diagnosis and 305 not) over six months were comparatively analysed, considering user behavior, Linguistic Inquiry Word Count (LIWC), and sentiment analysis. Twitter users with a self-disclosed diagnosis of anxiety were classified as 'anxious' to facilitate group comparisons.

RESULTS

Supervised machine learning models showed a high prediction accuracy (Naïve Bayes 81.1 %, Random Forests 79.8 %, and LASSO-regression 79.4 %) in identifying Twitter users' self-disclosed diagnosis of anxiety. Additionally, a Latent Profile Analysis (LPA) identified four profiles characterized by high sentiment (31 % anxious participants), low sentiment (68 % anxious), self-immersed (80 % anxious), and normative behavior (38 % anxious).

CONCLUSION

The digital footprint of self-disclosed anxiety on Twitter posts presented a high frequency of words conveying either negative sentiment, a low frequency of positive sentiment, a reduced frequency of posting, and lengthier texts. These distinct patterns enabled highly accurate prediction of anxiety diagnosis. On this basis, appropriately resourced, awareness raising, online mental health campaigns are advocated.

Explore public concerns about environmental protection on Sina Weibo: evidence from text mining

The increasingly serious problem of ecological environmental pollution warns the importance of human environmental protection behavior. However, public attention to environmental protection plays an important role in solving environmental problems. Therefore, in order to explore the environmental concerns of Chinese residents, the trends in time and space, the relationship between online retweets, and the extraction of environmental concerns, this study analyzed the data of Sina Weibo users and their comments on related posts. At the same time, we used the text mining analysis method to analyze the social media text data, and the results are as follows. In that analysis of concern about environmental protection, women show a stronger attitude and willingness to protect the environment than men, and the public in economically developed areas is more concerned. In order to further investigate the public's environmental concerns, this study also utilized the PageRank algorithm to further study the forwarding relationships between users. The study found that celebrities and some good media organizations can attract environmental attention. Finally, we use pyLDAvis technology to visualize and analyze popular environmental themes and propose reasonable countermeasures and suggestions to enhance public environmental awareness based on the research results.

Global narratives on unequal outcomes produced by lockdown in Africa: A social science perspective on the “one-size-fits all” COVID-19 response

Introduction

Lockdown measures were introduced worldwide to prevent the spread of COVID-19, and several studies showed the positive impacts of these policies in places such as China and Europe. Many African governments also imposed lockdowns at the beginning of the pandemic. These lockdowns met with mixed reactions; some were positive, but others focused on concerns about the consequences of lockdowns.

Methods

In this article, we use social listening to examine social media narratives to investigate how people balanced concerns about preventing the spread of COVID-19 with other priorities. Analyzing social media conversations is one way of accessing different voices in real time, including those that often go unheard. As internet access grows and social media becomes more popular in Africa, it provides a different space for engagement, allowing people to connect with opinions outside of their own conceptual frameworks and disrupting hierarchies of how knowledge is shaped.

Results

This article indicates which narratives were favored by different organizations, stakeholders, and the general public, and which of these narratives are most dominant in policy discourses. The range of narratives is found to be reflective of the blindness to inequality and social difference of much decision-making by policymakers.

Discussion

Thus, contrary to the “we are all in this together” narrative, diseases and public health responses to them clearly discriminate, accentuating long-standing structural inequalities locally, nationally, and globally, as well as interplaying with multiple, dynamic, and negotiated sources of marginalization. These and other insights from this article could play a useful role in understanding and interpreting how social media could be included in pandemic preparedness plans.

When WhatsApp changed its privacy policy: explaining WhatsApp discontinuation using an enablers-inhibitors' perspective

Purpose

The purpose of this paper is to understand the factors that enable and inhibit WhatsApp users' discontinuance intention (DI) following the change in WhatsApp's privacy policy.

Design/methodology/approach

Using the enabler-inhibitor model as a framework, a research model consisting of discontinuation enabler distrust (DT) and the DT's antecedents [(negative electronic word of mouth (NEWOM), negative offline word of mouth (NOWOM) and privacy invasion (PI)], discontinuation inhibitor inertia (INR) and INR's antecedents (affective commitment, switching cost and use habit) and moderator structural assurance was proposed and tested with data from 624 WhatsApp users using partial least square structure equational modeling (PLS-SEM).

Findings

The results show that DT created due to NEWOM and a sense of PI significantly impact DI. However, INR has no significant impact on DI. Structural assurance significantly moderates the relationship between DT and DI.

Originality/value

The paper collected data when many WhatsApp users switched to other platforms due to the change in WhatsApp's terms of service. The timing of data collection allowed for collecting the real impact of the sense of PI compared to other studies where the effect is hypothetically induced. Further, the authors acknowledge social media providers' efforts to address privacy criticism and regain users’ trust, an area that has received little attention in prior literature.

Social Commerce Adoption: A Consumer’s Perspective to an Emergent Frontier

The mass diffusion of social media has enabled new commercial models in retailing. It heralded the emergence of social commerce, with consumers and retailers interacting and transacting through a multitude of social media. While the organizational benefits of such interactions have attracted much attention, little is known about the consumers’ motives. In addressing this limitation, a theoretical model was developed, extending the UTAUT2 framework. The model was then operationalized, and quantitative data collected from 108 Indonesian consumers engaged in social commerce and analyzed using the partial least squares method. The findings point to new dynamics influencing consumer behavior, driven by lifestyle, price value, facilitating conditions, and pragmatisms. Interestingly, social influence was significant yet negative indicating that consumers may be developing a distinct online persona, which is more independent and assertive to normative pressures. The results hold important theoretical and practical implications for the rapidly emerging field of social commerce.

Go Green, Go Social: Exploring the Antecedents of Pro-Environmental Behaviors in Social Networking Sites beyond Norm Activation Theory

The paucity of environmental resources and the threatening warning of global climate change have led to increasing research on environmental issues [e.g., pro-environmental behaviors (PEBs)]. Although norm activation theory (NAT) is a well-recognized theory for approaching PEBs, existing works appear insufficient to explain PEB in the context of social networking sites (SNSs) without taking contextual, emotional, and social factors into account. Grounded in the egocentric tactician model (ETM), NAT, along with the notions of guilt and social stressors, this study integrates a new ETM path, a supplemented emotional path, alongside the conventional NAT path to achieve a more complete picture of what are crucial determinants of PEBs in the context of SNSs. Social stressors positively moderate the emotional path. Data collected from 897 Facebook users confirm all of our proposed hypotheses. Results indicate that beyond the traditional NAT path, the new ETM path and the emotional path add values to illustrate PEBs on SNSs, and new constructs of self-influence on SNSs (SIS) and guilt remarkably drive PEBs alongside personal norms. Implications for theory and practice are discussed, and guidelines for future research are identified.

What keeps me engaging? A study of consumers' continuous social media brand engagement practices

Purpose

This study examines some pertinent individual-level factors and consequences of consumers' continuous social media brand engagement (SMBE) practices. Further, this study examines the moderating effect of other-efficacy to deepen the understanding.

Design/methodology/approach

Online survey data collected from 785 respondents, through a convenience sampling technique on Facebook, was analyzed through structural equation (SEM) modeling with AMOS 23.0.

Findings

The findings suggest that compatibility with lifestyle, perceived information quality and escapism, which significantly drive consumers' continuous engagement with brands on social media. However, perceived enjoyment does not. Other-efficacy duly moderates consumers' continuous SMBE practices. While continuous SMBE significantly drives consumer-based brand equity (CBBE), continuous SMBE does not have any significant relationship with consumers' subjective well-being (SWB).

Research limitations/implications

This study reports robust findings on the effects of individual-level factors that drive consumers' continuous SMBE practices. However, the study only focused on Facebook brand pages. This is a limitation for generalizability of results because the research did not take a holistic view of all types of social media.

Practical implications

The research suggests a need for managers to project their brands and share relevant and stimulating information throughout their continuous SMBE with consumers to build strong consumer–brand relationships. Managers should also engage consumers with interesting social media messages as well as both informative and transformative creative strategies to excite them. This will further give consumers a reason to continuously interact with the brand on social media platforms.

Originality/value

This study is one of the very few works to tease out pertinent factors that drive consumers' continuous SMBE practices. The paper integrates the consumer-level factors and moderating effects of other-efficacy through the lens of Social Cognitive Theory (SCT) and Uses and Gratification Theory (UGT) to make a significant contribution to the SMBE literature.

Examining social media live stream’s influence on the consumer decision-making: a thematic analysis

Social media live streaming, in the form of live video and user stories, is widely used by influencers, organisations and individuals to connect with their audiences. Its popularity is well-established in a range of theoretical and managerial contexts. However, there is a lack of scholarship on the role of this phenomenon on consumer decision-making. Filling this gap in the research is essential due to the importance of consumer decision-making in marketing and brand strategy development in organisations. Therefore, the purpose of this paper is to explore and outline the nature of the influence of live stream on the consumer decision-making. The study was part of a 12-month Netnography consisting of participant observation and social media monitoring of brand pages and branded hashtags on social media platforms, Facebook, YouTube, Twitter and Instagram. A thematic analysis revealed five main themes and a conceptual model is proposed which outlines the social media live stream’s influence on consumer decision-making at each stage.

Analysis of the structure and time-series evolution of knowledge label network from a complex perspective

Purpose

The research on social media-based academic communication has made great progress with the development of the mobile Internet era, and while a large number of research results have emerged, clarifying the topology of the knowledge label network (KLN) in this field and showing the development of its knowledge labels and related concepts is one of the issues that must be faced. This study aims to discuss the aforementioned issue.

Design/methodology/approach

From a bibliometric perspective, 5,217 research papers in this field from CNKI from 2011 to 2021 are selected, and the title and abstract of each paper are subjected to subword processing and topic model analysis, and the extended labels are obtained by taking the merged set with the original keywords, so as to construct a conceptually expanded KLN. At the same time, appropriate time window slicing is performed to observe the temporal evolution of the network topology. Specifically, the basic network topological parameters and the complex modal structure are analyzed empirically to explore the evolution pattern and inner mechanism of the KLN in this domain. In addition, the ARIMA time series prediction model is used to further predict and compare the changing trend of network structure among different disciplines, so as to compare the differences among different disciplines.

Findings

The results show that the degree sequence distribution of the KLN is power-law distributed during the growth process, and it performs better in the mature stage of network development, and the network shows more stable scale-free characteristics. At the same time, the network has the characteristics of “short path and high clustering” throughout the time series, which is a typical small-world network. The KLN consists of a small number of hub nodes occupying the core position of the network, while a large number of label nodes are distributed at the periphery of the network and formed around these hub nodes, and its knowledge expansion pattern has a certain retrospective nature. More knowledge label nodes expand from the center to the periphery and have a gradual and stable trend. In addition, there are certain differences between different disciplines, and the research direction or topic of library and information science (LIS) is more refined and deeper than that of journalism and media and computer science. The LIS discipline has shown better development momentum in this field.

Originality/value

KLN is constructed by using extended labels and empirically analyzed by using network frontier conceptual motifs, which reflects the innovation of the study to a certain extent. In future research, the influence of larger-scale network motifs on the structural features and evolutionary mechanisms of KLNs will be further explored.

The role of blogs in restoring the self-integrity of women victims of intimate partner sexual violence

Purpose

This paper aims to identify the role of blogs in helping women victims of intimate partner sexual violence to restore their self-integrity.

Design/methodology/approach

The authors’ research uses an interpretive stance, supported by motivational and “self” theories to analyze 33 blogs reporting the experiences of women in Brazil who suffered sexual violence perpetrated by an intimate partner.

Findings

This study identifies the reasons why women who suffer violence from intimate partners write blog posts. It also develops an analytical framework that bridges the gap between the design and use of IT-artifacts and the context of sexual violence from an intimate partner. Women who suffer violence from intimate partners look for blogs in order to find a safe space for expression, a knowledge hub and a social support network. Blogs play a pivotal role in supporting the journey of reconstructing their self-integrity.

Research limitations/implications

The results help to understand the role of blogs in helping victims in vulnerable situations trying to restore their self-integrity. It also contributes to improve the design and functionality of such platforms as an important resource for social support networks.

Practical implications

This study shows the positive impact of blogs as a tool to support victims in the process of restoring their self-integrity.

Social implications

This study aims to promote the use of digital artifacts such as blogs as a complementary instrument to fight violence against women.

Originality/value

The analytical framework used in this paper helps to understand the role of IT-artifacts in the context of sexual violence from an intimate partner.

A Theory-based Deep-Learning Approach to Detecting Disinformation in Financial Social Media

The spreading of disinformation in social media threatens cybersecurity and undermines market efficiency. Detecting disinformation is challenging due to large volumes of social media content and a rapidly changing environment. This research developed and validated a theory-based, novel deep-learning approach (called TRNN) to disinformation detection. Grounded in social and psychological theories, TRNN uses deep-learning and data-centric augmentation to enhance disinformation detection in financial social media. Temporal and contextual information is encoded as specific knowledge about human-validated disinformation, which was identified from our unique collection of 745,139 financial social media messages about four U.S. high-tech company stocks and their fine-grained trading data. TRNN uses multiple series of long short-term memory (LSTM) recurrent neurons to learn dynamic and hidden patterns to support disinformation detection. Our experimental findings show that TRNN significantly outperformed widely-used machine learning techniques in terms of precision, recall, F-score and accuracy, achieving consistently better classification performance in disinformation detection. A case study of Apple Inc.'s stock price movement demonstrates the potential usability of TRNN for secure knowledge management. The research contributes to developing novel approach and model, producing new information systems artifacts and dataset, and providing empirical findings of detecting online disinformation.

Understanding How and Under What Circumstances Social Media Supports Health Care Providers' Knowledge Use in Clinical Practice: A Realist Review

Background: Although theoretical frameworks exist to guide social media interventions, few of them make it explicit how social media is supposed to work to improve the knowledge use by health care providers. This study aimed to synthesize literature to understand how and under what circumstances social media supports knowledge use by health care providers in clinical practice. Methods: We followed the realist review methodology described by Pawson et al. It involved six iterative steps: (1) develop an initial program theory; (2) search for evidence; (3) select and appraise studies; (4) extract data; (5) synthesize data; and (6) draw conclusions. Results: Of the 7,175 citations retrieved, 32 documents were prioritized for synthesis. We identified two causal explanations of how social media could support health care providers' knowledge use, each underpinned by distinct context-mechanism-outcome (CMO) configurations. We defined these causal explanations as: (1) the rationality-driven approach that primarily uses open social media platforms (n = 8 CMOs) such as Twitter, and (2) the relationality-driven approach that primarily uses closed social media platforms (n = 6 CMOs) such as an online community of practice. Key mechanisms of the rationality-driven approach included social media content developers capabilities and capacities, in addition to recipients' access to, perceptions of, engagement with, and intentions to use the messages, and ability to function autonomously within their full scope of practice. However, the relationality-driven approach encompassed platform receptivity, a sense of common goals, belonging, trust and ownership, accessibility to expertise, and the fulfillment of needs as key mechanisms. Conclusion: Social media has the potential to support knowledge use by health care providers. Future research is necessary to refine the two causal explanations and investigate their potential synergistic effects on practice change.

Shape of the Uncanny Valley and Emotional Attitudes Toward Robots Assessed by an Analysis of YouTube Comments

The uncanny valley hypothesis (UVH) suggests that almost, but not fully, humanlike artificial characters elicit a feeling of eeriness or discomfort in observers. This study used Natural Language Processing of YouTube comments to provide ecologically-valid, non-laboratory results about people’s emotional reactions toward robots. It contains analyses of 224,544 comments from 1515 videos showing robots from a wide humanlikeness spectrum. The humanlikeness scores were acquired from the Anthropomorphic roBOT database. The analysis showed that people use words related to eeriness to describe very humanlike robots. Humanlikeness was linearly related to both general sentiment and perceptions of eeriness—-more humanlike robots elicit more negative emotions. One of the subscales of humanlikeness, Facial Features, showed a UVH-like relationship with both sentiment and eeriness. The exploratory analysis demonstrated that the most suitable words for measuring the self-reported uncanny valley effect are: ‘scary’ and ‘creepy’. In contrast to theoretical expectations, the results showed that humanlikeness was not related to either pleasantness or attractiveness. Finally, it was also found that the size of robots influences sentiment toward the robots. According to the analysis, the reason behind this is the perception of smaller robots as more playable (as toys), although the prediction that bigger robots would be perceived as more threatening was not supported.

Social Media Usage and SME Firms’ Sustainability: An Introspective Analysis from Ghana

Social media is gradually transforming diverse business ecosystems due to the limitless capabilities they offer. Given this, emerging businesses across the globe are leveraging this innovation to improve their operations. While the literature on the usage of social media by small and medium enterprises (SMEs) is still emerging, the outcomes from existing research have not been coherent. Amid this, limited empirical evidence has been adduced on the affordance of the technology for the SME ecosystem in developing economies, particularly Ghana. Following this, this study aims to fill this research gap by investigating the impact of social media usage on the long-term sustainability of SMEs, specifically in Ghana. Using empirical data from 424 respondents who are representatives of manufacturing SMEs in Ghana, using SmartPLS techniques, the study confirmed that, generally, social media usage does not only have a positive impact on SMEs but drastically drives their motivations towards resilience and sustainability. The results further revealed a positive and significant effect of social media usage value creation, business connections and opportunities on SMEs’ sustainability. This study contributes to knowledge of social media usage and sustainability from a developing country’s perspective. This study offers several implications for theory and practice.

Variety-Seeking Behavior in Consumption: A Literature Review and Future Research Directions

Variety-seeking is a popular choice strategy in consumers’ daily lives, and many factors influence it. This study conducted a narrative and structured literature review based on three popular online academic databases to understand how researchers used influencing factors, adopted theoretical perspectives and underlying mechanisms, and developed measure methods in their studies. This paper consolidated and analyzed 61 articles on variety-seeking behaviors in consumer research, including empirical studies spanning from 2000 to 2021. This paper primarily focused on articles published at top tiers in the marketing literature. From these articles, a collection of internal and external factors, theoretical perspectives, underlying mechanisms, and measure methods adopted was summarized and tabulated for easy reference and comprehension. A research framework was developed to illustrate the relationships between influence factors and variety-seeking proposed by previous researchers. The literature review may not be exhaustive because variety-seeking behaviors could involve various research topics; however, the proposed research framework and suggested directions may be representative references for future research. This study is a more comprehensive literature review of variety-seeking behaviors in consumption research after 2000, and it contributes to a better understanding of the causes and effects of variety-seeking behaviors in consumption.

Corporate Users' Attachment to Social Networking Sites: Examining the Role of Social Capital and Perceived Benefits

The debate on the pros and cons of employee attachment to social networking sites (SNS) has led to social media policy paralysis in many organizations, and often a prohibition on employee use of SNS. This paper examines corporate users' attachment to SNS. An analysis of 316 survey responses showed that corporate users' socialization in large public SNS was steeped in perceived work-related benefits, which in turn nourished their SNS attachment. Social use outperformed informational use in generating perceived work-related benefits from SNS. Weak ties in large heterogeneous networks resulted in strategic and operational benefits, whereas the effects of strong bonding in homogenous networks were limited to operational benefits. The paper contributes to research on SNS use by corporate users and the debate on the effect of SNS use for work. The findings will benefit SNS strategists of organizations and policymakers to exploit the benefit potential of public SNS.

A Moderated Mediation Model Linking Excessive Enterprise Social Media Usage With Job Performance

Despite the larger interest of information systems scholars in excessive ESM usage, little is known about how excessive ESM usage is related to employee performance. This study focused on excessive ESM usage and investigated its impact on employee performance. Based on the status quo perspective with the integration of social cognitive theory, this study first proposed that excessive ESM usage has a positive and negative relationship with employee performance through ESM usage regret and ESM usage inertia. Furthermore, COVID-19 threat moderates the direct relationship between excessive ESM usage and ESM usage regret, and ESM usage inertia. Time-lagged, multi-source data collected in China support most of our hypothesis. Results reveal that excessive ESM has a positive and negative indirect effect on employee performance via ESM usage regret and ESM usage inertia. Furthermore, the COVID-19 threat moderates the positive direct effect of excessive ESM usage on ESM usage inertia. In the later section, theoretical contributions and practical implications are discussed.

Value co-creation through social media: a multistakeholder, communication perspective

Purpose

Despite an increasing body of research on value co-creation through social media, service organizations still face difficulties in leveraging the potential of social media communication to facilitate value co-creation with multiple stakeholders. This article addresses this challenge by adopting a multistakeholder, communication perspective.

Design/methodology/approach

This article uses a conceptual approach and builds upon concepts widely recognized in the public relations (PR) literature to assess communication in multistakeholder social media-mediated exchanges.

Findings

This article discusses the role of social media communication in enabling value co-creation as well as the communicative challenges that come along with it. Moreover, applying PR academic insights to the service innovation and service recovery research fields, it advances theoretical propositions that predict how service organizations can successfully build upon the social media communication fundamentals – namely dialogue, engagement, social presence and conversational human voice – to trigger value co-creation with and among multiple stakeholders.

Originality/value

This article introduces selected relevant theoretical concepts from the PR field and develops novel theoretical propositions that are likely to make unique contributions to the service management field. The article also advances future research avenues that will help service and communication scholars together move the field forward.

Project Sustainability and Public-Private Partnership: The Role of Government Relation Orientation and Project Governance

In China, the government is not only responsible for the supply of local public facilities and services, but also the maker of public-private-partnership (PPP) policies and systems, and has a greater voice in PPP projects. The attitude and behavior of the government are essential to the sustainable development of PPP projects. This research focuses on the deep-seated connotation of the external attitude and behavior of the government, that is, the impact mechanism and path of the government’s relation orientation on project sustainability. First, enrich the connotation of the government’s relation orientation, project sustainability, and project governance, and improve the measurement scale. Then, construct a structural equation model, collect data through questionnaires, and explore the path of the government’s relation orientation on project sustainability. The research results show that: (1) different relation orientations have different effects on project governance and project sustainability, among which instrumental relation orientation and rent-seeking relation orientation will directly affect project sustainability; (2) relationship governance and contract governance play different mediating roles. The research results provide new ideas and perspectives for improving project governance mechanisms and project sustainability in the practice of PPP projects in China.

Social Relationship Prediction Integrating Personality Traits and Asymmetric Interactions

Social networks have become an important way for users to find friends and expand their social circle. Social networks can improve users’ experience by recommending more suitable friends to them. The key lies in improving the accuracy of link prediction, which is also the main research issue of this study. In the study of personality traits, some scholars have proved that personality can be used to predict users’ behavior in social networks. Based on these studies, this study aims to improve the accuracy of link prediction in directed social networks. Considering the integration of personality link preference and asymmetric interaction into the link prediction model of social networks, a four-dimensional link prediction model is proposed. Through comparative experiments, it is proved that the four-dimensional social relationship prediction model proposed in this study is more accurate than the model only based on similarity. At the same time, it is also verified that the matching degree of personality link preference and asymmetric interaction intensity in the model can help improve the accuracy of link prediction.

Social Media for ImpLementing Evidence (SMILE): Conceptual Framework

Background

Social media has become widely used by individual researchers and professional organizations to translate research evidence into health care practice. Despite its increasing popularity, few social media initiatives consider the theoretical perspectives of how social media works as a knowledge translation strategy to affect research use.

Objective

The purpose of this paper is to propose a conceptual framework to understand how social media works as a knowledge translation strategy for health care providers, policy makers, and patients to inform their health care decision-making.

Methods

We developed this framework using an integrative approach that first involved reviewing 5 long-standing social media initiatives. We then drafted the initial framework using a deductive approach by referring to 5 theories on social media studies and knowledge translation. A total of 58 empirical studies on factors that influenced the use of social media and its messages and strategies for promoting the use of research evidence via social media were further integrated to substantiate and fine-tune our initial framework. Through an iterative process, we developed the Social Media for ImpLementing Evidence (SMILE) framework.

Results

The SMILE framework has six key constructs: developers, messages and delivery strategies, recipients, context, triggers, and outcomes. For social media to effectively enable recipients to use research evidence in their decision-making, the framework proposes that social media content developers respond to target recipients’ needs and context and develop relevant messages and appropriate delivery strategies. The recipients’ use of social media messages is influenced by the virtual–technical, individual, organizational, and system contexts and can be activated by three types of triggers: sparks, facilitators, and signals.

Conclusions

The SMILE framework maps the factors that are hypothesized to influence the use of social media messages by recipients and offers a heuristic device for social media content developers to create interventions for promoting the use of evidence in health care decision-making. Empirical studies are now needed to test the propositions of this framework.

A trans-diagnostic cognitive behavioural conceptualisation of the positive and negative roles of social media use in adolescents’ mental health and wellbeing

Whilst research into the association between social media and mental health is growing, clinical interest in the field has been dominated by a lack of theoretical integration and a focus on pathological patterns of use. Here we present a trans-diagnostic cognitive behavioural conceptualisation of the positive and negative roles of social media use in adolescence, with a focus on how it interacts with common mental health difficulties. Drawing on clinical experience and an integration of relevant theory/literature, the model proposes that particular patterns of social media use be judged as helpful/unhelpful to the extent that they help/hinder the adolescent from satisfying core needs, particularly those relating to acceptance and belonging. Furthermore, it introduces several key interacting processes, including purposeful/habitual modes of engagement, approach/avoidance behaviours, as well as the potential for social media to exacerbate/ameliorate cognitive biases. The purpose of the model is to act as an aide for therapists to collaboratively formulate the role of social media in young people’s lives, with a view to informing treatment, and ultimately, supporting the development of interventions to help young people use social media in the service of their needs and values.

Key learning aims

(1)

Social network fatigue: revisiting the antecedents and consequences

Purpose

The study explores the antecedents and consequences of social network fatigue (SNF) using the stress–strain–outcome (S-S-O) model. It builds on the work of previous scholars in the area of SNS by focussing on the intervening processes that explain the study's focal constructs.

Design/methodology/approach

To test the proposed framework, the study draws cross-sectional data from Indian Facebook users. Data were collected using an online survey, and the final sample of 309 valid and complete responses was analysed using SmartPLS to test the study's hypotheses.

Findings

The findings of the study report fear of missing out (FoMO) to be positively related to compulsive use (CU) of Facebook. CU had positive and significant direct and indirect effects (via information and social overload) on SNF. SNF was significantly associated with both depression (DEP) and discontinuous use intention (DUI). However, Facebook use intensity (FBI)'s moderating role on the relationship between FoMO and CU was insignificant.

Originality/value

First, the current study proposes and empirically tests a comprehensive model on the lines of the S-S-O model to understand the antecedents and consequences of SNF. Second, the study uses an Indian sample that is not age-specific (adolescents or young adults), unlike most past studies. Third, it examines various intervening stages and processes (through mediation and moderation) suggested by previous scholars but not yet explored.

Social media use for health, cultural characteristics, and demographics: A survey of Pakistani millennials

Objective

Over the last 10 years, an extensive body of literature has been produced to investigate the role of social media in health. However, little is known about the impact of cultural characteristics (e.g. masculinity, collectivism, and uncertainty avoidance) on social media use regarding health-related information, especially in developing countries like Pakistan. The present study employed Hofstede’s cultural characteristics framework and uses and gratification theory to examine how Pakistani millennials’ demographic attributes and cultural characteristics are associated with their social media use for health-related information.

Method

An online survey of 722 people aged 18–35 living in Pakistan was conducted in spring 2020 to examine the intensity and frequency of social media use, health-related use of social media, cultural characteristics, and demographic attributes.

Results

Results showed that cultural characteristics—masculinity, collectivism, and uncertainty avoidance—are strongly related with their perceptions of social media importance, usefulness, and perceived ease of access for health-related information even when controlling for demographic characteristics. Age and gender are also significantly associated with their perspectives on social media for health.

Conclusions

We found that communicating and sharing information is the most important motivation for Pakistani millennials to use social media in the area of health with WhatsApp and YouTube being most preferred social media sites for health-related issues.

Detection and moderation of detrimental content on social media platforms: current status and future directions

Social Media has become a vital component of every individual's life in society opening a preferred spectrum of virtual communication which provides an individual with a freedom to express their views and thoughts. While virtual communication through social media platforms is highly desirable and has become an inevitable component, the dark side of social media is observed in form of detrimental/objectionable content. The reported detrimental contents are fake news, rumors, hate speech, aggressive, and cyberbullying which raise up as a major concern in the society. Such detrimental content is affecting person's mental health and also resulted in loss which cannot be always recovered. So, detecting and moderating such content is a prime need of time. All social media platforms including Facebook, Twitter, and YouTube have made huge investments and also framed policies to detect and moderate such detrimental content. It is of paramount importance in the first place to detect such content. After successful detection, it should be moderated. With an overflowing increase in detrimental content on social media platforms, the current manual method to identify such content will never be enough. Manual and semi-automated moderation methods have reported limited success. A fully automated detection and moderation is a need of time to come up with the alarming detrimental content on social media. Artificial Intelligence (AI) has reached across all sectors and provided solutions to almost all problems, social media content detection and moderation is not an exception. So, AI-based methods like Natural Language Processing (NLP) with Machine Learning (ML) algorithms and Deep Neural Networks is rigorously deployed for detection and moderation of detrimental content on social media platforms. While detection of such content has been receiving good attention in the research community, moderation has received less attention. This research study spans into three parts wherein the first part emphasizes on the methods to detect the detrimental components using NLP. The second section describes about methods to moderate such content. The third part summarizes all observations to provide identified research gaps, unreported problems and provide research directions.

A Comparison of the Use of Smart Devices, Apps, and Social Media Between Adults With and Without Hearing Impairment: Cross-sectional Web-Based Study

Background

eHealth and social media could be of particular benefit to adults with hearing impairment, but it is unknown whether their use of smart devices, apps, and social media is similar to that of the general population.

Objective

Our aim is to study whether adults with normal hearing and those with impaired hearing differ in their weekly use of smart devices, apps, and social media; reasons for using social media; and benefits from using social media.

Methods

We used data from a Dutch cohort, the National Longitudinal Study on Hearing. Data were collected from September 2016 to April 2020 using a web-based questionnaire and speech-in-noise test. The results from this test were used to categorize normal hearing and hearing impairment. Outcomes were compared using (multiple) logistic regression models.

Results

Adults with impaired hearing (n=384) did not differ from normal hearing adults (n=341) in their use of a smartphone or tablet. They were less likely to make use of social media apps on a smartphone, tablet, or smartwatch (age-adjusted odds ratio [OR] 0.67, 95% CI 0.48-0.92; P=.02). Use of social media on all devices and use of other apps did not differ. Adults with hearing impairment were more likely to agree with using social media to stay in touch with family members (OR 1.54, 95% CI 1.16-2.07; P=.003) and friends (age-adjusted OR 1.35, 95% CI 1.01-1.81; P=.046). Furthermore, they were more likely to agree with using social media to perform their work (age-adjusted OR 1.51, 95% CI 1.04-2.18; P=.03). There were no differences in the experienced benefits from social media.

Conclusions

The potential for eHealth is confirmed because adults with hearing impairment are not less likely to use smart devices than their normal hearing peers. Adults with hearing impairment are less likely to use social media apps on a smart device but not less likely to use social media on all types of internet-connected devices. This warrants further research on the types of social media platforms that adults with hearing impairment use and on the type of device on which they prefer to use social media. Given that participants with hearing impairment are more likely than their normal hearing peers to use social media to perform their work, use of social media may be seen as an opportunity to enhance vocational rehabilitation services for persons with hearing impairment.

A SEM-NCA Approach towards Social Networks Marketing: Evaluating Consumers' Sustainable Purchase Behavior with the Moderating Role of Eco-Friendly Attitude

This paper aims to investigate how social network marketing affects consumers' sustainable purchase behavior (CSPB) while considering the role of Eco-friendly attitude. The statistical population of the study included Iranian users of online social networks with at least one online purchasing experience. An online questionnaire was distributed on Instagram, Telegram, and WhatsApp platforms as the most popular networks in the country. By use of convenience sampling, commonly used in quantitative studies to overcome bias, 450 out of 475 returned questionnaires were acceptable, showing a response rate of 94.7%. The results indicated that an increase in Eco-friendly attitude positively increases the effect of word of mouth on consumers' sustainable purchase behavior. Meanwhile, Necessary Condition Analysis (NCA) revealed that to reach a 50% level of consumers' sustainable purchase behavior, six essential necessary conditions are required: an eco-friendly consumers' attitude at no less than 50%, the trend at no less than 57.1%, word of mouth at no less than 45.5%, interaction at no less than 42.9%, customization at no less than 35.3% and entertainment at no less than 26.7%. Furthermore, the Importance-Performance Matrix Analysis (IPMA) was investigated as a strategic tool. The results of IPMA showed that "buy products that use biodegradable material in packaging", "buy those products that are picked up and recycled", and "buy biodegradable products even if they belong to a less well-known company" show desirable performance and high importance and there is a great opportunity for expansion in this area.

Knowledge management for extreme public health events COVID-19: based on Tiktok data

Purpose

Taking the COVID-19 as the background, this study aims to investigate the direct influencing factors regarding knowledge sharing behavior (KSB) on new media platforms and discuss how the characteristics of the users could enhance the KSB through moderation effect, and provide empirical evidences.

Design/methodology/approach

Based on the social exchange theory and after the text analysis of the data collected from the Tiktok platform in 2020, this paper uses the quantitative method to evaluate the factors influence KSB on short video social platform during the COVID-19 outbreak.

Findings

KSB on new media platform could be enhanced by richer knowledge content of the video posted and the attribute of the platform users directly. Platform users could affect the trustworthiness of the knowledge shared, thus influence the knowledge sharing. On the early stage of the COVID-19, the richer content of the knowledge released by users could effectively enhance the KSB. On the early stage of the emergency events, the official users could play a significant role on KS. During the mitigation stage of COVID-19, the KSB of the knowledge shared by unofficial users with richer content could be enhanced and the moderation effect is relatively stronger.

Originality/value

The research extends the social exchange theory to a disaster management context. The authors provide an effective reference for future governments to effectively cope with the epidemic and spread public knowledge in an emergency response context. By analyzing the influence of knowledge content and influencer characteristics, it could help the social media platform to improve content management and optimize resource allocation.

Use of Social Media to Exchange Critical Care Practice Evidence During the Pandemic

BACKGROUND

The evidence-based practice (EBP) process was challenged during the early phase of the COVID-19 pandemic by factors such as a novel disease, rapidly changing guidelines, shortage of personal protective equipment, and other health care supplies.

OBJECTIVES

Our aims were to (1) explore sources of evidence sought by critical care nurses during a pandemic and (2) explore nurses' perceptions of EBP.

METHODS

A qualitative exploratory study was conducted using deidentified data from the American Association of Critical-Care Nurses (ACCN) open-access Facebook page, January 28 to April 30, 2020.

RESULTS

Two major themes were identified: (1) "sharing and seeking evidence," that is, nurses used both formal and informal sources to explore evidence supporting evolving clinical practices, and (2) "concerns about evidence," that is, nurses expressed concerns about lack of evidence and mistrust of evolving evidence.

DISCUSSION

Initially, there was a mismatch in nurses' expectations of the American Association of Critical-Care Nurses Facebook page. A major limitation of Facebook is the lack of a repository for quick retrieval of information. Despite these limitations, and fear and mistrust of changing guidelines, social media was used to communicate, collaborate, and share evidence to support clinical practice. Critical care nurses seemed to value evidence to support patient management and their personal safety during this evolving health crisis.

CONCLUSIONS

Social media played a large role in dissemination of timely evidence-based information during the early pandemic. Our results show that current EBP models should be revised to prepare for future crises and include direction for dealing with limited health care resources, and lack of and/or rapidly changing evidence.

Analyzing Natural Digital Information in the Context of Market Research

The dynamics of irreversible multidimensional digitalization of production and consumption processes can be described today with a linear-positive or even exponential function. A significant part of the information background of a product, enterprise or brand is formed by their consumers, competitors or partners on the Internet, which considerably increases its accessibility and spread. Such kind of information can be called natural digital information (NDI). Its high market value is counterbalanced by its inhomogeneity and complexity for analysis. The solution to this problem lies in the field of creating automated tools for its subsequent search, aggregation, primary processing, quantification and analysis. The aim of this study is to describe the unique methodological properties of market research based on natural digital information. In order to achieve this aim, this study analyzes the theoretical basis in the field of NDI research, defines the categories of NDI and sources of its formation, describes the key properties of NDI, determines its advantages in comparison with other types of market information, and suggests a basic methodology for conducting typical NDI-based market research. An applied research study was carried out according to the designed methodology to show its advantages, as well as to describe the unique methodological properties of market research based on processing of NDI. The main result of this study is a universal algorithmic model for analyzing NDI in the context of market research, which includes a mechanism for defining and categorizing the digital sources of NDI, a model for forming the key properties of NDI, and basic classes of NDI analytical metrics. The toolkit developed by the authors allows market research to be conducted without direct attraction of research subjects, which results in cost reduction and elimination of the phenomenon of social desirability; this creates the so-called reasoned advertising messages that meet the requests of the target audience, which is proved by the big data that underlie the presented methodology. The developed algorithmic model is universal for analyzing natural digital information, and, with minor adaptations, can be used by any subject conducting market research.

Twitter Users' Views on Mental Health Crisis Resolution Team Care Compared With Stakeholder Interviews and Focus Groups: Qualitative Analysis

BACKGROUND

Analyzing Twitter posts enables rapid access to how issues and experiences are socially shared and constructed among communities of health service users and providers, in ways that traditional qualitative methods may not.

OBJECTIVE

To enrich the understanding of mental health crisis care in the United Kingdom, this study explores views on crisis resolution teams (CRTs) expressed on Twitter. We aim to identify the similarities and differences among views expressed on Twitter compared with interviews and focus groups.

METHODS

We used Twitter's advanced search function to retrieve public tweets on CRTs. A thematic analysis was conducted on 500 randomly selected tweets. The principles of refutational synthesis were applied to compare themes with those identified in a multicenter qualitative interview study.

RESULTS

The most popular hashtag identified was #CrisisTeamFail, where posts were principally related to poor quality of care and access, particularly for people given a personality disorder diagnosis. Posts about CRTs giving unhelpful self-management advice were common, as were tweets about resource strains on mental health services. This was not identified in the research interviews. Although each source yielded unique themes, there were some overlaps with themes identified via interviews and focus groups, including the importance of rapid access to care. Views expressed on Twitter were generally more critical than those obtained via face-to-face methods.

CONCLUSIONS

Traditional qualitative studies may underrepresent the views of more critical stakeholders by collecting data from participants accessed via mental health services. Research on social media content can complement traditional or face-to-face methods and ensure that a broad spectrum of viewpoints can inform service development and policy.

Do Deterrence Mechanisms Reduce Cyberloafing When It Is an Observed Workplace Norm? A Moderated Mediation Model

Despite the documented individual, job, and organizational antecedents of cyberloafing at the workplace, few studies have addressed whether, how and when group factors affect employees’ cyberloafing behaviors. Drawing on social learning theory and general deterrence theory, the purpose of this study is to test if observability of coworkers’ cyberloafing behavior affects employees’ perceptions of norms related to cyberloafing and subsequent cyberloafing behaviors and to test if sanctions can play a role in buffering these effects. An investigation of 335 employees working at Chinese enterprises establishes that observing others engaging in cyberloafing influences the employees’ perceived norms and cyberloafing behaviors and that employees’ perceived norms related to cyberloafing play a partial mediating role in the relationship between observability and employees’ cyberloafing. As predicted, we also found that perceived certainty and severity of potential sanctions for cyberloafing moderate the effect of observability on employees’ cyberloafing as well as the indirect effect of observability on employees’ cyberloafing via perceived norms related to cyberloafing. This study enriched the cyberloafing literature by revealing how observability of cyberloafing influences employees’ cyberloafing and by unveiling two boundary conditions under which the cyberloafing learning effect can be buffered.

Antecedents and outcomes of enterprise social network usage within UK higher education

Purpose

The purpose of this paper is to investigate factors influencing knowledge sharing on enterprise social network (ESN) use behaviour among academic staff in universities, using the unified theory of acceptance and use of technology (UTAUT) as the underlying research framework

Design/methodology/approach

A conceptual framework was created by extending the UTAUT by incorporating three additional factors, namely, feature value (FV), relationship expectancy (RE) and professional benefits. A quantitative approach based on the survey was used to collect data from 254 academic staff. Data were analysed using structural equation modelling.

Findings

The result indicated significant differences around factors influencing both consumptive and contributive usage patterns within ESNs. These factors suggest more contributive than consumptive use.

Research limitations/implications

Future research should consider a longitudinal study focusing on the change in ESN use behaviour among academic staff and the fundamental aspects influencing this change.

Originality/value

This study extends the UTAUT model by incorporating three additional factors: FV, RE and professional benefits, to study ESN use behaviour in a higher education context. This study has significantly modified UTAUT to include the dynamic nature of ESN usage.