122 research outputs found

    What influences the dissemination of online rumour messages in social media: the role of message, communicator, channel and rumour features

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    Social media enables efficient and easy exchange of information. However, this not only enhances the sharing of valid information but also facilitates the dissemination of rumours which may have harmful impacts on individuals, companies and the society. To manage the impacts of rumours, it is important to understand the drivers and patterns of online rumour message dissemination. Considering the uniqueness of social media as information exchange platforms, this thesis aims to understand the themes and traits of online rumour topics and messages. Moreover, traditional rumour theories often study individual motivation of rumouring; however, in social media, messages are mostly broadcasted and can be accessed by the public, diminishing the influences of individual recipients’ attributes. This thesis thus seeks to develop a message-level framework to delineate how message features, communicator features and channel features influence the dissemination of online rumour messages and how rumour features moderate those effects. Specifically, this thesis considers online rumour messages as persuasive messages. Combining rumour theories, persuasion theories, emotion theories and congruence theories, this thesis aims to investigate the roles of cognitive appeals (i.e. content unambiguity and source unambiguity), affective appeals (i.e. message pleasantness, activation and imagery), communicator attributes (i.e. communicator trustworthiness, proximity, social influence and likeability), communication channels (i.e. hashtag and @) and rumour features (i.e. rumour target reputation and rumour valence) in influencing online rumour message dissemination in social media. Furthermore, the patterns of online rumour message dissemination may vary across rumour topics. To deepen the understanding of rumour message dissemination, this thesis also aims to summarise topic-level dissemination patterns of online rumour messages. Based on the research aims and objectives, this thesis takes a multi-method research design. First, an exploratory qualitative content analysis was carried out to understand the types of online rumour topics and the themes of online rumour messages. The findings were used to support the development of research framework. Second, the research framework and corresponding hypotheses were tested quantitatively using regression. Third, linguistic analyses were applied to describe how rumour messages vary across different types of rumour topics, and the effects of research framework were compared. Qualitative exploration finds that an online rumour topic may target a business’s brand, its offerings, its people or its operations and may focus on what happens, why or with what impacts. Results of regression analysis reveal that expression certainty, emotional activation, community communication and communicator attributes are positively associated with the number of retransmissions (i.e. the number of retweets in this research context) of online rumour messages, whereas the source explicitness, source accessibility, emotional pleasantness, emotional imagery and direct communication are negatively associated with the number of retransmissions. In addition, both topic-congruence (i.e. congruence between rumour target reputation and rumour topic valence) and message-congruence (i.e. congruence between rumour target reputation and rumour message valence) play important moderating roles. Results also show that for different types of rumour topics, the effects of cognitive and affective appeals on online rumour dissemination are different. This thesis contributes to the existing literature in five aspects. First, it applies rumour theory to the context of social media and updates rumour theories by introducing expression certainty, use of evidence, source explicitness and source accessibility as new dimensions of information unambiguity. Second, this thesis investigates the effects of emotional pleasantness, activation and imagery on rumour dissemination, bringing new insights to rumour theories from emotion theories. Third, built on congruence theories and persuasion theories, this thesis investigates how topic-congruence and message-congruence moderates the effects of cognitive appeals and affective appeals on rumour dissemination. By doing so, this thesis extends rumour theory by combining the rumour context features and rumour message features. Moreover, this thesis identifies different types of online rumour topics and illustrates that online rumour messages are disseminated differently across rumour topics, enriching the understanding of online rumour dissemination on social media. Furthermore, while traditionally researchers have found it difficult to identify rumours and trace their disseminations, this thesis uses social media data to track rumours and their disseminations. Using social media data, this thesis tests the proposed research framework at rumour message level and explores the patterns of aggregate rumour message dissemination at rumour topic level. Practically, the findings of this thesis can be used to identify viral rumour messages so that practitioners can monitor and control rumours efficiently and effectively

    When Service Recovery Becomes Visible: Effects Of Recovery Strategies On Electronic Word-of-mouth Receiver

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    The emergence of social media stimulates electronic word-of-mouth (eWOM) and makes consumers’ service encounter experiences ‘visible’ to a wide range of information receivers. In the existing literature, eWOM is mostly studied as the consequences of service failure and service recovery. This study extends prior research by bridging the service recovery experiences of eWOM communicators and the attitudes and behaviors of eWOM receivers. Using scenario-based experiments, this study tests eWOM receiver’s responses to the communicator’s experience and compares the impacts of different service recovery strategies. The results confirm that, for eWOM receivers, vicarious distributive, procedural and interactional justices influence their brand attitudes, which further affect their purchase intentions. Moreover, results support that the relationship between brand attitude and purchase intention is moderated by the perceived information credibility. It is also found that, compared to observing apology, eWOM receivers tend to have more positive justice perceptions and brand attitudes and stronger purchase intentions when they observe compensation. However, whether the recovery is conducted at the service failure scene or after eWOM are not significantly different. This study contributes to the previous literature on service recovery by incorporating vicarious justice in understanding how eWOM receivers develop attitudes and behavioral intentions from others’ service recovery experiences in social media. The findings can be used by service providers to guide their recovery strategies

    Understanding the Dissemination of Online Rumor Message in Social Media: The Roles of Emotions and Content Ambiguity

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    Social media enhances information exchange efficiency, yet it also facilitates the dissemination of rumors which can cause harmful consequences for companies and the society. Previous research mainly focuses on identifying online rumor messages and examining individual rumoring behavior; however, little is known about what makes some online rumor messages disseminate more than others. In this study, we propose that content unambiguity and emotional appeal influence dissemination of rumor, and when situational emotion is congruent with emotional appeal, the effect of emotional appeal on dissemination is strengthened whereas the effect of content unambiguity is weakened. To test the hypotheses, data were collected from Twitter and labelled via sentiment analysis and manual coding. This study contributes to previous literature by extending the conceptualization of content ambiguity and understanding how content ambiguity and emotions at different levels influence rumor message dissemination

    The Influence of Anthropomorphic Chatbot Design on Consumer Tolerance of Service Failures: The Mediating Roles of Attachment and Cognitive Dissonance

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    Problem statement: The widespread use of chatbots in hospitality and tourism leads to inevitable service failures. Although research has investigated the influence of chatbots` anthropomorphic cues, comprehending how distinct anthropomorphic cues influence user behavior in service failure is still limited. Methodology: To explore how the anthropomorphic design of chatbots affect user`s tolerance for service failure, this research conducts a 2 (anthropomorphic appearance: 3D vs. 2D) x 2 (language style: informal vs. formal) x 2 (interdependent self-construal: high vs. low) between-subject online experiment. Result: Results show that the congruent anthropomorphic cues of chatbots can significantly improve consumers \u27 tolerance, where attachment mediates this process positively. Additionally, the interdependent self-construal level plays a positive moderating role in this process. Implications: This study contributes theoretically by explicating anthropomorphism in attachment and cognitive dissonance theory and extending the understanding of self-construal theory. Moreover, the study provides recommendations for managers to design effective anthropopathic chatbots

    What triggers sharing in viral marketing? The role of emotion and social feature

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    Viral marketing has attracted attention from both academics and practitioners. With the rise of user-generated content (UGC) and broadcasting networks, viral online video advertising campaigns (viral advertising in short) are an emerging trend in viral marketing. Previous literature mainly studied the influence of network structure on viral advertising. Here, we extend such works by decomposing the diffusion network into individual sharing behavior. We based our work on theories of emotion and social networks by proposing a framework that specifies the role of emotion and social feature on individuals’ sharing of online video advertisements in viral marketing campaigns. The framework will be tested using real-world data extracted from online broadcasting networks in the future work

    How Social Experience Encourages Donation Intention to Charitable Crowdfunding Projects on Social Media: Empathy and Personal Impulsiveness

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    Embedding charitable crowdfunding into social media is a new practice that encourages prosocial behaviors. The rich social experience in charitable crowdfunding on social media distinguishes this context from other conventional contexts like charity fundraising websites. Specifically, this study incorporates social experience, empathy and personal impulsiveness to investigate donation intention in this new context. By analyzing survey data collected in China, this study finds that empathy mediates the effects of interaction with fundraiser and perceived proximity with donatee on a user’s donation intention. Social influence on social media platform is found to have positive influences on empathy and on donation intention. This study also investigates how empathy’s influence on donation intention varies by personal impulsiveness. It contributes to extant literature by highlighting the mediating role of empathy and the moderating role of personal impulsiveness. It also provides practical insights to encourage pro-social behaviors

    Adversarial Training for Physics-Informed Neural Networks

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    Physics-informed neural networks have shown great promise in solving partial differential equations. However, due to insufficient robustness, vanilla PINNs often face challenges when solving complex PDEs, especially those involving multi-scale behaviors or solutions with sharp or oscillatory characteristics. To address these issues, based on the projected gradient descent adversarial attack, we proposed an adversarial training strategy for PINNs termed by AT-PINNs. AT-PINNs enhance the robustness of PINNs by fine-tuning the model with adversarial samples, which can accurately identify model failure locations and drive the model to focus on those regions during training. AT-PINNs can also perform inference with temporal causality by selecting the initial collocation points around temporal initial values. We implement AT-PINNs to the elliptic equation with multi-scale coefficients, Poisson equation with multi-peak solutions, Burgers equation with sharp solutions and the Allen-Cahn equation. The results demonstrate that AT-PINNs can effectively locate and reduce failure regions. Moreover, AT-PINNs are suitable for solving complex PDEs, since locating failure regions through adversarial attacks is independent of the size of failure regions or the complexity of the distribution

    Reproducing Kernel Method for Singular Fourth Order Four-Point Boundary Value Problems

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    Abstract. This paper investigates the analytical approximate solutions of singular fourth order four-point boundary value problems using reproducing kernel method (RKM). The solution obtained by using the method takes the form of a convergent series with easily computable components. However, the RKM can not be used directly to solve singular fourth order four-point boundary value problems (BVPs), since there is no method of obtaining reproducing kernel (RK) satisfying four-point boundary conditions. The aim of this paper is to fill this gap. A method for obtaining RK satisfying four-point boundary conditions is proposed so that RKM can be used to solve singular fourth order four-point BVPs. Results of numerical examples demonstrate that the method is quite accurate and efficient for singular fourth order four-point BVPs

    What drives people to purchase virtual gifts in live streaming? The mediating role of flow

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    Live streaming, a new form of social media, is growing explosively due to its real-time interaction and new monetization model. Considering its popularity and unique features, it is important to gain a theoretical understanding of live streaming. Yet limited attention has been paid to it. This research investigates what factors may affect people’s consumption intention of virtual gifts in live streaming from contextual and personal dimensions. Based on flow theory, this study also explores the mediating role of flow and the moderating role of gender. The theoretical framework is tested using Structural Equation Modeling based on survey data collected in China. The study contributes to flow theory by highlighting the importance of flow in mediating the effects of interactivity, social presence, curiosity and social media dependence on consumption intention of virtual gifts. It also reveals gender differences in the influence of flow on consumption intention of virtual gifts
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