Search results

A clickbait is a deceptive headline designed to boost ad revenue without presenting closely relevant content. There are numerous negative repercussions of clickbait, such as causing viewers to feel tricked and unhappy, causing long-term confusion, and even attracting cyber criminals. Automatic detection algorithms for clickbait have been developed to address this issue. The fact that there is only one semantic representation for the same term and a limited dataset in Chinese is a need for the existing technologies for detecting clickbait. This study aims to solve the limitations of automated clickbait detection in the Chinese dataset.

This study combines both to train the model to capture the probable relationship between clickbait news headlines and news content. In addition, part-of-speech elements are used to generate the most appropriate semantic representation for clickbait detection, improving clickbait detection performance.

This research successfully compiled a dataset containing up to 20,896 Chinese clickbait news articles. This collection contains news headlines, articles, categories and supplementary metadata. The suggested context-aware clickbait detection (CA-CD) model outperforms existing clickbait detection approaches on many criteria, demonstrating the proposed strategy's efficacy.

The originality of this study resides in the newly compiled Chinese clickbait dataset and contextual semantic representation-based clickbait detection approach employing transfer learning. This method can modify the semantic representation of each word based on context and assist the model in more precisely interpreting the original meaning of news articles.

This paper aims to conduct an interdisciplinary systematic literature review (SLR) of fake news research and to advance the socio-technical understanding of digital information practices and platforms in business and management studies.

The paper applies a focused, SLR method to analyze articles on fake news in business and management journals from 2010 to 2020.

The paper analyzes the definition, theoretical frameworks, methods and research gaps of fake news in the business and management domains. It also identifies some promising research opportunities for future scholars.

The paper offers practical implications for various stakeholders who are affected by or involved in fake news dissemination, such as brands, consumers and policymakers. It provides recommendations to cope with the challenges and risks of fake news.

The paper discusses the social consequences and future threats of fake news, especially in relation to social networking and social media. It calls for more awareness and responsibility from online communities to prevent and combat fake news.

The paper contributes to the literature on information management by showing the importance and consequences of fake news sharing for societies. It is among the frontier systematic reviews in the field that covers studies from different disciplines and focuses on business and management studies.

Propaganda is a prevalent technique used in social media to intentionally express opinions or actions with the aim of manipulating or deceiving users. Existing methods for propaganda detection primarily focus on capturing language features within its content. However, these methods tend to overlook the information presented within the external news environment from which propaganda news originated and spread. This news environment reflects recent mainstream media opinions and public attention and contains language characteristics of non-propaganda news. Therefore, the authors have proposed a graph-based multi-information integration network with an external news environment (abbreviated as G-MINE) for propaganda detection.

G-MINE is proposed to comprise four parts: textual information extraction module, external news environment perception module, multi-information integration module and classifier. Specifically, the external news environment perception module and multi-information integration module extract and integrate the popularity and novelty into the textual information and capture the high-order complementary information between them.

G-MINE achieves state-of-the-art performance on both the TSHP-17, Qprop and the PTC data sets, with an accuracy of 98.24%, 90.59% and 97.44%, respectively.

An external news environment perception module is proposed to capture the popularity and novelty information, and a multi-information integration module is proposed to effectively fuse them with the textual information.

This study aims to investigate how message sidedness affects the impact of fake news posted on social media on consumers' emotional responses.

The study involves a face-tracking experiment in which 198 participants were exposed to different fake news messages concerning the COVID-19 vaccine. Specifically, participants were exposed to fake news using (1) a one-sided negative fake news message in which the message was entirely unfavorable and (2) a two-sided fake news message in which the negative message was mixed with favorable information. Noldus FaceReader 7, an automatic facial expression recognition system, was used to recognize participants' emotions as they read fake news. The authors sampled 17,450 observations of participants' emotional responses.

The results provide evidence of the significant influence of message sidedness on consumers' emotional valence and arousal. Specifically, two-sided fake news positively influences emotional valence, while one-sided fake news positively influences emotional arousal.

The current study demonstrates that research on fake news posted on social media may particularly benefit from insights regarding the potential but often overlooked importance of strategic design choices in fake news messages and their impact on consumers' emotional responses.

The purpose of this study is to explore the plurality of logics composing an organizational field and how that plurality affects a sport governing body's (SGB) sense of self. The authors sought to determine what logics exist in a specific field and how they interact according to Kraatz and Block's (2017) types of organizational responses. Finally, the authors explore how an organization's responses affect organizational outcomes.

The authors analyzed 476 unique organizational web pages and documents and 293 news media articles from four news outlets. The authors conduct a content analysis informed by Gioia et al.’s (2013) method to explore the website data to understand the logics of the field. The authors analyze the media articles for media accounts of events and determine how logics inform an SGB's actions (Cocchairella and Edwards, 2020).

The authors find institutional plurality leads to a fractured organizational sense of self, resulting in poor outcomes. The authors' findings suggest Kraatz and Block's (2017) as well as other previously theorized strategies do not lead to an organization reconciling competing logics. Rather, the strategies employed led to outcomes harming the organization's legitimacy and financial well-being.

There are several calls within the broader management field and the sport management field to address institutional plurality (Kraatz and Block, 2017; Robertson et al., 2022). Unlike previous research studies, this study finds detrimental effects of plurality on an organization. The authors discuss the strength of the strategies employed and why the strategies failed.

This study aims to explore the spillover effects of data breaches from a consumer perspective in the e-commerce context. Specifically, we investigate how an online retailer’s data breach affects consumers’ privacy risk perceptions of competing firms, and further how it affects shopping intention for the competitors. We also examine how the privacy risk contagion effect varies depending on the characteristics of competitors and their competitive responses.

We conducted two scenario-based experiments with surveys. To assess the spillover effects and the moderating effects, we employed an analysis of covariance. We also performed bootstrapping-based mediation analyses using the PROCESS macro.

We find evidence for the privacy risk contagion effect and demonstrate that it negatively influences consumers’ shopping intention for a competing firm. We also find that a competitor’s cybersecurity message is effective in avoiding the privacy risk contagion effect and the competitor even benefits from it.

While previous studies have examined the impacts of data breaches on customer perceptions of the breached firm, our study focuses on customer perceptions of the non-breached firms. To the best of the authors’ knowledge, this study is one of the first to provide empirical evidence for the negative spillover effects of a data breach from a consumer perspective. More importantly, this study empirically demonstrates that the non-breached competitor’s competitive response is effective in preventing unintended negative spillover in the context of the data breach.

The COVID-19 pandemic triggered an increase in online traffic, with many assuming that this technology would facilitate coping through active social connections. This study aims to interrogate the nature of this traffic-engagement relationship by distinguishing between passive (e.g. browsing) and active (e.g. reacting, commenting and sharing) engagement, and examining behavioral shifts across platforms.

Three field studies assessed changes in social media engagement during the COVID-19 pandemic. These studies included social media engagement with the most followed accounts (Twitter), discussion board commenting (Reddit) and news content sharing (Facebook).

Even though people spent more time online during the pandemic, the current research finds people were actively engaging less. Users were reacting less to popular social media accounts, commenting less on discussion boards and even sharing less news content.

While the current work provides a systematic observation of engagement during a global crisis, it does not claim causality based on its correlational nature. Future research should test potential mechanisms (e.g. anxiety, threat and privacy) to draw causal inference and identify possible interventions.

The pandemic shed light on a complex systemic issue: the misunderstanding and oversimplification of how online platforms facilitate social cohesion. It encourages thoughtful consideration of online social dynamics, emphasizing that not all engagement is equal and that the benefits of connection may not always be realized as expected.

This research provides a postmortem on the traffic-engagement relationship, highlighting that increased online presence does not necessarily translate to active social connection, which might help explain the rise in mental health issues that emerged from the pandemic.

Just like human beings, some companies engage in recurrent bad behaviour that negatively impacts their stakeholders and their prospects for long-term survival. For example, some firms become caught up in a vortex of corruption. SNC-Lavalin, a large Canadian consulting engineering company, is an example of one organisation that embarked on this path. Since then, the company has taken numerous steps to overcome its persistent problems with corruption. The object of this study is to determine whether these steps can be compared to the 12-step program of Alcoholics Anonymous (AA), which is recognised for helping individuals overcome addiction to alcohol and drugs.

To examine events at SNC-Lavalin between 2000 and 2022, the authors carry out an in-depth examination of internal and external documentation. Three sources of data are used: archival documents, news articles and corporate documentation.

The results of the analysis show that the AA 12-step program seems to correspond to the steps SNC-Lavalin has taken over time. The “organisational” version of this program that the authors have developed could be useful to advisers of companies that are struggling with other types of bad behaviour and wish to stamp it out. These bad behaviours include the exploitation of vulnerable manpower, the exploitation of consumers through planned obsolescence or aggressive sales practices and pollution in all its forms.

The study has certain limitations. It should be noted that the analyses were limited to public information. In addition, given the quantity of public information available for the period from 2009 to 2022, a methodical approach to selecting the sources of information elements was applied, which inevitably entailed ignoring other sources of information (e.g. television, radio and internet).

This study adds to previous work by providing an original and global perspective of the steps taken by a large international consulting engineering firm to overcome its recurring corruption problems. The parallel drawn with AA’s 12-step programs seems to correspond surprisingly well to the steps taken by the company. This parallel can potentially serve as a roadmap for advisers who have to counsel companies on recurring misconduct that has harmful repercussions for their stakeholders.