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This paper aims to investigate the mechanisms through which social media news consumption across different platforms leads to opinion polarization in society. To this end, the authors draw from cultivation theory to examine whether social media news consumption imparts a mainstreaming or resonance effect. Media consumption imparts a mainstreaming effect if frequent users, regardless of their social identity, develop homogenous attitudes about issues, whereas resonance is at play if there is a differing cultivation effect on various social groups depending on their relatability of life experiences.

The authors conduct the study in the developing context of India, using a population survey dataset from 2019. Regression-based mediation and moderation analyses were carried out to test the hypotheses.

The findings reveal that resonance is the most prominent mechanism through which social media news consumption cultivates opinion polarization, contrary to the mainstreaming effect imparted by television. Further, WhatsApp use was found to strengthen the polarizing effect of overall social media news consumption, while YouTube use weakened the cultivation of polarization.

The paper unearths how social media news consumption influences the opinion polarization of various social groups differently. The authors also find the differential effect of specific platform use. These findings have the potential to inform policymakers and developers about how to mitigate the detrimental effects of platform-based political persuasion.

This study offers significant contributions. First, the authors explain social media-induced polarization using the novel theoretical lens of cultivation. Second, the authors find that social media and television news consumption differ in their polarizing effects. Third, the authors find that while WhatsApp use amplifies the polarizing effect of social media news consumption, YouTube use weakens it.

Fake news in cyberspace has greatly interfered with national governance, economic development and cultural communication, which has greatly increased the demand for fake news detection and intervention. At present, the recognition methods based on news content all lose part of the information to varying degrees. This paper proposes a lightweight content-based detection method to achieve early identification of false information with low computation costs.

The authors' research proposes a lightweight fake news detection framework for English text, including a new textual feature extraction method, specifically mapping English text and symbols to 0–255 using American Standard Code for Information Interchange (ASCII) codes, treating the completed sequence of numbers as the values of picture pixel points and using a computer vision model to detect them. The authors also compare the authors' framework with traditional word2vec, Glove, bidirectional encoder representations from transformers (BERT) and other methods.

The authors conduct experiments on the lightweight neural networks Ghostnet and Shufflenet, and the experimental results show that the authors' proposed framework outperforms the baseline in accuracy on both lightweight networks.

The authors' method does not rely on additional information from text data and can efficiently perform the fake news detection task with less computational resource consumption. In addition, the feature extraction method of this framework is relatively new and enlightening for text content-based classification detection, which can detect fake news in time at the early stage of fake news propagation.

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.

This study investigates the media activities of firms issuing private equity placements and seasoned equity offerings in Taiwan, as firms have incentives to manage media coverage to influence their stock prices during private equity placement.

We collect a corpus of news stories and transform the news into term sets based on the part of speech. Then, we refer to Cecchini et al. (2010) to classify the news terms into positive, negative, and usual categories. Next, we employ the SVM algorithm to perform the classification tasks and the term frequency method to perform the text mining task. In last, we use a multiple regression model to verify the hypotheses.

We determine that issuing firms in a private placement have substantially more positive news stories and fewer negative news stories than those in public offerings. Furthermore, we evidence that the media management effects of postequity issues are more active than those of preequity issues. Finally, our results demonstrate that the timing and content of financial media coverage among different equity issuance methods may be biased by firm management. According to previous studies, they may attempt to manipulate stock prices to increase the number of highly profitable insider stakeholders.

To our knowledge, this is the first study to investigate that if private placement will associate with more active media management than the public offerings. According to our results of the difference-in-means test, the public offerings market may control news coverage; however, this result is inconsistent with that of the regression results. The private placements market may also exercise media management in the “before announcement day” and “after announcement day” periods by increasing positive news and reducing negative news.

The dissemination of misleading and false information through media can jeopardize a company’s reputation, thus posing a threat to its stock and performance. Institutional investors are known to influence capital markets. Therefore, this paper investigates whether institutional investors engage in shaping the media sentiment stock nexus, stabilize company stocks and enhance performance.

We first investigate the effect of media sentiment on market reactions by using panel regression models. To examine the role of institutional investors, we design a quasi-experiment by exploiting the Financial Crisis of 2008 and go further by examining the heterogeneity across levels of institutional ownership. Due to risk-averse, investors may respond asymmetrically to pessimistic and positive sentiment. Accordingly, we split the sample into two sub-types, good news and bad news, based on keywords representing positive or negative content.

We find supportive evidence that institutional investors have impacts on how the markets react to media news, and the impacts are heterogeneous in the face of bad and good news. We conjecture that institutional investors act as a stabilizer of stock prices through media sentiment management.

This paper confirms the distinctive effects of institutional investors on capital markets, and uncovers the behind-the-scenes intervention and possible causal link running from institutional investors to media sentiment management. It contributes to the broad field of institutional investors' behavior, media news involvement in capital markets and market efficiency.

Most new media research focuses on behavior as a measure of engagement, while the psychological state of being occupied with its content has received little attention. This study examined news engagement beyond pure action observation by exploring young people’s psychological experiences with the news.

The study carried out a digital native’s survey on 212 people (18–28 years). The focus of the survey was on understanding individuals’ engagement with online news using affective and cognitive components. The authors compared the influence of each type of engagement on youth consumption of and attitudes toward online news.

The results of the hierarchical regression analysis showed that affective engagement can be a stronger predictor of online news consumption than cognitive engagement. While affective engagement significantly predicts positive attitudes toward online news, cognitive engagement had no significant effect.

These findings suggest that “engaging the heart” is more influential than “engaging the mind” in drawing young people to the news in today’s information environment. The study thus contributes to the understanding of the cognitive and emotional focus on news content and their importance in shaping young people’s expectations of online news. The findings from this study could have broader implications for future trends in online news consumption.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

Purpose: The main purpose of the study is to understand the factors that facilitate correction behavior among individuals. In this study the authors examine the impact of self-perceived media literacy (SPML) and reflection on participants’ correction behavior.

Methods: Data for the study were collected from Amazon's MTurk using an online survey. Data were collected after a certificate of exemption was received by the Institutional Review Board in a research university in the United States (US) Qualtrics software was used to collect data. The total number of participants was 797.

Findings: The findings show that although both SPML and reflection are positively associated with rumor refutation, higher SPML alone is not enough. Reflective judgment is critical for individuals to take part in this behavior online, such that individuals with higher reflective judgment indicated that they refute rumors online, irrespective of their SPML score.

Originality: The authors tested the relationship of multiple variables with participants correction behavior. Although research shows the importance of social correction, there is not much knowledge about what facilitates actual misinformation correction.

Taking advantage of distinctive text-based measures of climate policy uncertainty and firm-specific exposure to climate change, this study aims to examine the impact of firm-specific vulnerability on dividend policy.

To mitigate endogeneity, the authors apply an instrumental-variable analysis based on climate policy uncertainty as well as use additional analysis using propensity score matching and entropy balancing.

The authors show that an increase in climate policy uncertainty exacerbates firm-specific exposure considerably. Exploiting climate policy uncertainty to generate exogenous variation in firm-specific exposure, the authors demonstrate that companies more susceptible to climate change are significantly less likely to pay dividends and those that do pay dividends pay significantly smaller dividends. For instance, a rise in firm-specific exposure by one standard deviation weakens the propensity to pay dividends by 5.11%. Climate policy uncertainty originates at the national level, beyond the control of individual firms and is thus plausibly exogenous, making endogeneity less likely.

To the best of the authors’ knowledge, this study is the first attempt in the literature to investigate the effect of firm-specific exposure on dividend policy using a rigorous empirical framework that is less vulnerable to endogeneity and is more likely to show a causal influence, rather than a mere correlation.

Misperceptions hinder our ability to effectively respond to health crises such as the COVID-19. We aimed to examine the dynamic influences between information exposure, information trust and misperceptions during the early phase of the COVID-19 pandemic. Specifically, we focused on the relative influence of exposure to COVID-19-related information via social media versus interpersonal offline communication.

The current study conducted a two-wave national survey of US adults in May and June of 2020 with a two-week time interval. A professional polling firm recruited participants, and 911 and 679 respondents participated in the first and the second wave survey, respectively. To test proposed hypotheses, researchers conducted path analyses using AMOS 27.0.

Findings show that individuals exposed to COVID-19-related information via social media are likely to hold increased misperceptions. In contrast, exposure to COVID-19-related information offline did not elicit any effects on misperceptions. The exposure to information on social media was positively associated with trust in that information, which, in turn, contributed to an increase in misperceptions. Furthermore, when examining the effects of misperception, it was found that misperceptions increased the likelihood of individuals being exposed to and having trust in COVID-19-related information on social media. The findings provide valuable insights into the role of social media as a platform where a detrimental cycle thrives, shaping the formation of misperceptions and cultivating a heightened dependence among individuals with elevated misperceptions.

The current study significantly extends the findings of prior research by examining the differential effects of social media and interpersonal communication offline on misperception and by revealing the intricate dynamics between information exposure and misperception by focusing on the role of trust. The findings emphasize the detrimental role of social media in generating a vicious information cycle. That said, seemingly superficial discussions about health crises within a social media environment rich in misinformation can contribute to fueling a self-reinforcing loop, making it challenging to effectively counteract misperceptions.