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The purpose of this paper is to study the impact of the 2016 presidential election polls on the stock market.

The empirical model includes daily stock returns as the dependent variable and past asset prices, 10-year treasury rates, opinion polls and VIX (market uncertainty) as explanatory variables with a one-year lag. The model was estimated using two sets of daily polling data: from July 1, 2015, to November 8, 2016, and from June 1, 2016, to November 8, 2016. Additional descriptive statistics, such as means and standard deviations, were also calculated.

The estimated results did not reveal any statistically significant effects of opinion polls in favor of one candidate over another on stock returns. Simple statistical tests, however, show that the market performed better when Trump held a polling advantage over Clinton.

To the best of the authors’ knowledge, this is the only study that has examined the effects of the 2016 presidential election polls on the US stock market. This study adds value to the understanding of the relationship between election polls and the stock market in the USA.

Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media.

For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance.

The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts.

Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.

Misinformation is notoriously difficult to combat. Although social media firms have focused on combating the publication of misinformation, misinformation accusations, an important by-product of the spread of misinformation, have been neglected. The authors offer insights into factors contributing to the spread of misinformation accusations on social media platforms.

The authors use a corpus of 234,556 tweets about the 2020 US presidential election (Study 1) and 99,032 tweets about the 2022 US midterm elections (Study 2) to show how the sharing of misinformation accusations is explained by locomotion orientation.

The study findings indicate that the sharing of misinformation accusations is explained by writers' lower locomotion orientation, which is amplified among liberal tweet writers.

Practitioners and policymakers can use the study findings to track and reduce the spread of misinformation accusations by developing algorithms to analyze the language of posts. A limitation of this research is that it focuses on political misinformation accusations. Future research in different contexts, such as vaccines, would be pertinent.

The authors show how social media firms can identify messages containing misinformation accusations with the potential to become viral by considering the tweet writer's locomotion language and geographical data.

Early identification of messages containing misinformation accusations can help to improve the quality of the political conversation and electoral decision-making.

Strategies used by social media platforms to identify misinformation lack scale and perform poorly, making it important for social media platforms to manage misinformation accusations in an effort to retain trust. The authors identify linguistic and geographical factors that drive misinformation accusation retweets.

Given inconsistent results in prior studies, this paper applies the dual process theory to investigate what social media messages yield audience engagement during a political event. It tests how affective cues (emotional valence, intensity and collective self-representation) and cognitive cues (insight, causation, certainty and discrepancy) contribute to public engagement.

The authors created a dataset of more than three million tweets during the 2020 United States (US) presidential elections. Affective and cognitive cues were assessed via sentiment analysis. The hypotheses were tested in negative binomial regressions. The authors also scrutinized a subsample of far-famed Twitter users. The final dataset, scraping code, preprocessing and analysis are available in an open repository.

The authors found the prominence of both affective and cognitive cues. For the overall sample, negativity bias was registered, and the tweet’s emotionality was negatively related to engagement. In contrast, in the sub-sample of tweets from famous users, emotionally charged content produced higher engagement. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with many followers. Collective self-representation (“we-talk”) is consistently associated with more likes, comments and retweets in the overall sample and subsamples.

The authors expand the dominating one-sided perspective to social media message processing focused on the peripheral route and hence affective cues. Leaning on the dual process theory, the authors shed light on the effectiveness of both affective (peripheral route) and cognitive (central route) cues on information appeal and dissemination on Twitter during a political event. The popularity of the tweet’s author moderates these relationships.

Social media has become an indispensable part of modern politics. Its rise in the political arena has coincided with the decline in trust toward mainstream media. Today, more than half of the population gets their political news and information through social media platforms like Twitter and Facebook. Social media offers a great marketing opportunity to politicians as they allow them to bypass traditional media and communicate directly with voters, engage citizens during campaign and noncampaign periods, and create a brand image. As social media's influence in politics grows, so has the research devoted to political marketing on social media. It is against this backdrop that this chapter is written, which provides readers with an overview of the academic domain and the current state of literature. The chapter highlights the various research areas that have been explored in the literature and the implications of social media for political marketing strategy, along with the domain's current limitations and possible avenues of further research.

Drawing on moral foundations theory (MFT), this paper aims to examine the relationship between community-level political ideology, organisational performance and leader tenure by proposing and testing an “ideology-authority hypothesis” wherein political ideology moderates the relationship between organisational performance decline and leader tenure in organisations.

The authors used archival data pertaining to the performance of teams from the National Basketball Association (NBA), the tenure of the head coaches and the voting record of the communities in which the teams are located. The authors used hierarchical linear modelling (HLM) to test the relationships among these variables at multiple levels.

The results provided empirical support for the “ideology-authority hypothesis”. Specifically, the magnitude of team winning percentage decrease from the previous season is positively associated with the tenure of the head coach in teams located in more conservative communities but not in teams located in more liberal communities.

This study examines leadership stability and change by highlighting the moral foundation of authority/subversion. The findings also illustrate the importance of a community-level variable – the general political climate of the community in which an organisation is embedded – in organisational decision-making.

This chapter discusses the impacts of David Maines's scholarship in communication research. The utilities of Maines's scholarship in communication research were first identified in a 1997 session in the annual convention of National Communication Association (NCA) by many leading scholars. This chapter documents the applications of Maines's scholarship in communication research in recent years when communication researchers utilized concepts and arguments constructed by Maines to investigate narratives in relations to Donald Trump's presidential election as well as the COVID-19 pendemic.

While there is research that has explored how institutions have responded to various crises, these are usually locally or regionally situated. However, no event has impacted higher education globally like COVID-19 and it will certainly alter the way top administrators lead and how institutions move forward. Thus, this chapter will explore how to better understand how presidents and top administrators navigate the (inter)national geopolitics as they move the institution forward. In addition, clear and up-to-date communication has proven to be important in battling this crisis. Thus, how presidents at national universities have communicated with students, faculty, staff, and various off-campus communities members regarding COVID-19 and how they have achieved is important to explore. Our findings suggest that presidents and top administrators need to build support to help them navigate the political roadblocks they may encounter. Findings also suggest that communication is the main role they play as leaders on their campus. On/off-campus community members see the presidents as the face of the university and key communicator as relates to communicating what the institutions is doing and how they are addressing the crisis. This chapter helps in better understanding the roles presidents and top administrators play during a global crisis.

The broader analytical framing of systematically distorted communication (SDC) helps extract value out of the enormous amount of scholarship on fake news.

The massive literature on fake news has been the subject of handbook overviews, systematic literature reviews, summaries, taxonomies, citation studies and so on. Deploying these tools, the approaches that the literature takes can be characterized, Habermas' concept of systematically distorted communication (SDC) will then be presented in its context, reviewed and put to work to frame fake news research to tell us new things that individual pieces of specific analysis and research do not. Conclusions will be offered from this analysis.

Fake news research has become repetitive, revolving around themes such as the fate of journalism, the role of technology, remediating its effects and deep dives into definitional components (disinformation, misinformation, lies and so on). A broader framing of systematically distorted communication allows us to arrive at some conclusions about contemporary fake news: that it is a power strategy with a particular right-wing slant and it creates a sociology – that is, its own interpretive environment – hostile to democratic functioning. It answers the question: what is fake news for?

A perspective on fake news research is much needed and Habermas' concept is a useful framing mechanism for the large corpus of research. Systematically distorted communication asks – and answers – different questions of the research. Meanwhile, SDC itself is modified by its application to fake news research and contemporary conditions.