Search results

Following Hovland’s persuasion theory, this paper aims to develop a conceptual model and analyzes characteristics of online political deliberation behavior from three aspects (i.e. information, situation and manager). Based on the whole interactive process of online political deliberation, this paper aims to reveal the key points that affect the response effect of the government from the persuasive perspective of online political consultation.

Based on more than 40,000 netizens’ posts and government responses from 2011 to the first half of 2019 of the Chinese political platform, this paper used the text analysis and machine learning methods to extract measurement variables of online political deliberation characteristics and the econometrics analysis method to conduct empirical research.

The results showed that the textual information, political environment and identity of the political objects affect the effectiveness of government response. Furthermore, for different position categories of political officials, the length of political texts, topic categories and emotional tendencies have different effects on the response effectiveness. Additionally, the effect of political time on the effectiveness of response differs.

The findings will help ascertain the characteristics of online political deliberation behavior that affect how effective government response is and provide a theoretical basis for why the public should express their political concerns.

Corporations are confronted with growing demands to take a stand on socio-political issues, i.e. corporate social advocacy (CSA), which affects their reputation in the public. Companies use different CSA message strategies, including calling the public to support and act on the issue they advocate. Using reactance theory, the authors investigate the impact of CSA messages with a call to action on corporate reputation in the case of a company's gender equality initiative.

A one-factorial (CSA message with or without a call to action) between-subjects experiment was conducted by surveying 172 individuals living in Switzerland. The CSA messages were created in the context of gender equality.

The authors' study indicates that CSA messages with a call to action compared to those without overall harmed corporate reputation due to individuals' reactance, which is higher for CSA messages with a call to action, negatively affecting corporate reputation. The impact of the CSA message strategy with a call to action on corporate reputation remains significant after controlling for issue alignment and political leaning.

Communicating about socio-political issues, especially taking a stand, is a significant challenge for corporations in an increasingly polarized society and has often led to backlash, boycotts and damage to corporate reputation. This study shows that the possible adverse effects of advocating for socio-political issues can be related to reactance. It emphasizes that companies advocating for contested issues must be more cautious about the message strategy than the issue itself.

This study aims to examine brand personality and its application to political branding. This study focuses on the brand personality of a political leader from the BJP Party brand (Bharatiya Janta Party). The development of a strong political brand personality is crucial for success at the polls. Little research has been dedicated to this phenomenon particularly beyond Western political and post-election contexts.

The scope and development of the study required a qualitative approach. The theoretical frameworks of the study acted as the deductive base of the study. The insights of the respondents were the inductive base of the study. Semi-structured interviews were conducted with external stakeholders [voters]. In addition, semi-structured interviews were also adopted to capture the branding activities used by internal stakeholders [BJP].

The brand personality dimensions such as sincerity; agreeableness, competence, energy, openness, conscientiousness and emotional stability were clearly associated with a political leader. Negative qualities such as dictatorial attitudes and arrogance affected the political leader’s brand personality. Religious partisanship was another strong negative trait affecting the brand personality of the political leader.

The study has an actionable framework for political brand personality in the post-election context. It offers negative qualities to be avoided in the development of the political brand personality of the leader. It offers insights about the political brand personality of the leader in terms of young digitally savvy voters.

Este trabajo examina la aplicación de la personalidad de marca al ámbito del marketing político y de la marca personal política. Concretamente se centra en la personalidad de marca de un líder político del partido Bharantiya Janta Party (BJP). El desarrollo de una fuerte marca personal política es crucial para el éxito en las elecciones. Pocos trabajos se han centrado hasta el momento en este fenómeno más allá del contexto político occidental.

El alcance y desarrollo del estudio requirió la adopción de un enfoque cualitativo. El marco teórico sirvió de base deductiva al tiempo que las entrevistas realizadas sirvieron de base inductiva. Estas entrevistas fueron semi-estructuradas y dirigidas a grupos de interés externos del BJP (los votantes). Además, se realizaron entrevistas también semi-estructuradas para capturar las actividades de marca desarrolladas por los grupos de interés internos (candidatos, políticos, trabajadores y gerentes del partido).

Las dimensiones de personalidad de marca sinceridad, competencia, energía, estabilidad emocional, franqueza y escrupulosidad están claramente asociadas con un líder político. Por el contrario, rasgos negativos como las actitudes arrogantes y dictatoriales dañan la personalidad de marca de dicho líder, pero sobretodo el partidismo religioso.

El trabajo proporciona un marco de acción para la marca personal política en un contexto post-electoral. Proporciona indicaciones de los rasgos y cualidades negativas que deben de evitarse en el desarrollo de una marca personal para un líder político. Ofrece también evidencias sobre la personalidad de marca que tiene que desarrollar un líder de cara a los votantes más dinámicos y digitales.

The purpose of this paper is to investigate practices of argumentation on Twitter discussions about climate change.

Conversational threads were collected from the Twitter API. Fundamental concepts from argumentation theory and linking practices were operationalised through a coding schema for content analysis. Tweets were analysed in the context of the discussions and coded according to their argumentative approach, interaction type and argumentation stage. Linked and embedded sources were analysed in order to find how they were used in arguments, the plausibility and soundness of the message, the consistency and trustworthiness of the linked source and its adequacy with the target audience.

Among the interactions between arguers, this study found five typical practices and several patterns involving the dynamics of the conversations, the strategy of the argumentation and the linking practices. Although the rhetorical approach was prominent, the agreement was rarely achieved. The arguers used a variety of sources to justify or support their positions, often embedding non-textual content. These linking practices, together with the strategy adopted and the topics discussed, suggest the involvement of a multiple audience engaged in discussing ad lib scientific artefacts, topics and outputs.

While Twitter has been the focus for many research papers, the conversational threads have been given little attention so far. With the Twitter API making conversations more accessible for research, this paper does not only give insight into multiple audience group argumentation dynamics but also provides a method to study the conversations from an argumentation theory perspective.

There are many ways for young people to get involved with their communities, but Community participation is one of the most important ways. As a way of expressing their commitment, young people form political and social action groups, devise educational initiatives tailored to their interests, and serve as community activists. This study was carried out in Myanmar prior to the military takeover in 2021. A military coup protest was organized by CEC (Chief Executive Committees). In addition, the majority of the committee members advocate for democratic values in this era. For the purpose of this study, researchers looked into which factors had the greatest impact on the participation of youth affairs committee members in their communities. Mon State was chosen as the study site because the median age of the population there is 26.7 years old. The 2014 Census revealed a range of median ages that is lower than this one. It shows that the median age of Mon state's youth affairs committee members is lower than the state's overall median age. In addition, the state of Mon was home to three major ethnicities: the Mon, the Kayan, and the Burmese. This situation demonstrates that young people have settled in Mon state with a wide range of viewpoints and ideas. The 131 members of Mon state's youth affairs committee were selected from each of the state's three levels of youth affairs committee. The data collected was analyzed using linear regression and descriptive methods. It was discovered that the community involvement of young leaders is positively influenced by social, political & legal factors.

The purpose of this paper is the better understanding of the increasing relation between big data 2.0 and neuromarketing, particularly to influence election outcomes, along with a special aim to discuss some raised doubts about Trump’s presidential campaign 2016 and its ability to hijack American political consumers’ minds, and to direct their votes.

This paper combines deductive/inductive methodology to define the term of political neuromarketing 2.0 through a brief literature review of related concepts of big data 2.0, virtual identity and neuromarketing. It then applies a single qualitative case study by presenting the history and causes of online voter microtargeting in the USA, and analyzing the political neuromarketing 2.0 mechanisms adopted by Trump’s political campaign team in the 2016 presidential election.

Based on Trump’s political marketing mechanisms analysis, the paper believes that big data 2.0 and neuromarketing techniques played an unusual role in reading political consumers’ minds and helping the controversial candidate to meet one of the most unexpected victories in the presidential elections. Nevertheless, this paper argues that the ethics of using political neuromarketing 2.0 to sell candidates and its negative impacts on the quality of democracy are and will continue to be a subject of ongoing debates.

The marriage of big data 2.0 and political neuromarketing is a new interdisciplinary field of inquiry. This paper provides a useful introduction and further explanations for why and how Trump’s campaign defied initial loss predictions and attained victory during this election.

Since the end of 2016, “fake news” has had a clear meaning in the USA. After years of scholarship attempting to define “fake news” and where it fits among the larger schema of media hoaxing and deception, popular culture and even academic studies converged following the 2016 US presidential election to define “fake news” in drastically new ways. The paper aims to discuss these issues.

In light of the recent elections in the USA, many fear “fake news” that have gradually become a powerful and sinister force, both in the news media environment as well as in the fair and free elections. The scenario draws into questions how the general public interacts with such outlets, and to what extent and in which ways individual responsibility should govern the interactions with social media.

Fake news is a growing threat to democratic elections in the USA and other democracies by relentless targeting of hyper-partisan views, which play to the fears and prejudices of people, in order to influence their voting plans and their behavior.

Essentially, “fake news” is changing and even distorting how political campaigns are run, ultimately calling into question legitimacy of elections, elected officials and governments. Scholarship has increasingly confirmed social media as an enabler of “fake news,” and continues to project its potentially negative impact on democracy, furthering the already existing practices of partisan selective exposure, as well as heightening the need for individual responsibility.

Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

A total of 1,022 individuals took part in the survey; participants were asked to fill out the ten item personality measure questionnaire to capture personality traits and the dysfunctional attitude scale (DAS) to measure dysfunctional beliefs and cognitive vulnerabilities. ML classification models using participant profiling information as input were developed to predict the extent to which an individual was influenced by statements that contained different linguistic styles/persuasion techniques. Several ML algorithms were used including support vector machine, LightGBM and Auto-Sklearn to predict the effect of each technique given each individual’s profile (personality, belief system and demographic data).

The findings highlight the importance of incorporating emotion-based variables as model input in predicting the influence of textual statements with embedded persuasion techniques. Across all investigated models, the influence effect could be predicted with an accuracy ranging 53%–70%, indicating the importance of testing multiple ML algorithms in the development of a persuasive communication (PC) system. The classification ability of models was highest when predicting the response to statements using rhetorical devices and flattery persuasion techniques. Contrastingly, techniques such as authority or social proof were less predictable. Adding DAS scale features improved model performance, suggesting they may be important in modelling persuasion.

In this study, the survey was limited to English-speaking countries and largely Western society values. More work is needed to ascertain the efficacy of models for other populations, cultures and languages. Most PC efforts are targeted at groups such as users, clients, shoppers and voters with this study in the communication context of education – further research is required to explore the capability of predictive ML models in other contexts. Finally, long self-reported psychological questionnaires may not be suitable for real-world deployment and could be subject to bias, thus a simpler method needs to be devised to gather user profile data such as using a subset of the most predictive features.

The findings of this study indicate that leveraging richer profiling data in conjunction with ML approaches may assist in the development of enhanced persuasive systems. There are many applications such as online apps, digital advertising, recommendation systems, chatbots and e-commerce platforms which can benefit from integrating persuasion communication systems that tailor messaging to the individual – potentially translating into higher economic returns.

This study integrates sets of features that have heretofore not been used together in developing ML-based predictive models of PC. DAS scale data, which relate to dysfunctional beliefs and cognitive vulnerabilities, were assessed for their importance in identifying effective persuasion techniques. Additionally, the work compares a range of persuasion techniques that thus far have only been studied separately. This study also demonstrates the application of various ML methods in predicting the influence of linguistic styles/persuasion techniques within textual statements and show that a robust methodology comparing a range of ML algorithms is important in the discovery of a performant model.

This article examines the effect of China's soft power projection through the Chinese media in Africa on the African audiences' perception of China's national image through a case study of the residents of Nairobi. It adopted Joseph Nye's soft power model and sought to address three fundamental questions : What is the extent and objective of China's media diplomacy in Africa? How has China's media “offensive” in Africa impacted African audiences' imagery of China? What are the implications, if any, of China's media diplomacy on the Kenyan public view of China?

This article used a mixed-methods research design, which deployed elements of positivism and interpretivism. It used a deductive approach and deployed the survey strategy, which entailed the collection of data from Nairobi city residents. The secondary data were collected from relevant academic literature sources. The primary data were analyzed empirically using the Statistical Package for the Social Sciences (SPSS), while the secondary data were analyzed using discourse analysis.

China's soft power projection through the Chinese media in Africa is aimed at addressing the “misinformation” about China. China seeks its share of representation among the African public to correct negative perceptions of China. Kenyans had a generally positive attitude toward China. South Africa and Angola have “Fairly” positive perceptions of the Chinese media. However, this study did not reveal whether the perception was due to the influence of Chinese media. These findings implied that the African public's positive imagery of China cannot be fully attributed to Chinese media's influence.

This study is groundbreaking in that it is one of the few studies that have focused on China's public diplomacy in Africa and assessed the impact of Chinese media on the African public’s perception of China.

This study aims to understand, from the analysis of the work of a Brazilian network of non-governmental organizations (NGOs), how advocacy on human rights issues is developed to defend causes before the legislative branch, identifying its contributions and effectiveness. For this, were observed, the strategies and tactics employed in the implementation of two advocacy campaigns promoted by a Brazilian NGOs network.

The research adopts the method of inductive investigation with a qualitative approach and uses the techniques of semi-structured in-depth interviews and documentary research. The paper is developed within the scientific field of public relations (PR), uses as reference the critical theory and the rhetorical theory of PR, and is based on the concept of advocacy.

Some results of the advocacy are observed, such as the greater awareness of political decision-makers, in addition to the influence on the definition of the political agenda and on the action of the political decision-makers.

Among the limitations of this study are the time span for analyzing the campaigns' actions, which could be extended to observe long-term results, as well as the dedication of the study exclusively to the legislative branch since the campaigns also sought to influence decision-making in the executive branch.

The results found encourage the strengthening of the democratic environment since it increases the power and influence of civil society in the political decision-making of the legislative branch.

The study showed that advocacy, as a PR activity, increases civil society participation in political decisions.