Opinion Polarization Research Articles

Rethinking political warfare in Italy: a bottom-up approach

PurposeThe purpose of this paper is to provide a brief answer to the following questions: in the arena for State and non-State actors, who and how may guarantee the balance between democracy, State and market? How can the citizens’ economic well-being be prioritized, in terms of national security?Design/methodology/approachAdapting both the link analysis approach and the order of Pierce’s inference stages, the author illustrates the state of the art, some economic indices and Italy’s need for countermeasures.FindingsStarting from the notion of “social sustainability of the political decisions,” given by the author, the paper highlights the opportunity to rethink the concept of political warfare, in view of a productive fabric characterized by both a high number of small and medium-sized enterprises and the pervasiveness of mafia-type organizations. At the end, the author shares some proposal in the fields of Public Law and Social Marketing and a broader definition of the above-mentioned concept.Originality/valueThis study shows the link between security studies, people’s perception of grey areas and polarization of opinions and wealth, giving the reader a bottom-up input to the comprehension of the contemporary complexity.

A model of opinion and propagation structure polarization in social media

The issue of polarization in online social media has been gaining attention in recent years amid the changing political landscapes of many parts of the world. Several studies empirically observed the existence of echo chambers in online social media, stimulating a slew of works that tries to model the phenomenon via opinion modeling. Here, we propose a model of opinion dynamics centered around the notion that opinion changes are invoked by news exposure. Our model comes with parameters for opinions and connection strength which are updated through news propagation. We simulate the propagation of multiple news under the model in synthetic networks and observe the evolution of the model’s parameters and the propagation structure induced. Unlike previous models, our model successfully exhibited not only polarization of opinion, but also segregated propagation structure. By analyzing the results of our simulations, we found that the formation probability of echo chambers is primarily connected to the news polarization. However, it is also affected by intolerance to dissimilar opinions and how quickly individuals update their opinions. Through simulations on Twitter networks, we found that the behavior of the model is reproducible across different network structure and sizes.

Polarizing the middle: internet exposure and public opinion

PurposeResearch on opinion polarization in the USA repeatedly finds more divergence among politically privileged groups: respondents who are college educated, politically interested, party identified or have a liberal/conservative orientation. The purpose of this paper is to examine whether their excluded counterparts can be polarized by exposure to political information on the internet.Design/methodology/approachQuantile regression and visual analysis of raw data from the online and face-to-face samples in the 2012 and 2016 American National Election Studies (n=9,563) assessed the impact of online political information on opinion polarization among ideological moderates, political Independents, respondents without a college degree, and those with low interest in politics.FindingsExposure to online political information during the survey was associated with significant polarizing shifts toward more consistent ideological positions in all four groups.Practical implicationsEngaging the middle is a social justice issue as much as a matter of political conflict, and evidence suggests that politically excluded groups use the internet to translate their own views into the language of policy opinions and popular (polarized) politics. Recommended policy interventions include information literacy programs. Further research should use experimental models and browser histories.Originality/valueCurrent research on political polarization leaves open the question of whether larger portions of the electorate are available to join the fray. This study shows that excluded publics can be polarized via exposure to online information.

RETRACTED ARTICLE: The intelligent method of public opinion polarisation modelling and simulation analysis based on multi-dimensional and multi-level evaluation

We, the Editors and Publisher of the journal Behaviour & Information Technology, have retracted the following article which was part of the Special Issue on Behaviour Monitoring and Management of Customers, People and Organizations using Deep Learning: Chunhua Ju, Jie Wang & Jiawen Shi (2020) The intelligent method of public opinion polarisation modelling and simulation analysis based on multi-dimensional and multi-level evaluation, Behaviour & Information Technology, DOI: 10.1080/0144929X.2019.1708972 After publication it came to our attention that the person named as the Guest Editor of the Special Issue was impersonated by a fraudulent entity and the articles were not reviewed fully in line with the journal’s peer review standards and policy. We did not find any evidence of misconduct by the authors. However, in order to ensure full assessment has been conducted, we sought expert advice on the validity and quality of the published articles from independent peer reviewers. Following this post publication peer review, the editor has determined that the articles do not meet the required scholarly standards to remain published in the journal, and therefore has taken the decision to retract the articles. The authors have been informed of this decision. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted articles will remain online to maintain the scholarly record, but they will be digitally watermarked on each page as ‘Retracted’.

An implicit opinion analysis model based on feature-based implicit opinion patterns

With the rapid growth of social networks, mining customer opinions based on online reviews is crucial to understand consumer needs. Due to the richness of language expressions, customer opinions are often expressed implicitly. However, previous studies usually focus on mining explicit opinions to understand consumer needs. In this paper, we propose a novel implicit opinion analysis model to perform implicit opinion analysis of Chinese customer reviews at both the feature and review levels. First, we extract an implicit-opinionated review/clause dataset from raw review dataset and introduce the concept of the feature-based implicit opinion pattern (FBIOP). Secondly, we develop a clustering algorithm to construct product feature categories. Based on the constructed feature categories, FBIOPs can be mined from the extracted implicit-opinionated clause dataset. Thirdly, the sentiment intensity and polarity of each FBIOP are calculated by using the Chi squared test and pointwise mutual information. Fourthly, according to the resulting FBIOP polarities, the polarities of implicit opinions can be determined at both the feature and review levels. Car forum reviews written in Chinese are collected and labeled as the experimental dataset. The results show that the proposed model outperforms the traditional support vector machine model and the cutting-edge convolutional neural network model.

Role of voting intention in public opinion polarization.

We introduce and study a simple model for the dynamics of voting intention in a population of agents that have to choose between two candidates. The level of indecision of a given agent is modeled by its propensity to vote for one of the two alternatives, represented by a variable p∈[0,1]. When an agent i interacts with another agent j with propensity p_{j}, then i either increases its propensity p_{i} by h with probability P_{ij}=ωp_{i}+(1-ω)p_{j}, or decreases p_{i} by h with probability 1-P_{ij}, where h is a fixed step. We assume that the interactions form a complete graph, where each agent can interact with any other agent. We analyze the system by a rate equation approach and contrast the results with Monte Carlo simulations. We find that the dynamics of propensities depends on the weight ω that an agent assigns to its own propensity. When all the weight is assigned to the interacting partner (ω=0), agents' propensities are quickly driven to one of the extreme values p=0 or p=1, until an extremist absorbing consensus is achieved. However, for ω>0 the system first reaches a quasistationary state of symmetric polarization where the distribution of propensities has the shape of an inverted Gaussian with a minimum at the center p=1/2 and two maxima at the extreme values p=0,1, until the symmetry is broken and the system is driven to an extremist consensus. A linear stability analysis shows that the lifetime of the polarized state, estimated by the mean consensus time τ, diverges as τ∼(1-ω)^{-2}lnN when ω approaches 1, where N is the system size. Finally, a continuous approximation allows us to derive a transport equation whose convection term is compatible with a drift of particles from the center toward the extremes.

Psychological and Ethnocultural Sensitivities in the Perception of COVID-19 Memes by Young People in Russia and China

Background. The COVID-19 pandemic has brought dramatic changes to all spheres of life. These changes have triggered an immediate response from the media, including social media, which repeatedly posts not only up-to-date information about this most relevant issue, but also users’ reactions to it, including Internet memes. Objective. The research presented in this article focused on comparing the psychological and ethnocultural sensitivities in the perception of COVID-19memes by young people in Russia and China. Design. The selected sample contained 108 respondents (n = 108), comprised of 50 Chinese and 58 Russian university students. The study consisted of two procedures: a survey and a student’s t-test on the perception of specific Internet memes. Results. The main results were that memes which evoke a positive response from the respondents and cheer them up were scored the highest. Such qualities as relevance, kindness, cheerfulness, creativity, meaningfulness, and thought-provoking ability were rated high. Each group of respondents gave a higher score to “our own” memes and a lower score to the other group’s memes. It is generally typical of the Chinese to have a more positive perception of reality. We ascertained a tendency towards polarization of opinions and focus on individualization among the Russian respondents, whereas the Chinese respondents strove for orderliness and consensus. Conclusion. As a whole, COVID-19 memes in such ethnoculturally different audiences as the Russians and Chinese serve a compensatory function for young people, helping them overcome the hardships of the pandemic through the memes’ relevance and creative character.

Opinion Polarization in a Parliamentary Democracy Generates Extreme Legislation

Opinion Polarization in a Parliamentary Democracy Generates Extreme Legislation

Sentiment Classification Using a Single-Layered BiLSTM Model

This study presents a computationally efficient deep learning model for binary sentiment classification, which aims to decide the sentiment polarity of people's opinions, attitudes, and emotions expressed in written text. To achieve this, we exploited three widely practiced datasets based on public opinions about movies. We utilized merely one bidirectional long short-term memory (BiLSTM) layer along with a global pooling mechanism and achieved an accuracy of 80.500%, 85.780%, and 90.585% on MR, SST2 and IMDb datasets, respectively. We concluded that the performance metrics of our proposed approach are competitive with the recently published models, having comparatively complex architectures. Also, it is inferred that the proposed single-layered BiLSTM based architecture is computationally efficient and can be recommended for real-time applications in the field of sentiment analysis.

Squeezed Out? The Liberal Democrats and the 2019 General Election

AbstractThe 2019 general election was a crushing disappointment for the Liberal Democrats, as Jo Swinson lost her East Dunbartonshire seat to the SNP and the party’s anti‐Brexit stance failed to deliver gains from the Conservatives. Although the Liberal Democrats’ poor performance can partly be blamed on a misfiring campaign strategy, it also reflected the structural difficulties which the party faces in an increasingly polarised political environment. The polarisation of public opinion along multiple axes over the last decade—over austerity, Brexit, and attitudes to Jeremy Corbyn—has fractured the broad coalition of support which the Liberal Democrats assembled during the 1990s and 2000s. Analysis of the 2019 results suggest that the party has made some progress towards developing a new core vote, particularly among suburban Remainers in south east England, but it is not clear whether this will be large or robust enough to have a significant impact on the future of British politics.

SOCIAL REPRESENTATIONS ABOUT HOMOSEXUALITY AMONG DIFFERENT GENERATIONS OF MODERN RUSSIANS

Relevance. The problem of homosexuality is constantly in the spotlight of the mass media, social media and politicians. Psychological studies of this phenomenon are easier to find in foreign rather than in Russian research. At the same time the cultural and national specificity of attitudes towards the phenomenon of homosexuality seems obvious as well as a significant polarization of opinions within society itself. This polarization can be gender, urban, class, and intergenerational, as evidenced by numerous sociological polls. With significant attention to this issue at the level of social strata, there are not many attempts to analyze the concept of homosexuality in line with the socio-psychological tradition. In a number of previous studies it was revealed that the modern Z Gen is distinguished by greater tolerance and freedom of views in terms of attitude towards traditionally segregated social groups. The purpose of this study was to identify perceptions of homosexuality among different generations of modern Russians. Homosexuality has been singled out among other sexual orientations (LGBT) as the most discussed in public discourse. The subject of the research is social perceptions of homosexuality, particularly among representatives of different generations. Methods. The methodological basis of the research was the study of the structure of social perceptions (metho P. Vergesse method). The research methods were the author’s questionnaire aimed at identifying perceptions of homosexuality as well as a modified version of the RAHI questionnaire (Gulevich et al., 2016). The study sample consisted of 444 people (residents of the Russian Federation,16 to 65 years old). Results and Conclusions. The hypotheses of the study were confirmed: an inverse relationship between age (belonging to a generational cohort) and perceptions of homosexuality as normative was revealed. A significant difference was shown in the Z Gen perceptions in terms of tolerance of homosexuality. The so-called double standards were identified in terms of attitudes towards male and female homosexuality. The rooted concept of homosexuality as a relationship based on a sexual rather than a romantic-spiritual level, was stated.

Algorithm for Detecting Opinion Polarity in Laptop and Restaurant Domains

Abstract Knowing the state of public opinion regarding a product, the reputation of a celebrity or the assessment of a political candidate is very useful in today’s world. For example, in the particular case of a company, analyzing the opinions of its customers is very beneficial, since it allows to know the disconformities and, from these, to define new strategies that guarantee to obtain a greater degree of satisfaction in the users, as well as a greater success within the market. This article aims to develop a method for classifying the polarity of product aspects.

Sentimental Analysis of Twitter Data with respect to General Elections in India

Abstract It is known that social media is one of the largest sources of unstructured data. Analyzing that data and harvesting meaning out of that is a tedious job. Recently opinion mining has become an emerging topic due to the vast amount of opinioned data available on the various social networking sites. Microblogging has appeared relatively recently, and twitter is the most popular microblogging sites used by the people. It is one of the biggest free, open data-source. In the world today, twitter often witnesses a lot of opinions. Opinion mining and sentiment analysis help researchers to gain insight into public emotions. In this paper, Twitter is used as a source of opinioned data. Twitter APIs are used for the collection of tweets. In this paper, R is used for the acquisition, pre- processing, analyzing the tweets, then sentiment analysis is performed based on the different approaches. In this paper, Tweets were collected from the period of Jan 2019 to March 2019. Using that tweets, sentiment analysis was performed to gain the opinion polarity of the folks concerning general elections held in India. Two candidates were considered for this study: Candidate-1 and Candidate-2. It was concluded that Candidate-1 is more liked and is famous as compared to Candidate-2. The result obtained in our paper was in full compliance with the actual election results obtained in May 2019.

Weakly Supervised Framework for Aspect-Based Sentiment Analysis on Students’ Reviews of MOOCs

Students’ feedback is an effective mechanism that provides valuable insights about teaching-learning process. Handling opinions of students expressed in reviews is a quite labour-intensive and tedious task as it is typically performed manually by the human intervention. While this task may be viable for small-scale courses that involve just a few students’ feedback, it is unpractical for large-scale cases as it applies to online courses in general, and MOOCs, in particular. Therefore, to address this issue, we propose in this paper a framework to automatically analyzing opinions of students expressed in reviews. Specifically, the framework relies on aspect-level sentiment analysis and aims to automatically identify sentiment or opinion polarity expressed towards a given aspect related to the MOOC. The proposed framework takes advantage of weakly supervised annotation of MOOC-related aspects and propagates the weak supervision signal to effectively identify the aspect categories discussed in the unlabeled students’ reviews. Consequently, it significantly reduces the need for manually annotated data which is the main bottleneck for all deep learning techniques. A large-scale real-world education dataset containing around 105k students’ reviews collected from Coursera and a dataset comprising of 5989 students’ feedback in traditional classroom settings are used to perform experiments. The experimental results indicate that our proposed framework attains inspiring performance with respect to both the aspect category identification and the aspect sentiment classification. Moreover, the results suggest that the framework leads to more accurate results than the expensive and labour-intensive sentiment analysis techniques relying heavily on manually labelled data.

Modelling public opinion polarisation process considering the influence of initial viewpoint and interaction mode

As an important media, there is often a polarisation of the internet group triggered by hot social topics, and the emotions of netizens will react on the society. These effects are sometimes positive or negative, so it is urgent to conduct in-depth research and study. Behind the polarisation phenomenon is the change of people's attitude towards events, such as convergence, alienation and neutrality. Considering the priority possession theory, this paper focuses on the influence of initial attitude on the evolutionary process. On the basis of J-A model (proposed by Jager and Amblard), the influence function of the initial viewpoint is added, and the computer simulation experiment is carried out and the concrete example is taken for empirical analysis.

Modelling public opinion polarisation process considering the influence of initial viewpoint and interaction mode

As an important media, there is often a polarisation of the internet group triggered by hot social topics, and the emotions of netizens will react on the society. These effects are sometimes positive or negative, so it is urgent to conduct in-depth research and study. Behind the polarisation phenomenon is the change of people's attitude towards events, such as convergence, alienation and neutrality. Considering the priority possession theory, this paper focuses on the influence of initial attitude on the evolutionary process. On the basis of J-A model (proposed by Jager and Amblard), the influence function of the initial viewpoint is added, and the computer simulation experiment is carried out and the concrete example is taken for empirical analysis.

Does socioeconomic status moderate the political divide on climate change? The roles of education, income, and individualism

Previous research documents that U.S. conservatives, and conservative white males in particular, tend to dismiss the threat of climate change more than others in the U.S. public. Other research indicates that higher education and income can each exacerbate the dismissive tendencies of the political Right. Bridging these lines of research, the present study examines the extent to which higher education and/or income moderate the ideological divide and the “conservative white male effect” on several climate change opinions, and whether these effects are mediated by an individualistic worldview (e.g., valuing individual liberty and limited government). Using nationally representative survey data of U.S. adults from 2008 to 2017 (N = 20,024), we find that across all beliefs, risk perceptions, and policy preferences examined, the ideological divide strengthens with both higher education and higher income. However, educational attainment plays a stronger role than income in polarizing the views of conservative white males. Further analyses support the hypothesis that differences in individualism partially explain the increased political polarization among more educated and higher-income adults, as well as greater dismissiveness among conservative white males relative to other demographic groups. These results highlight key moderators of opinion polarization, as well as ideological differences among conservatives, that are often overlooked in public discourse about climate change. Implications for climate change education and communication across demographic groups are considered.

Polarised Security: How do Chinese Netizens Respond to the Securitisation of Terrorism?

ABSTRACTThe heightened securitisation of Islamic terrorism has received significant attention in Western countries, but little is known about the extent to which netizens in centralised political systems such as China have responded to this threat. This article seeks to address this gap by examining the localisation of the globalised fear of terrorism in China. It analyses online posts about international terrorism that appeared on Sina Weibo in China between 2011 and 2016, and shows how the opinions about terrorism expressed in the Chinese digital media sphere are strongly polarised. We argue that in China’s online sphere the localisation of the “war on terror” frame generates two key polarised public responses – “negotiated acceptance” and “negative re-utilisation” – and that this polarisation of opinions about terrorism stems, in part, from China’s stability-oriented approach to managing terrorism. These findings point to both an acceptance of and a resistance to the securitisation of terrorism and the globalised fear that it (re)produces. Moreover, the findings offer insights into the extent to which local security concerns and beliefs in the Chinese political system can create a divergence between the local perspectives on terrorism and the Western experiences and practices of security labelling.

Exposure to the IPCC special report on 1.5 °C global warming is linked to perceived threat and increased concern about climate change

This article investigates the influence of exposure to the IPCC special report on 1.5 °C global warming on climate change attitudes. Among a nationally representative sample of the Norwegian public, we found that exposure to the report is associated with greater perceived threat from climate change and increased climate change concern. However, this association was modestly moderated by political orientation. Exposure to the report had a weaker association with perceived threat and climate change concern among politically right-leaning individuals, compared with their left-leaning counterparts, and there was no association between exposure to the report and climate change concern among individuals who self-identified as being on the far-right end of the political spectrum. We conclude that, despite the commonly observed tendency for biased assimilation of climate change information and polarisation of opinion among the public, scientific communication regarding climate risks may still have a viable role to play in promoting climate change engagement and action.

The development of partisan polarization over the Green New Deal

In early 2019, a US climate change and economic renewal policy proposal called the Green New Deal (GND)1 rose from obscurity to national prominence in just four months. This situation created a natural field experiment in which to study the emergence of partisan polarization. Here, we report findings from two nationally representative surveys of registered US voters that measured familiarity with and support for the GND shortly before and after the issue entered the national spotlight. Initially, there was low public awareness of the GND but majority support for it across party lines. Four months later, voters had become much more familiar with the GND and partisan polarization had increased significantly due to a sharp decrease in support among Republicans. In fact, Republicans who had heard the most about the GND were the least likely to support it. In contrast, support for the GND remained high among Democrats, and did not vary substantially across degrees of familiarity. We also identify a likely mechanism: a ‘Fox News effect’. That is, among Republicans, Fox News viewing was a significant predictor of both familiarity with the GND and opposition to it, even when controlling for alternative explanations. Opinions on climate policy in the United States are politically polarized. Here, survey research shows that opinion polarization on the Green New Deal developed rapidly due to decreasing support among Republicans, which was associated with exposure to conservative media and increasing familiarity with the policy.