Mixing Dyadic and Deliberative Opinion Dynamics in an Agent-Based Model of Group Decision-Making

International audienceIn this article, we propose an agent-based model of opinion diffusion and voting where influence among individuals and deliberation in a group are mixed. The model is inspired from social modeling, as it describes an iterative process of collective decision-making that repeats a series of interindividual influences and collective deliberation steps, and studies the evolution of opinions and decisions in a group. It also aims at founding a comprehensive model to describe collective decision-making as a combination of two different paradigms: argumentation theory and ABM-influence models, which are not obvious to combine as a formal link between them is required. In our model, we find that deliberation, through the exchange of arguments, reduces the variance of opinions and the proportion of extremists in a population as long as not too much deliberation takes place in the decision processes. Additionally, if we define the correct collective decisions in the system in terms of the arguments that should be accepted, allowing for more deliberation favors convergence towards the correct decisions

Argumentation Stance Polarity and Intensity Prediction and its Application for Argumentation Polarization Modeling and Diverse Social Connection Recommendation

Cyber argumentation platforms implement theoretical argumentation structures that promote higher quality argumentation and allow for informative analysis of the discussions. Dr. Liu’s research group has designed and implemented a unique platform called the Intelligent Cyber Argumentation System (ICAS). ICAS structures its discussions into a weighted cyber argumentation graph, which describes the relationships between the different users, their posts in a discussion, the discussion topic, and the various subtopics in a discussion. This platform is unique as it encodes online discussions into weighted cyber argumentation graphs based on the user’s stances toward one another’s arguments and ideas. The resulting weighted cyber argumentation graphs can then be used by various analytical models to measure aspects of the discussion. In prior work, many aspects of cyber argumentation have been modeled and analyzed using these stance relationships. However, many challenging problems remain in cyber argumentation. In this dissertation, I address three of these problems: 1) modeling and measure argumentation polarization in cyber argumentation discussions, 2) encouraging diverse social networks and preventing echo chambers by injecting ideological diversity into social connection recommendations, and 3) developing a predictive model to predict the stance polarity and intensity relationships between posts in online discussions, allowing discussions from outside of the ICAS platform to be encoded as weighted cyber argumentation graphs and be analyzed by the cyber argumentation models. In this dissertation, I present models to measure polarization in online argumentation discussions, prevent polarizing echo-chambers and diversifying users’ social networks ideologically, and allow online discussions from outside of the ICAS environment to be analyzed using the previous models from this dissertation and the prior work from various researchers on the ICAS system. This work serves to progress the field of cyber argumentation by introducing a new analytical model for measuring argumentation polarization and developing a novel method of encouraging ideological diversity into social connection recommendations. The argumentation polarization model is the first of its kind to look specifically at the polarization among the users contained within a single discussion in cyber argumentation. Likewise, the diversity enhanced social connection recommendation re-ranking method is also the first of its kind to introduce ideological diversity into social connections. The former model will allow stakeholders and moderators to monitor and respond to argumentation polarization detected in online discussions in cyber argumentation. The latter method will help prevent network-level social polarization by encouraging social connections among users who differ in terms of ideological beliefs. This work also serves as an initial step to expanding cyber argumentation research into the broader online deliberation field. The stance polarity and intensity prediction model presented in this dissertation is the first step in allowing discussions from various online platforms to be encoded into weighted cyber argumentation graphs by predicting the stance weights between users’ posts. These resulting predicted weighted cyber augmentation graphs could then be used to apply cyber argumentation models and methods to these online discussions from popular online discussion platforms, such as Twitter and Reddit, opening many new possibilities for cyber argumentation research in the future

Critical Discourse Analysis of Iranian Presidents’ Addresses to the United Nations General Assembly (2007-2016)

Critical Discourse Analysis studies of communication in political contexts have scrutinized the use of language by politicians striving to win public opinion and votes. Utilizing Teun A. van Dijk’s framework for political discourse analysis, this thesis examines linguistic features in eight addresses of Iranian Presidents, Hassan Rouhani and Mahmoud Ahmadinejad, to the United Nations General Assembly. The study described in this thesis combines micro-level text analysis (following 25 discursive devices introduced by Van Dijk, 2005) with a macro-analysis focusing on the dichotomy of ‘positive self-representation’ and ‘negative other-representation.’ The data analysis demonstrates that President Rouhani made more use of the discursive devices ‘consensus’, ‘illustration’, ‘hyperbole’ and ‘polarization’, whereas President Ahmadinejad employed more frequently ‘lexicalization’ and ‘vagueness’. The comparison of the speeches by two presidents at macro-level shows that Rouhani relied more on ‘positive self-representation’ and Ahmadinejad on ‘negative other-representation’. The results of the study also show that the two presidents convey different viewpoints on most topics covered in the eight UNGA addresses although their ideological stances on a few topics, such as world Zionism and the occupation of Palestine, seem quite similar

Reason Against the Machine: Future Directions for Mass Online Deliberation

Designers of online deliberative platforms aim to counter the degrading quality of online debates. Support technologies such as machine learning and natural language processing open avenues for widening the circle of people involved in deliberation, moving from small groups to "crowd" scale. Numerous design features of large-scale online discussion systems allow larger numbers of people to discuss shared problems, enhance critical thinking, and formulate solutions. We review the transdisciplinary literature on the design of digital mass deliberation platforms and examine the commonly featured design aspects (e.g., argumentation support, automated facilitation, and gamification) that attempt to facilitate scaling up. We find that the literature is largely focused on developing technical fixes for scaling up deliberation, but may neglect the more nuanced requirements of high quality deliberation. Current design research is carried out with a small, atypical segment of the world's population, and much research is still needed on how to facilitate and accommodate different genders or cultures in deliberation, how to deal with the implications of pre-existing social inequalities, how to build motivation and self-efficacy in certain groups, and how to deal with differences in cognitive abilities and cultural or linguistic differences. Few studies bridge disciplines between deliberative theory, design and engineering. As a result, scaling up deliberation will likely advance in separate systemic siloes. We make design and process recommendations to correct this course and suggest avenues for future researchComment: Adjusting title and abstract to arxiv metadat

A Graph-Based Context-Aware Model to Understand Online Conversations

Online forums that allow for participatory engagement between users have been transformative for the public discussion of many important issues. However, such conversations can sometimes escalate into full-blown exchanges of hate and misinformation. Existing approaches in natural language processing (NLP), such as deep learning models for classification tasks, use as inputs only a single comment or a pair of comments depending upon whether the task concerns the inference of properties of the individual comments or the replies between pairs of comments, respectively. But in online conversations, comments and replies may be based on external context beyond the immediately relevant information that is input to the model. Therefore, being aware of the conversations' surrounding contexts should improve the model's performance for the inference task at hand. We propose GraphNLI, a novel graph-based deep learning architecture that uses graph walks to incorporate the wider context of a conversation in a principled manner. Specifically, a graph walk starts from a given comment and samples "nearby" comments in the same or parallel conversation threads, which results in additional embeddings that are aggregated together with the initial comment's embedding. We then use these enriched embeddings for downstream NLP prediction tasks that are important for online conversations. We evaluate GraphNLI on two such tasks - polarity prediction and misogynistic hate speech detection - and found that our model consistently outperforms all relevant baselines for both tasks. Specifically, GraphNLI with a biased root-seeking random walk performs with a macro-F1 score of 3 and 6 percentage points better than the best-performing BERT-based baselines for the polarity prediction and hate speech detection tasks, respectively.Comment: 25 pages, 9 figures. arXiv admin note: text overlap with arXiv:2202.0817

Ideological distinction. The political ideologies of social psychologists in the East and West.

The problem of “liberal bias” among personality and social psychologists has been widely discussed in recent years (Haidt, 2011; Duarte et al., in press; Inbar, Lammers, 2012). Most of these discussions extrapolated findings observed in American and Western European social psychology to the whole discipline. This article presents a first insight into regional differences in the political opinions of Western, and Eastern social psychologists. Based on the characteristics of intellectuals in Eastern European countries as reproducers of existing structures of dependence, we hypothesised that Eastern European psychologists would not express a “liberal bias” but instead, at least in the domain of economic opinions, that they would support rather conservative political solutions. An empirical study of social psychologists from Hungary, Poland, the USA and the UK supported this hypothesis. Furthermore, it was demonstrated that, despite forming the majority in the field of social psychology, Polish supporters of a free market economy were reluctant to express their views in public. Finally, based on the European Values Survey, we compared the economic attitudes of European social psychologists with the attitudes prevalent in their countries (i.e. Hungary, Poland and the UK). This comparison suggested that Hungarian and Polish social psychologists hold more procapitalist stances on economic issues than the poorest segments of the societies they live in, whereas British social psychologists supported state interventionism to a greater extent than the poorest sections of their society

The dialogic turn: dialogue for deliberation

Much of current debate on deliberative democracy verses on the difficulty of bridging the gap between normative theory and practical development. This article argues that, in order to bridge that gap and facilitate deliberative scenarios, more attention must be paid to the sociological core of deliberative democracy, namely, interpersonal communication. Dialogue scholarship has gained momentum over the past decade, offering a way forward in terms of enlarging the concept of deliberation while enriching its processes. This article proposes some reflections towards an integrated model of dialogue and deliberation (D+D) for collaborative policy making scenarios. The purpose is to explore, from a pragmatic and post-empiricist orientation, this particular crossroads of political science and communication scholarship.div_MCaPA4pub1379pub

Myside Bias Shifting in the Written Arguments of First Year Composition Students

This dissertation reports on research conducted to better understand how college student writers learned to work against their own biases as they researched and wrote arguments. I conducted a review of former studies to design a curriculum that would help students avoid bias and increase their ability to write arguments tailored to specific readers in ways that accomplish their goals. This review also informed the kinds of data to be collected and analyzed in order to accomplish the research goal, which was to understand whether and how each of seven students enrolled in a composition course reduced their biases. I collected written arguments, drawings, and classroom discussions of these students and administered surveys, and participants underwent interviews, to study the effect of the curriculum and instruction. This dissertation reports findings on how each student writer’s bias shifted differently over the course of the semester, and the role identity played in bias shifting. Results include the observation that the curriculum was effective at reducing bias in student arguments, though to various degrees and for differing reasons, based on a variety of contextual factors. Unlike experimental studies of bias, this study provides rich details about seven individual students’ experiences in a course designed to reduce bias. Implications include researched evidence upon which teachers, administrators, curriculum designers, and policymakers may base future decisions upon regarding the teaching of argumentation