Is Twitter a Public Sphere for Online Conflicts? A Cross-Ideological and Cross-Hierarchical Look

The rise in popularity of Twitter has led to a debate on its impact on public opinions. The optimists foresee an increase in online participation and democratization due to social media's personal and interactive nature. Cyber-pessimists, on the other hand, explain how social media can lead to selective exposure and can be used as a disguise for those in power to disseminate biased information. To investigate this debate empirically, we evaluate Twitter as a public sphere using four metrics: equality, diversity, reciprocity and quality. Using these measurements, we analyze the communication patterns between individuals of different hierarchical levels and ideologies. We do this within the context of three diverse conflicts: Israel-Palestine, US Democrats-Republicans, and FC Barcelona-Real Madrid. In all cases, we collect data around a central pair of Twitter accounts representing the two main parties. Our results show in a quantitative manner that Twitter is not an ideal public sphere for democratic conversations and that hierarchical effects are part of the reason why it is not.Comment: To appear in the 6th International Conference on Social Informatics (SocInfo 2014), Barcelon

On Online Collaboration and Construction of Shared Knowledge: Assessing Mediation Capability in Computer Supported Argument Visualization Tools

Collaborative Computer-Supported Argument Visualization (CCSAV) has often been proposed as an alternative over more conventional, mainstream platforms for online discussion (e.g., online forums and wikis). CCSAV tools require users to contribute to the creation of a joint artifact (argument map) instead of contributing to a conversation. In this paper we assess empirically the effects of this fundamental design choice and show that the absence of conversational affordances and socially salient information in representation-centric tools is detrimental to the users' collaboration experience. We report empirical findings from a study in which subjects using different collaborative platforms (a forum, an argumentation platform, and a socially augmented argumentation tool) were asked to discuss and predict the price of a commodity. By comparing users' experience across several metrics we found evidence that the collaborative performance decreases gradually when we remove conversational interaction and other types of socially salient information. We interpret these findings through theories developed in conversational analysis (common ground theory) and communities of practice and discuss design implications. In particular, we propose balancing the trade-off between knowledge reification and participation in representation-centric tools with the provision of social feedback and functionalities supporting meaning negotiation

Social determinants of content selection in the age of (mis)information

Despite the enthusiastic rhetoric about the so called \emph{collective intelligence}, conspiracy theories -- e.g. global warming induced by chemtrails or the link between vaccines and autism -- find on the Web a natural medium for their dissemination. Users preferentially consume information according to their system of beliefs and the strife within users of opposite narratives may result in heated debates. In this work we provide a genuine example of information consumption from a sample of 1.2 million of Facebook Italian users. We show by means of a thorough quantitative analysis that information supporting different worldviews -- i.e. scientific and conspiracist news -- are consumed in a comparable way by their respective users. Moreover, we measure the effect of the exposure to 4709 evidently false information (satirical version of conspiracy theses) and to 4502 debunking memes (information aiming at contrasting unsubstantiated rumors) of the most polarized users of conspiracy claims. We find that either contrasting or teasing consumers of conspiracy narratives increases their probability to interact again with unsubstantiated rumors.Comment: misinformation, collective narratives, crowd dynamics, information spreadin

Global warming and the cosmopolitan political conception of justice

Within the literature in green political theory on global environmental threats one can often find dissatisfaction with liberal theories of justice. This is true even though liberal cosmopolitans regularly point to global environmental problems as one reason for expanding the scope of justice beyond the territorial limits of the state. One of the causes for scepticism towards liberal approaches is that many of the most notable anti-cosmopolitan theories are also advanced by liberals. In this paper, I first explain why one of the strongest expressions of liberal anti-cosmopolitanism cannot simply be dismissed because it may fail to support desired environmental ends. The political conception of justice represents one of the most important challenges to cosmopolitanism generally and is thus a serious challenge to viewing global environmental problems in terms of cosmopolitan justice. Second, I will show through the case of anthropogenic global warming that the political conception of justice under current conditions does have clear cosmopolitan implications despite its proponents' claims

Vague heuristics

Even when they are defined with precision, one can often read and hear judgments about the vagueness of heuristics in debates about heuristic reasoning. This opinion is not just frequent but also quite reasonable. In fact, during the 1990s, there was a certain controversy concerning this topic that confronted two of the leading groups in the field of heuristic reasoning research, each of whom held very different perspectives. In the present text, we will focus on two of the papers published in Psychological Review, wherein the arguments of each of these groups were presented:

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization