Giuseppe Alessandro Veltri

Imagining nanotechnology: cultural support for technological innovation in Europe and the United States

This paper compares public perceptions of technologies in the United States and Europe. Asked whether nanotechnology will improve our way of life, 50 percent of the US sample say “yes” and 35 percent say “don’t know.” The European figures are almost the mirror image, 29 percent saying “yes” and 53 percent saying “don’t know.” People in the US are also more optimistic than Europeans about eight more familiar technologies. We suggest that people in the US assimilate nanotechnology within a set of pro-technology cultural values. By contrast, in Europe there is more concern about the impact of technology on the environment, less commitment to economic progress and less confidence in regulation. These differences in values are reflected in media coverage, with more emphasis on the potential benefits of nanotechnology in the US than in the UK. Finally, we speculate on possible futures for the reception of nanotechnology in the US and Europe.

Automated analysis of the US presidential elections using Big Data and network analysis

The automated parsing of 130,213 news articles about the 2012 US presidential elections produces a network formed by the key political actors and issues, which were linked by relations of support and opposition. The nodes are formed by noun phrases and links by verbs, directly expressing the action of one node upon the other. This network is studied by applying insights from several theories and techniques, and by combining existing tools in an innovative way, including: graph partitioning, centrality, assortativity, hierarchy and structural balance. The analysis yields various patterns. First, we observe that the fundamental split between the Republican and Democrat camps can be easily detected by network partitioning, which provides a strong validation check of the approach adopted, as well as a sound way to assign actors and topics to one of the two camps. Second, we identify the most central nodes of the political camps. We also learnt that Clinton played a more central role than Biden in the Democrat camp; the overall campaign was much focused on economy and rights; the Republican Party (Grand Old Party or GOP) is the most divisive subject in the campaign, and is portrayed more negatively than the Democrats; and, overall, the media reported positive statements more frequently for the Democrats than the Republicans. This is the first study in which political positions are automatically extracted and derived from a very large corpus of online news, generating a network that goes well beyond traditional word-association networks by means of richer linguistic analysis of texts.

Worldviews and discursive construction of GMO-related risk perceptions in Turkey

This paper analyses the discursive construction of the genetically modified organisms (GMOs) issue in the Turkish political arena following the public debate on the pending legislation on biosecurity. The study proposes an operational approach to semiotic/actor network theory (Latour) applied to public representations of a new technology within the theoretical frameworks of social representation theory and cultural theory of risks. It aims to highlight how different worldviews produce different risk discourses of GMOs in Turkey. Using cluster analysis to inductively extract evaluative categories, we use these to identify themes by human coding. Lastly, we apply formal concept analysis to link themes to actors and their worldviews, establishing their semantic networks. Formal concept analysis revealed four discourse networks reflecting nationalist, Islamist, progressive (left) and neo-liberal worldviews. Finally, these structures will be grounded back in the articles for a richer interpretive analysis.

Pathos & ethos: emotions and willingness to pay for tobacco products

In this article we use data from a multi-country Randomized Control Trial study on the effect of anti-tobacco pictorial warnings on an individual’s emotions and behavior. By exploiting the exogenous variations of images as an instrument, we are able to identify the effect of emotional responses. We use a range of outcome variables, from cognitive (risk perception and depth of processing) to behavioural (willingness to buy and willingness to pay). Our findings suggest that the odds of buying a tobacco product can be reduced by 80% if the negative affect elicited by the images increases by one standard deviation. More importantly from a public policy perspective, not all emotions behave alike, as eliciting shame, anger, or distress proves more effective in reducing smoking than fear and disgust. JEL Classification C26, C99, D03, I18 PsycINFO classification 2360; 3920

On the coverage of science in the media: A big data study on the impact of the Fukushima disaster

The contents of English-language online-news over 5 years have been analyzed to explore the impact of the Fukushima disaster on the media coverage of nuclear power. This big data study, based on millions of news articles, involves the extraction of narrative networks, association networks, and sentiment time series. The key finding is that media attitude towards nuclear power has significantly changed in the wake of the Fukushima disaster, in terms of sentiment and in terms of framing, showing a long lasting effect that does not appear to recover before the end of the period covered by this study. In particular, we find that the media discourse has shifted from one of public debate about nuclear power as a viable option for energy supply needs to a re-emergence of the public views of nuclear power and the risks associated with it. The methodology used presents an opportunity to leverage big data for corpus analysis and opens up new possibilities in social scientific research.

The challenges and opportunities of ‘nudging’

Consider the following selective evidence of human behaviour in the domain of healthcare. The numeric-cognition feeds typically provided during public vaccination campaigns are less effective than affect-based perception of risk.1 It is common to avoid seeing doctors and/or doing health checks because of anxiety and fear of receiving bad results. The latter means that a perceived ‘loss today’ in the health status has a stronger impact than a ‘gain tomorrow’, namely preventing or curing a potential disease.2 Clinicians fail to act on available knowledge and guidelines despite the intention to do so.3nnInstead, consider now the following couple of examples of choice architectures capable of offsetting erroneous conducts. Recent trial studies show that it is enough to change the default settings of electronic order sets to dramatically ‘improve’ clinicians prescribing behaviours.4 A lottery-based financial incentive increased warfarin adherence and anticoagulation control.5nnWhat do these examples have in common? They exemplify the heuristics and biases and the counteracting ‘nudges’ that in the past decade have been presented as part of a behavioural sciences-dictated policy agenda. Altering prescription activities by changing defaults in electronic order sets, for instance, is just a very simple example of a ‘nudge’ leveraging the ‘status quo bias’ to steer clinicians toward a ‘normatively’ defined ‘better’ behaviour. This is achieved by framing the choice set without restricting available options, in other words, acting over presentation of the decision problem, and not on the constraints for the decision maker. This philosophy of policy intervention has been labelled ‘libertarian paternalism’ because by not affecting the options available in the choice set it can be deemed to be libertarian from a consequentialist point of view, while being paternalistic in the sense of trying to induce ‘better’ choices.6nnThe approach is grounded in behavioural economics (BE), …

Climate change on Twitter: Content, media ecology and information sharing behaviour.

This article presents a study of the content, use of sources and information sharing about climate change analysing over 60,000 tweets collected using a random week sample. We discuss the potential for studying Twitter as a communicative space that is rich in different types of information and presents both new challenges and opportunities. Our analysis combines automatic thematic analysis, semantic network analysis and text classification according to psychological process categories. We also consider the media ecology of tweets and the external web links that users shared. In terms of content, the network of topics uncovered presents a multidimensional discourse that accounts for complex causal links between climate change and its consequences. The media ecology analysis revealed a narrow set of sources with a major role played by traditional media and that emotionally arousing text was more likely to be shared.

The impact of different forms of cognitive scarcity on online privacy disclosure

The way in which people manage information disclosure contributes to one of the biggest challenges of the information age online privacy. The current study sheds a light on the privacy paradox, a gap between attitudes and behaviour, by exploring the role of cognitive scarcity in privacy disclosure behaviour. Using a large sample of the UK online general population (N=969), we conducted a Randomised Controlled Trial experiment to test the effect of two forms of induced cognitive scarcity: ego depletion and working memory load, on information disclosure levels. Results indicate a significant effect of both forms of scarcity on information disclosure in the direction of increasing the latter, even in the context of a generalised high disclosure. Findings are discussed in light of the privacy paradox, future research, possible remedies and interventions. This study explores the influence of cognity scarcity on information disclosure.We test the effects of two forms of cognitive scarcity.Both ego depletion and working memory load have an effect on information disclosure.Both cognitive scarcities leads to more information disclosure behaviour.

Big Data is not only about data: The two cultures of modelling

The contribution of Big Data to social science is not limited to data availability but includes the introduction of analytical approaches that have been developed in computer science, and in particular in machine learning. This brings about a new ‘culture’ of statistical modelling that bears considerable potential for the social scientist. This argument is illustrated with a brief discussion of model-based recursive partitioning which can bridge the theory and data-driven approach. Such a method is an example of how this new approach can help revise models that work for the full dataset: it can be used for evaluating different models, a traditional weakness of the ‘traditional’ statistical approach used in social science.

Symbolic universes between present and future of Europe: First results of the map of European societies’ cultural milieu

This paper reports the framework, method and main findings of an analysis of cultural milieus in 4 European countries (Estonia, Greece, Italy, and UK). The analysis is based on a questionnaire applied to a sample built through a two-step procedure of post-hoc random selection from a broader dataset based on an online survey. Responses to the questionnaire were subjected to multidimensional analysis–a combination of Multiple Correspondence Analysis and Cluster Analysis. We identified 5 symbolic universes, that correspond to basic, embodied, affect-laden, generalized worldviews. People in this study see the world as either a) an ordered universe; b) a matter of interpersonal bond; c) a caring society; d) consisting of a niche of belongingness; e) a hostile place (others’ world). These symbolic universes were also interpreted as semiotic capital: they reflect the capacity of a place to foster social and civic development. Moreover, the distribution of the symbolic universes, and therefore social and civic engagement, is demonstrated to be variable across the 4 countries in the analysis. Finally, we develop a retrospective reconstruction of the distribution of symbolic universes as well as the interplay between their current state and past, present and future socio-institutional scenarios.