Economic voting in a crisis: The Irish election of 2011

The paper explores a question raised by the 2011 Irish election, which saw an almost unprecedented decline in support for a major governing party after an economic collapse that necessitated an ECB/IMF ‘bailout’. This seems a classic case of ‘economic voting’ in which a government is punished for incompetent performance. How did the government lose this support: gradually, as successive economic indicators appeared negative, or dramatically, following major shocks? The evidence points to losses at two critical junctures. This is consistent with an interpretation of the link between economics and politics that allows for qualitative judgements by voters in assigning credit and blame for economic performance.     

Improving public services by mining citizen feedback: An application of natural language processing

Research on user satisfaction has increased substantially in recent years. To date, most studies have tested the significance of predefined factors thought to influence user satisfaction, with no scalable means of verifying the validity of their assumptions. Digital technology has created new methods of collecting user feedback where service users post comments. As topic models can analyse large volumes of feedback, they have been proposed as a feasible approach to aggregating user opinions. This novel approach has been applied to process reviews of primary care practices in England. Findings from an analysis of more than 200,000 reviews show that the quality of interactions with staff and bureaucratic exigencies are the key drivers of user satisfaction. In addition, patient satisfaction is strongly influenced by factors that are not measured by state-of-the-art patient surveys. These results highlight the potential benefits of text mining and machine learning for public administration.     

How to scale coded text units without bias: A response to Gemenis

Coding non-manifesto documents as if they were genuine policy platforms produced at election time clearly raises serious issues with error when these codings are used in the standard manner to estimate left-right policy positions. In addition to the long term solution of improving the document base of the Manifesto Project identified by Gemenis (2012), we argue that immediate gains in manifesto-based estimates of policy positions can be realised by using the confrontational logit scales from Lowe et al. (2011), which addresses the problems of scale content and scale construction that are exacerbated by but not unique to the problems found in proxy documents.     

Illicit payments for illicit goods: noncontact drug distribution on Russian online drug marketplaces

The distribution or consumption of traditional drugs has become the subject of stringent penalties throughout most of the world and synthetic designer drugs have become the alternative. Novel psychoactive substances, also called ‘legal highs’, are highly varied in terms of chemical composition. These substances are advertised and distributed as an alternative to traditional drugs on the Internet, making identification of new substances and enforcement difficult. For this article, we downloaded and analysed 28 Russian-language online drug marketplaces which distribute traditional and novel psychoactive substances. All marketplaces used a noncontact drug dealing method where the seller and the buyer communicate through the Internet to arrange for payment and delivery of drugs without meeting face-to-face. Geographic information, price, amount, substance type and payment method data were extracted. Findings indicate such marketplaces are able to operate due to the ability of their clients to pay anonymously with the virtual currencies – Qiwi and Bitcoin.     

Reading the Tea Leaves: Medvedev's Presidency through Political Rhetoric of Federal and Sub-National Actors

In the absence of public information on the inner workings of the Russian political regime, especially during Medvedev's presidency, outside observers often have to rely on politicians' unguarded comments or subjective analysis. Instead, we turn to quantitative text analysis of political rhetoric. Treating governors as a quasi-expert panel, we argue that policy positions revealed in regional legislative addresses explain how elites perceived the distribution of power between Putin and Medvedev. We find that governors moved from a neutral position in 2009 to a clearly pro-Putin position in 2011, and that policy initiatives advocated by Medvedev all but evaporated from the rhetoric of governors in 2012.     

Treating Words as Data with Error: Uncertainty in Text Statements of Policy Positions

Political text offers extraordinary potential as a source of information about the policy positions of political actors. Despite recent advances in computational text analysis, human interpretative coding of text remains an important source of text-based data, ultimately required to validate more automatic techniques. The profession's main source of cross-national, time-series data on party policy positions comes from the human interpretative coding of party manifestos by the Comparative Manifesto Project (CMP). Despite widespread use of these data, the uncertainty associated with each point estimate has never been available, undermining the value of the dataset as a scientific resource. We propose a remedy. First, we characterize processes by which CMP data are generated. These include inherently stochastic processes of text authorship, as well as of the parsing and coding of observed text by humans. Second, we simulate these error-generating processes by bootstrapping analyses of coded quasi-sentences. This allows us to estimate precise levels of nonsystematic error for every category and scale reported by the CMP for its entire set of 3,000-plus manifestos. Using our estimates of these errors, we show how to correct biased inferences, in recent prominently published work, derived from statistical analyses of error-contaminated CMP data.