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Ideal point models have become a powerful tool for defining and measuring the ideology of many kinds of political actors, including legislators, judges, campaign donors, and members of the general public. We extend the application of ideal point models to the public using a novel data source: real-time reactions to statements by candidates in the 2012 presidential debates. Using these reactions as inputs to an ideal point model, we estimate individual-level ideology and evaluate the quality of the measure. Debate reaction ideal points provide a method for estimating a continuous, individual-level measure of ideology that avoids survey response biases, provides better estimates for moderates and the politically unengaged, and reflects the content of salient political discourse relevant to viewers’ attitudes and vote choices. As expected, we find that debate reaction ideal points are more extreme among respondents who strongly identify with a political party, but retain substantial within-party variation. Ideal points are also more extreme among respondents who are more politically interested. Using topical subsets of the debate statements, we find that ideal points in the sample are more moderate for foreign policy than for economic or domestic policy.

When real-time response data from viewers of a televised debate is collected via the internet, the server timestamps of the received responses may not match the correct times of the debate. This paper addresses the question of how the data could be aligned in retrospect, using an algorithm that approximates the playout delay difference between each viewer’s TV signal. The validity is shown by successfully approximating distinctive delays for viewers with satellite or cable TV.

How does political involvement impact on data quality of virtualized Real-Time-Response (RTR) Measurement? The article addresses this issue, drawing on a large field study (n = 5660) conducted during the 2017 German general election campaign. Since it is unclear how heterogeneous characteristics of individuals influence data quality of RTR-Measurement from audiences surveyed outside the lab, we assess the impact of political involvement on the reliability and validity of virtualized real-time-response data. We show that political involvement shapes reliability and validity systematically but to a degree that does not compromise established standards of data quality. Thus, we conclude that virtualized RTR outside the laboratory with limited means of control is an appropriate method to survey heterogeneous samples in large N-field studies and therefore offers new paths of data collection.

Real-time social media data hold great conceptual promise for research and policymaking, but also face substantial limitations and shortcomings inherent to processing re-purposed data in near-real-time. This paper aims to fill two research gaps important for understanding utility of real-time social media data for policymaking: What policy-relevant information is contained in this data and whether this information changes in periods of abrupt social, economic, and policy change. To do so, this paper focuses on two salient policy areas heavily affected by the lockdown policies responding to the 2020 COVID-19 crisis – early childhood education and care policies, and labor market policies focused on (un)employment. We utilize Twitter data for a four-month period during the first wave of COVID-19 and data for the same four-month period the preceding year. We analyze this data using a novel method combining structural topic models and latent semantic scaling, which allows us to summarize the data in detail and to test for change of content between the period of ‘normalcy’ and period of ‘crisis’. With regards to the first research gap, we show that there is policy-relevant information in Twitter data, but that the majority of our data is of limited relevance, and that the data that is relevant present some challenges and limitations. With regards to the second research gap, we successfully quantify the change in relevant information between periods of ‘normalcy’ and ‘crisis’. We also comment on the practicality and advantages of our approach for leveraging micro-blogging data in near real-time.

The time evolution of the response of electors to political life is analyzed for the Italian Republic over a 70-year span in which 18 political elections have taken place. The basis for the performed analyses is the official data available from the Italian Ministry of Interiors exposing the results of the political elections from 1948 until 2018. The attention is concentrated on parameters providing information on the responsivity of the electors to country’s political life. These parameters, expressed in adequate percentages, are the effective number of voters and the percentage of these expressing blank or spoilt ballots. The time dependence of these parameters, over the analyzed period, shows regularities, correlations, and interesting peculiarities. The analysis concerns the results for both Chamber of Deputies and Chamber of Senators available, for each election, all along the 70-year time span that are those relative to people voting on the national territory. The results demonstrate that percentages of blank and spoilt ballots represent useful parameters to trace the responsivity of electors. Hypotheses for explaining the results obtained from the statistical analyses are presented both at technical and socio-political level.

Citizens’ exit polls are performed by local voters to verify the official reported election results. Five citizens’ exit polls were run in southeast Kansas during the Nov 8th 2016 election. These exit polls were designed specifically to verify computer generated vote counts and run solely by volunteer labor, all local citizens who were willing to put in the necessary hours on Election Day to conduct the poll and later, to count the results by hand. These exit polls were able to obtain high participation rates resulting in the ability to detect small yet statistically significant differences. All five polling stations surveyed show evidence of multiple statistical anomalies in both the pattern and size of the errors between the official results and exit poll results although biases were not uniformly oriented across sites. The small discrepancies found in the studied races were insufficient to alter the outcomes. Non-response bias and unintentional errors were evaluated as potential causes; those explanations were plausible in some but not all cases. These results show a pattern of discrepancies between the exit polls and computer counted results displaying consistent bias within sites. This would be an expected outcome of a deliberate manipulation of the computer results. While this data doesn’t conclusively prove election interference and manipulation of votes counts, it should be taken seriously as a sign of such interference. Doubts about the accuracy of the reported results are appropriate unless other plausible explanations for the discrepancies can be found.

Voluntary assessments by a team of critical friends (external peer challenges) among local governments became established as popular complement to compulsory and centralized audits and inspections. This study empirically investigates the decision of English local authorities to have a voluntary peer challenge or not by taking advantage of an original dataset about participation in the Local Government Association’s Peer Challenge Programme (CPC) 2010–2015. We find that the LGA’s CPC programme does not carry a risk of leaving behind authorities with performance shortcomings. Councils with poor past performance scores and those with excellent ones do not differ in their tendency to invite a team of critical friends. Spatial clusters exist in the case of small district councils but not in the case of larger unitary authorities, London boroughs and metropolitan authorities. This implies that the corporate peer challenge process seems to be more suited to small authorities delivering community based services.