Populist Twitter Posts in News Stories

Research in information processing suggests that the journalistic practice of embedding right-wing populist Twitter posts in news may stimulate political polarization. To test this notion, we conducted an online experiment (N = 379). We investigated how highlighted right-wing populist statements affected individuals from different ideological stances and whether potential effects were determined by Twitter-specific characteristics (Twitter frame, profile picture). We exposed participants to two articles, each including a statement by a politician of the Austrian Freedom Party. In the first group, the statements were not highlighted (control group). In the second and third group, the statements appeared as conventional block quotes either without (G2) or with (G3) a picture of the politician. In the fourth and fifth group, the statements were highlighted as Twitter posts, again either without (G4) or with (G5) a picture of the politician. Results revealed that all highlighting conditions increased statement recognition among left-wing individuals. However, the full Twitter post condition exerted the strongest effect. Higher recognition then decreased left-wing individuals’ anti-immigrant attitudes and sympathy toward the right-wing populist candidate. Thus, embedding right-wing populists’ Twitter posts may induce disconfirmation bias among left-wing voters and trigger a process in which they strengthen their initial attitudes.© 2019 The Author(s

A Meta-Analysis of the Effects of Cross-Cutting Exposure on Political Participation

Scholars have advanced many theoretical explanations for expecting a negative or positive relationship between individuals’ cross-cutting exposure—either through interpersonal or mediated forms of communication—and their political participation. However, whether cross-cutting exposure is a positive or negative predictor of participation is still an unsettled question. To help fill this gap, we conducted a meta-analysis of 48 empirical studies comprising more than 70,000 participants examining the association between cross-cutting exposure and political participation. The meta-analysis produced two main findings. First, it shows that, over all studies, there is no significant relationship, r = .002, Zr = .002 (95% CI = −.04 to .05). Second, the null relationship cannot be explained by variations in the characteristics of cross-cutting environments (e.g., topic, place, or source of exposure), participation outcomes (e.g., online vs. offline activities), or methods employed (e.g., experiment vs. survey). Taken together, these results should alleviate concerns about negative effects of cross-cutting exposure on political engagement. Implications for future research are discussed.© 2019 The Author(s

Metadata record for: The Scales Project, a cross-national dataset on the interpretation of thermal perception scales

This dataset contains key characteristics about the data described in the Data Descriptor The Scales Project, a cross-national dataset on the interpretation of thermal perception scales. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata

Metadata record for: The Scales Project, a cross-national dataset on the interpretation of thermal perception scales

This dataset contains key characteristics about the data described in the Data Descriptor The Scales Project, a cross-national dataset on the interpretation of thermal perception scales. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format Versioning Note:Version 2 was generated when the metadata format was updated from JSON to JSON-LD. This was an automatic process that changed only the format, not the contents, of the metadata

Data from: Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

AbstractThe idea that noncrop habitat enhances pest control and represents a win–win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win–win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies