Policy-specific effects of transgovernmental cooperation: a statistical assessment across the EU’s post-Soviet neighbours

<p>Can transgovernmental networks facilitate democratization in third countries? If so, to what extent and under what conditions can they impact states’ behaviour? Earlier works demonstrate that transgovernmental professional networks set by the European Union can shape attitudes of officials towards democracy in third countries. However, it remains unclear whether they change their behaviour, too; nor do we have an understanding of how long these changes last. Using the time-series cross-sectional analysis and focusing on two policy fields, human rights and public administration in the former Soviet republics, this article demonstrates that transgovernmental networks can stimulate improvements in domestic practices in third countries. At the same time, the results hint that their effects are policy-specific and rather short-lived.</p

Climate change on Twitter : Implications for climate governance research

There is increasing public debate about the governance of climate change and its repercussions for nature and human livelihoods. In today's digitalized communication landscape, both public and private actors involved in climate change governance use social media to provide information and to interact with stakeholders and the broader public. This Focus Article discusses two main aspects of debates about climate change and climate governance on Twitter, which previous theories suggest to shape climate governance across domestic and global levels: non-state climate action and public opinion formation on the social media. We see significant advancement in the environmental social sciences studying these two areas. Yet, we also see the need for a better understanding of how public and private actors in the climate governance complex interact on Twitter, and how these actors shape, and are shaped by, experiences, values, and positions. This understanding will help to advance climate governance theories. This article proceeds in three steps. We first discuss previous social media research on non-state climate action and public opinion formation related to climate change and its governance. Then we sketch avenues for future research, elaborating how Twitter data might be used to investigate how non-state climate action and public opinion formation on social media are linked to and influence climate governance. We conclude by making the case for drawing together Twitter data and climate governance research into a more coherent research agenda

Short text classification with machine learning in the social sciences: The case of climate change on Twitter.

To analyse large numbers of texts, social science researchers are increasingly confronting the challenge of text classification. When manual labeling is not possible and researchers have to find automatized ways to classify texts, computer science provides a useful toolbox of machine-learning methods whose performance remains understudied in the social sciences. In this article, we compare the performance of the most widely used text classifiers by applying them to a typical research scenario in social science research: a relatively small labeled dataset with infrequent occurrence of categories of interest, which is a part of a large unlabeled dataset. As an example case, we look at Twitter communication regarding climate change, a topic of increasing scholarly interest in interdisciplinary social science research. Using a novel dataset including 5,750 tweets from various international organizations regarding the highly ambiguous concept of climate change, we evaluate the performance of methods in automatically classifying tweets based on whether they are about climate change or not. In this context, we highlight two main findings. First, supervised machine-learning methods perform better than state-of-the-art lexicons, in particular as class balance increases. Second, traditional machine-learning methods, such as logistic regression and random forest, perform similarly to sophisticated deep-learning methods, whilst requiring much less training time and computational resources. The results have important implications for the analysis of short texts in social science research

The Role of EU Agencies in the Acquis Transfer: The Case of the European Neighbourhood Policy Countries

The politics and administration of institutional chang