The baloti.ch project shows the difficulties in engaging the disenfranchised in the political process using e-participation apps

Can a society be peaceful, prosperous, and happy when 25% of the population lack political rights on the national level? Uwe Serdült thinks not, and helped build an app to provide informal voting rights using an e-participation app for use in Swiss referendums. Although the app wasn’t a resounding success, it did provide an opportunity for disenfranchised people to participate in the national political process for the first time

Were the Brits Swiss, they would still have voted to leave

On the referendum day these were last minute decisions that most probably turned the tide in favour of the Leave camp. In this article Thomas Milic and Uwe Serdült draw up an analogy of the June 23rd vote between the referendum votes on the EU that took place in Switzerland over the past couple of years. They argue that would the Brits be Swiss, they would have voted for an exit as well

From Alibaba to Youtube: User Search for Digital Democracy Topics in Switzerland

Digital Democracy tools such as e-consultation, e-petitions or internet voting play an increasing role and are part of the digitalisation process in politics and government. Digital life styles in general and during the pandemic in particular might have pushed for an increasing demand for so called civic tech tools. Digital democracy search terms were monitored across multiple digital channels for several months in the year 2021 and contrasted to the offer for such tools in the German, French and Italian speaking part of the country. To measure the offer for digital participation tools an index per canton established in 2021 is being used

Soziale Netzwerkanalyse: eine Methode zur Untersuchung von Beziehungen zwischen sozialen Akteuren

'Dieser Überblicksartikel über die Anwendungsmöglichkeiten der Sozialen Netzwerkanalyse im Bereich der Politikwissenschaft besteht aus drei Teilen. In einem kurzen Einstieg sollen die verschiedenen Dimensionen des Netzwerkbegriffs gegeneinander abgegrenzt werden. Im Artikel geht es explizit um die Soziale Netzwerkanalyse als quantitative Methode. Ein kurzer historischer Abriss und die Erörterung der wichtigsten Prinzipien der Sozialen Netzwerkanalyse runden diesen Teil ab. Der ausführliche zweite Teil soll einen Einblick in zwei wichtige Forschungsstränge und dazugehörige empirische Studien bieten. Als erstes wird die Verwendung von netzwerkanalytischen Massen und Verfahren anhand eines inter-organisatorischen Politiknetzwerkes illustriert. Für PolitikwissenschaftlerInnen, die sich für Wahl- und Abstimmungsforschung interessieren, sind insbesondere ego-zentrierte Netzwerke eine weitere Einsatzmöglichkeit der vorgestellten Methode. In einem dritten Teil werden kurz die momentan laufenden methodischen Weiterentwicklungen der Sozialen Netzwerkanalyse präsentiert. Einerseits gibt es Versuche, Veränderungen über die Zeit untersuchen zu können; andererseits sind Modelle entwickelt worden, die es erlauben, relationale und attributive Daten simultan auszuwerten.' (Autorenreferat)'This overview of possible applications of Social Network Analysis in the realm of political science consists of there parts. A short introduction clarifies the different dimensions of the concept of network. This article explicitly deals with Social Network Analysis as a quantitative method. A short history and an introduction of the most important principles of Social Network Analysis round off this part. The second, more detailed part provides an insight into two important strands of research and related empirical studies. First, there is an illustration of how network measurements and methods can be applied to data relating to an inter-organizational policy network. Second, for political scientists interested in election and voting studies, ego-centered networks represent a variant of the above method. The third part briefly presents ongoing methodological developments in Social Network Analysis. On one hand, there are attempts at investigating changes of networks over time; on the other hand, most recent models permit the simultaneous analysis of relational and attributive data.' (author's abstract

Ideological and Temporal Components of Network Polarization in Online Political Participatory Media

Political polarization is traditionally analyzed through the ideological stances of groups and parties, but it also has a behavioral component that manifests in the interactions between individuals. We present an empirical analysis of the digital traces of politicians in politnetz.ch, a Swiss online platform focused on political activity, in which politicians interact by creating support links, comments, and likes. We analyze network polarization as the level of intra- party cohesion with respect to inter-party connectivity, finding that supports show a very strongly polarized structure with respect to party alignment. The analysis of this multiplex network shows that each layer of interaction contains relevant information, where comment groups follow topics related to Swiss politics. Our analysis reveals that polarization in the layer of likes evolves in time, increasing close to the federal elections of 2011. Furthermore, we analyze the internal social network of each party through metrics related to hierarchical structures, information efficiency, and social resilience. Our results suggest that the online social structure of a party is related to its ideology, and reveal that the degree of connectivity across two parties increases when they are close in the ideological space of a multi-party system.Comment: 35 pages, 11 figures, Internet, Policy & Politics Conference, University of Oxford, Oxford, UK, 25-26 September 201

Introducing the DigiPart-Index

Digital political participation increasingly complements analogue forms of political participation. Elements of the political process such as dialogue, consultation, participation as well as voting have received a further digital boost in the COVID-19 pandemic. Because they reflect the new digital experiences of ever broader sections of the population, using digital means to participate in the political process will play an increasingly important role in the future. The DigiPart-Index (DPI) measures three dimensions of digital political participation for all cantons in Switzerland. The first dimension reflects how political decision-making in democracies is preceded by an opinion-formation phase. It covers tools for e-deliberation, digital political education and e-transparency. The second dimension, co-creation, maps the exchange between government agencies and civil society. The two components, e-consultation and e-demand, are surveyed for this purpose. Thirdly, in addition to public debate and an exchange between the state and society, digital tools can also be used to enable the act of voting. To this end, the foundations must be laid in the form of electronic identification, i.e. an e-ID, so that it can then be used for e-voting and e-collecting, among other things. The values for the DigiPart-Index Switzerland range from 0 to 100 points. Results show that the differences between the cantons are considerable, ranging from a minimum of 6 to a maximum of 55 points. The mean value is 31 points. The ranking tends to be led by cantons with greater financial resources. However, even the cantons at the top range of the index still have room for considerable improvement in all dimensions

Enhancing the design of voting advice applications with BERT language model

The relevance and importance of voting advice applications (VAAs) are demonstrated by their popularity among potential voters. On average, around 30% of voters take into account the recommendations of these applications during elections. The comparison between potential voters' and parties' positions is made on the basis of VAA policy statements on which users are asked to express opinions. VAA designers devote substantial time and effort to analyzing domestic and international politics to formulate policy statements and select those to be included in the application. This procedure involves manually reading and evaluating a large volume of publicly available data, primarily party manifestos. A problematic part of the work is the limited time frame. This study proposes a system to assist VAA designers in formulating, revising, and selecting policy statements. Using pre-trained language models and machine learning methods to process politics-related textual data, the system produces a set of suggestions corresponding to relevant VAA statements. Experiments were conducted using party manifestos and YouTube comments from Japan, combined with VAA policy statements from six Japanese and two European VAAs. The technical approaches used in the system are based on the BERT language model, which is known for its capability to capture the context of words in the documents. Although the output of the system does not completely eliminate the need for manual human assessment, it provides valuable suggestions for updating VAA policy statements on an objective, i.e., bias-free, basis

A text segmentation approach for automated annotation of online customer reviews, based on topic modeling

Online customer review classification and analysis have been recognized as an important problem in many domains, such as business intelligence, marketing, and e-governance. To solve this problem, a variety of machine learning methods was developed in the past decade. Existing methods, however, either rely on human labeling or have high computing cost, or both. This makes them a poor fit to deal with dynamic and ever-growing collections of short but semantically noisy texts of customer reviews. In the present study, the problem of multi-topic online review clustering is addressed by generating high quality bronze-standard labeled sets for training efficient classifier models. A novel unsupervised algorithm is developed to break reviews into sequential semantically homogeneous segments. Segment data is then used to fine-tune a Latent Dirichlet Allocation (LDA) model obtained for the reviews, and to classify them along categories detected through topic modeling. After testing the segmentation algorithm on a benchmark text collection, it was successfully applied in a case study of tourism review classification. In all experiments conducted, the proposed approach produced results similar to or better than baseline methods. The paper critically discusses the main findings and paves ways for future work