Suchergebnisse

This thesis explores the opportunities to build a structural policy network model that is rooted in social network theories. By making a distinction between a process of steering in networks, and a process of steering by networks, it addresses the effects of network structures on network dynamics as well as on the production of policy outputs. Steering in policy networks refers to the process of horizontal bargaining over policy positions in which resources are exchanged between individual network actors. Steering by policy networks refers to the policy making processes in which policy networks are utilized as policy instruments. The details of network configuration profoundly influence individual actors' capacities to influence such bargaining processes and the social structures of policy networks change due to the process of steering in networks. The individual, sequential actions that characterize bargaining over various resources nevertheless do not explain how policy networks produce policy outputs. The study investigates how actor-based models of network dynamics provide a theoretical point of departure for explaining firstly the structural outcomes of steering in networks, and secondly the utility of any potential policy outputs for both government and individual actors. Because of the interdependency between actors in heterogeneous policy networks, outputs require subgroup-level coordination. There is therefore a mismatch between individual and group utility – whilst some individuals will benefit from a sparse network structure in negotiation processes, the optimum system outcome is produced by dense and cohesive social structures. The study elaborates on this paradox and shows the utility of different characteristics of network structures for both individual actors and government, and presents hypotheses on the relations between policy goals, policy positions, network structures, and the utility of policy outputs.

This article explores how Twitter was used by voters to participate in electoral campaigning during the Dutch election campaign of 2012. New social media networks like Twitter are believed to be efficient tools of communication between electoral candidates and voters during electoral campaign periods. Yet only few studies have been conducted so far to discover in what way the content of online discussions is being used for campaigning. In particular, there have been very few studies of electoral campaigning, which study the content of the social media messages sent by citizens. In order to understand the extent to which citizens utilize Twitter in different forms of electoral campaigning—that is, persuading followers about voting for a particular party or to conduct negative campaigning, we conducted an automated content analysis of a large corpus of tweets collected during the Dutch parliamentary election campaign of 2012. Our findings show that citizens participate significantly in online electoral campaigning on Twitter, whereas they differ from professional users in the style of campaigning. Persuasive campaigning is observed to a lesser extent among citizens than among politicians, while citizens more commonly use negative campaigning. Moreover, qualitative content analysis of campaigning tweets by citizens has revealed that expressions of emotions and opinions make up a large majority of negative tweets, indicating that citizens regard Twitter more as an outlet for expressing discontent than as a medium for negative campaigning.

Social media, in particular Twitter, become an increasingly attractive tool for political scientists for the study of political attitudes and behavior because of its potential for tracking public opinion with minimal costs. Yet extracting reliable, valid and precise measurements of politically relevant concepts from these data sources still forms a major challenge. The present research is part of the project "Transforming Social Media Contents to Political Data" (funded by the Netherlands Organization for Scientific Research NWO), which aims at addressing this challenge by developing new tools and methods for harvesting, coding and analyzing messages from social media. Using data collected from Twitter during the last three weeks of the Dutch parliamentary election campaign 2012, we demonstrate in this paper how two prominent concepts of research on voting behavior – issue salience and issue ownership – can be measured online, and how these measures compare to traditional survey data. The preliminary results obtained by this study show that measures of issue salience and issue ownership using data collected from Twitter are comparable with the survey data to a considerable extent. However, we have also found some discrepancies between the two data sets on key issues, which suggest that our online measurements of the two concepts need to be further developed for a more sound validation.