Mariken A.C.G. van der Velden

'Das Volk' or 'Bürger'? The Implications of Ethnic and Civic Conceptions of the People for the Measurement of Populist Attitudes.
(with Maurits J. Meijers)
Forthcoming in European Journal of Political Research .
Article | Open source code

Abstract: Populists believe in the sovereignty of the people. Yet, the people can be construed in ethnic terms or in civic terms. Using a novel wording experiment in Germany (N=7,034), we examine whether ethnic or civic conceptions of 'the people' affect respondents' adherence agreement to key populist attitude items. 'Volk' in German has an ethno-nationalist connotation and has been used throughout history to signify 'ethnic Germans'. The concept 'Bürger', or citizens, by contrast, lacks an ethnic undercurrent. Similar ethnic connotations of 'the people' are also common in other languages. We find that there are statistically significant differences between items framed in an ethnic and a civic manner -- and that this differs per item. This relationship is significantly moderated by respondents' degree of exclusive national identity and voting behaviour for the radical right. Our findings suggest that the way in which the people is conceptualized has important implications for the measurement of populist attitudes. When populist attitudes are measured with an ethnic understanding of the 'the people', the construct is biased toward right-wing populism, inhibiting the measurement of populism as a `thin-ideology'. Moreover, we demonstrate the importance of careful translations in comparative research, since some translated synonyms carry different meanings, and thereby change the concept under investigation."

Content Analysis in the Research Field of Political Coverage
(with Felicia Loecherbach)
Book chapter in Standardisierte Inhaltsanalyse in der Kommunikationswissenschaft–Standardized Content Analysis in Communication Research . Springer.
Book chapter

Abstract: The coverage of politics, and more specifically policies or political issues, in news media has been abundantly studied by scholars of agenda setting (see for example, McCombs and Shaw, 1972, 1993; Baumgartner and Jones, 2010, 1991; Soroka, 1999; Walgrave and Van Aelst, 2016; Vliegenthart and Walgrave, 2011; Walgrave and Van Aelst, 2016; Baumgartner et al., 2006). Building on Walter Lippmann’s (1957) argument of the media’s ability to construct social realities in the public mind, agenda setting refers to the transfer of often covered topics in news media to its salience in the public agenda. McCombs and Shaw (1972) pioneered this field, surveying voters in North Carolina (USA) on the most important political issues and comparing these results to a media content analysis of nine local news media outlets. This finding has been coined the first-level agenda setting theory. Ever since the seminal study of McCombs and Shaw (1972), this finding has been replicated hundreds of times all across the world – ranging from other locations in the USA, to Europe, Asia, Latin America and Australia – for both election and non-election settings over a broad range of public issues and other aspects of political communication. Moreover, the agenda-setting theory has been extended from objects of attention to attributes, known as the second-level (McCombs, 1992; McCombs and Shaw, 1993; McCombs et al., 2014). From the second-level, it became apparent that “the media not only can be successful in telling us what to think about, they also can be successful in telling us how to think about it” (McCombs, 2005, p.546, emphasis in original). In the early 2010’s, the theory extended with a third-level (Guo et al., 2012; Guo and McCombs, 2011). This level includes a network component to the theory. In this chapter, we will describe the state-of-the-art of agenda-setting theory for the coverage of politics, and especially policies and political issues in media in three trends. Thereafter, we discuss the most common used research designs (pp.5–8), and we conclude with the limitations and possible future directions of the field (pp.8–10).

Fueling Toxicity? Studying Deceitful Opinion Leaders and Behavioral Changes of Their Followers
(with Puck Guldemond and Andreu Casas Salleras)
Politics and Governance .
Article

Abstract: The spread of deceiving content on social media platforms is a growing concern amongst scholars, policymakers, and the public at large. We examine the extent to which influential users (i.e., “deceitful opinion leaders”) on Twitter engage in the spread of different types of deceiving content, thereby overcoming the compartmentalized state of the field. We introduce a theoretical concept and approach that puts these deceitful opinion leaders at the center, instead of the content they spread. Moreover, our study contributes to the understanding of the effects that these deceiving messages have on other Twitter users. For 5,574 users and 731,371 unique messages, we apply computational methods to study changes in messaging behavior after they started following a set of eight Dutch deceitful opinion leaders on Twitter during the Dutch 2021 election campaign. The results show that users apply more uncivil language, become more affectively polarized, and talk more about politics after following a deceitful opinion leader. Our results thereby underline that this small group of deceitful opinion leaders change the norms of conversation on these platforms. Hence, this accentuates the need for future research to study the literary concept of deceitful opinion leaders.

Three Gaps in Computational Text Analysis Methods for Social Sciences: A Research Agenda
(with Christian Baden, Christian Pipal, and Martijn Schoonvelde)
Computational Methods and Measures .
Article

Abstract: We identify three gaps that limit the utility and obstruct the progress of computational text analysis methods (CTAM) for social science research. First, we contend that CTAM development has prioritized technological over validity concerns, giving limited attention to the operationalization of social scientific measurements. Second, we identify a mismatch between CTAMs’ focus on extracting specific contents and document-level patterns, and social science researchers’ need for measuring multiple, often complex contents in the text. Third, we argue that the dominance of English language tools depresses comparative research and inclusivity toward scholarly communities examining languages other than English. We substantiate our claims by drawing upon a broad review of methodological work in the computational social sciences, as well as an inventory of leading research publications using quantitative textual analysis. Subsequently, we discuss implications of these three gaps for social scientists’ uneven uptake of CTAM, as well as the field of computational social science text research as a whole. Finally, we propose a research agenda intended to bridge the identified gaps and improve the validity, utility, and inclusiveness of CTAM.

Epistemic Overconfidence in Algorithmic News Selection
(with Felicia Loecherbach)
Forthcoming at Media and Communication
Article | Open source code

Abstract: The process of news consumption has undergone great changes over the past decade: Information is now available in an ever-increasing amount from a plethora of sources. Recent work suggests that most people would favor algorithmic solutions over human editors. This stands in contrast to public and scholarly debate about the pitfalls of algorithmic news selection - i.e. so-called “filter bubbles”. This study therefore investigates the reasons and motivations which might lead people to prefer algorithmic gatekeepers over human ones. We expect that people have more algorithmic appreciation when consuming news to pass time, entertain oneself or out of escapism than when using news to keep up-to-date with politics (H1). Secondly, we hypothesize the extent to which people are confident in their own cognitive abilities moderates that relationship: When people are overconfident in their own capabilities to estimate the relevance of information, they are more likely to have higher levels of algorithmic appreciation, due to the third person effect (H2). For testing those two pre-registered hypothesis , we conducted an online survey with a sample of 268 U.S. participants, and replicated our study using a sample of 384 Dutch participants. The results show that the first hypothesis cannot be supported by our data. However, a positive interaction between overconfidence and algorithmic appreciation in case the gratification of news usage is surveillance (i.e. gaining information about the world, society, and politics) was found in both samples. Thereby, our study contributes to our understanding of the underlying reasons people have for choosing different forms of gatekeeping when selecting news.

Media, politics, and affect
(with Isabella Rebasso)
Book chapter in Routledge Handbook of Emotions and Media
Book chapter

Abstract: Ever since the seminal campaign of Lyndon B. Johnson in 1964 where Daisy was introduced, emotions are present in political campaigns and other political processes. Their effect used to be understudied by scholars of political communication, however, until the early 2000s. Scholars have demonstrated ample times that making emotional appeals matters for their electoral strategy. Moreover, it has been shown that specific emotions elicit behavioral effects on citizens. This review shows how emotions are applied by political elites, their effects on citizens as well as how to study these emotional appeals in political communication.

The Validity of Sentiment Analysis: Comparing Manual Annotation, Crowd-Coding, Dictionary Approaches, and Machine Learning Algorithms
(with Wouter van Atteveldt & Mark Boukes)
Communication Methods and Measures
Article | Open source code

Abstract: Sentiment is central to many studies of communication science, from negativity and polarization in political communication to analyzing product reviews and social media comments in other sub-fields. This study provides an exhaustive comparison of sentiment analysis methods, using a validation set of Dutch economic headlines to compare the performance of manual annotation, crowd coding, numerous dictionaries and machine learning using both traditional and deep learning algorithms. The three main conclusions of this article are that: (1) The best performance is still attained with trained human or crowd coding; (2) None of the used dictionaries come close to acceptable levels of validity; and (3) machine learning, especially deep learning, substantially outperforms dictionary-based methods but falls short of human performance. From these findings, we stress the importance of always validating automatic text analysis methods before usage. Moreover, we provide a recommended step-by-step approach for (automated) text analysis projects to ensure both efficiency and validity.

Selecting in or Selecting Out? Gender Gaps and Political Methodology in Europe
(with Malu A.C. Gatto, Anita R. Gohdes & Denise Traber)
PS: Political Science & Politics
Article

Abstract: Studies investigating gender gaps in the doctoral training of political science students have focused so far overwhelmingly on the US context. Although important research within this context has made strides in identifying the persistent challenges to women’s incorporation in political methodology, much remains unknown about whether women and men have different experiences in methods training during their PhD programs. We contribute to this debate by analyzing data from an original survey on the methods-training experiences of political science PhD students at different European universities. We assess whether gender gaps exist with respect to PhD students’ methods training and confidence in employing methods skills. Our findings show that women cover significantly fewer methods courses in their doctoral training. When women do participate in methods training, they show levels of method employment similar to their male colleagues. We discuss the implications of these findings in the context of European doctoral training.

A new dataset of Dutch and Danish party congress speeches
(with Gijs Schumacher, Daniel Hansen & Sander Kunst)
Research & Politics
Article

Abstract: We present a new dataset of speeches given by Danish and Dutch politicians at party congresses between 1946 and 2017. The dataset is a unique collection of materials from different party archives and digital repositories. It offers a unique opportunity to analyse the issues discussed in these speeches, the positions taken and the rhetoric used by party elites over time and between countries. We describe the data and illustrate them with one application: a sentiment analysis that describes differences between parties and over time.

The Use and Usefulness of p-Values in Political Science: Introduction
(with Daniel Bischof)
Swiss Political Science Review
Article

Abstract: P-values are the most frequently employed metric to assess the significance of statistical findings in the social sciences. Since the earliest years of their usage the meaning and usefulness of p-values were topics of heated discussion (Berkson 1942; Fisher 1935). Lately the reproduction/replication crisis resuscitated this debate (Benjamin et al. 2018; Gelman 2018; Lakens et al. 2018; McShane et al. 2019; Nuzzo 2014; Trafimow and Marks 2015). Meanwhile, the skepticism has not stopped at the gates of political science. Most prominently the journal “Political Analysis” banned p-values “in regression tables or elsewhere” after the new editor took over the board of editors in 2017 (Gill 2018: 1).1 Also political scientists contributed to a swelling debate suggesting to lower the threshold for p-values to 0.005 (Benjamin et al. 2018; Esarey 2017). This present debate seeks to contribute to the discussion on p-values by summarizing the main arguments of it, providing an encompassing discussion of p-values – also from an epistemological perspective – as well as advice for the discipline about the Do's and Don'ts for p-values. In doing so it contributes to two ongoing debates: First, the actual meaning of p-values – the mathematical definition. Second, the potential to misuse p-values – even if correctly understood and defined. In February 2018 the Department of Political Science at the University of Zurich held a workshop containing public lectures about the use and usefulness of p-values. The goal of the workshop was to cover a wide spectrum of opinions on p-values, covering frequentist, bayesian and more epistemological views. The present contribution summarizes these public lectures but also goes beyond them by giving each author the opportunity to engage with the position of the remaining authors on the one hand and by adding a critical discussion of all lectures in the conclusion on the other hand. Our introduction first gives a brief history of p-values and their definition before summarizing the discussion about the use and “misuse” of p-values in the discipline and situates this into the larger debate on the replication crisis; Vera Troeger (2019) discusses the logic of statistical inference and significance testing and the implications of significance testing for empirical research; Susumu Shikano (2019) provides a detailed insight into two Bayesian approaches to hypothesis testing; Marco R. Steenbergen (2019) takes a stronger epistemological view on to p or not to p; and finally, Simon Hug (2019) critically discusses the contributions of this debate by emphasizing that none of the discussed approaches appear to provide a “silver bullet” for the issues they seek to address.

Studying Political Decision Making With Automatic Text Analysis
(with Wouter van Atteveldt & Kasper Welbers)
Oxford Research Encyclopedia of Politics
Article

Abstract: Analyzing political text can answer many pressing questions in political science, from understanding political ideology to mapping the effects of censorship in authoritarian states. This makes the study of political text and speech an important part of the political science methodological toolbox. The confluence of increasing availability of large digital text collections, plentiful computational power, and methodological innovations has led to many researchers adopting techniques of automatic text analysis for coding and analyzing textual data. In what is sometimes termed the “text as data” approach, texts are converted to a numerical representation, and various techniques such as dictionary analysis, automatic scaling, topic modeling, and machine learning are used to find patterns in and test hypotheses on these data. These methods all make certain assumptions and need to be validated to assess their fitness for any particular task and domain.

Living in the past or living in the future? Analyzing parties’ platform change in between elections, the Netherlands 1997–2014
(with Gijs Schumacher & Barbara Vis)
Political Communication
Article

Abstract: Do parties change their platform in anticipation of electoral losses? Or do parties respond to experienced losses at the previous election? These questions relate to two mechanisms to align public opinion with party platforms: (1) rational anticipation, and (2) electoral performance. While extant work empirically tested, and found support for, the latter mechanism, the effect of rational anticipation has not been put to an empirical test yet. We contribute to the literature on party platform change by theorizing and assessing how party performance motivates parties to change their platform in-between elections. We built a new and unique dataset of >20,000 press releases issued by 15 Dutch national political parties that were in parliament between 1997 and 2014. Utilizing automated text analysis (topic modeling) to measure parties’ platform change, we show that electoral defeat motivates party platform change in-between elections. In line with existing findings, we demonstrate that parties are backward-looking.

Don't Budge! The Reputational Cost of Political Compromises
(with Maurits J. Meijers)

Abstract
Extant research shows that citizens support he abstract democratic principle of political compromise, but tend to reject specific compromises between political parties. Yet, it remains unclear how positional flexibility during coalition negotiations affect the perceived trustworthiness and credibility of parties. We examine whether compromises by one's in-party during coalition negotiations can breed political distrust and dissatisfaction with representation using a pre-registered survey experiment in Germany fielded just after the 2021 parliamentary elections (`N=8,000`), in which we 1) isolate the effect of parties’ negotiation position from success or failure in the negotiations; and 2) delve into the social psychological mechanisms that drive voters’ responses to compromise. We find that compromises signficantly harm citizens' evaluations of trust, credibility and representational performance. This effect is particularly pronounced among highly principled citizens and citizens with low social trust. Finally, in a pre-registered observational study we examine whether the negative relationship between citizens' anti-compromise attitudes and political trust holds across 20 modern democracies, showing that anti-compromise attitudes coincide with lower levels of political trust. Our study sheds light on the reputational costs associated with party compromises in coalition negotiations. Thereby, our study has important implications for the study of political representation.

When the Cat’s Away, the Mice will Play? How Journalistic Intervention Influences Political Parties' Decision to Go Negative
(with Dirck de Kleer)
Draft | Open Source Material

Abstract
Negative campaigning is widely studied in the context of American and Western European elections. Studies that seek to explain when political actors "go negative" often locate these determinants in contextual or party characteristics, such as parties’ position in the polls, their incumbency status or political ideologically. Against the backdrop of our current high-choice media environment, a crucial element that is often overlooked is that parties can also weigh their rhetorical strategies across communication channels, based on the amount of journalistic intervention that takes place and the audience political parties can reach. Focusing on the 2017 Dutch General Elections, we examine how Dutch political parties use negative campaigning strategies across different communication channels. Analyzing 1490 appeals that appeared in newspaper articles, talk shows and in parties' Facebook posts, we show that in increase in journalistic intervention is associated with more negative appeals. Our findings highlight the importance of studying communication channels in comparative perspective and add more nuance to our understanding of rhetorical strategies during campaigns.

Do Coalition Partners Drift Apart or Stick Together? An analysis of party platform changes in 8 Western European countries
(with Gijs Schumacher)
Draft | Open Source Material

Abstract
Coalition governments are the norm in West European democracies. Yet, we do not know whether governing together affects parties' calculations about setting their policy position in their next election manifesto. Therefore we ask: do coalition parties drift apart or stick together after a spell in office? We hypothesize that government parties stick together in anticipation of government continuation. Coalition parties are more likely to expect continuation if they are popular, have no inter-party conflict and have experience in co-governing. If this is not the case, coalition parties drift apart as they seek new coalition formation opportunities. We empirically substantiate our hypotheses with an innovative measure of party platform change analyzing 1,193 platform changes in 8 European democracies between 1968 and 2013 using new opinion poll data and several existing data sets. We demonstrate that parties plant the seeds of future coalition participation in their platforms: the more experienced and the more popular coalition parties are, the more they converge. Encountering conflict, on the contrary, leads them to diverge.

StukRoodVlees
I regularly write articles for the Dutch political science blog Stuk Rood Vlees . Read my contributions here.

Hoe anders kan Rutte IV worden als dezelfde partijen doorgaan? 'Zorg voor nieuwe gezichten in het kabinet'
Radio and TV interview with Dutch news program EenVandaag

Een minderheidskabinet: waarom eigenlijk niet?
Interview with Dutch quality newspaper NRC Handelsblad

Polarisatie in de polder
Table host to discuss cooperation and polarization in Dutch politics at the Amsterdam Debating Center Pakhuis de Zwijger

Betrouwbare boodschapper
Table host to discuss the reliability of Dutch (new) media at the Amsterdam Debating Center Pakhuis de Zwijger

Wederzijds wantrouwen
Table host to discuss the state of political (dis)trust in Dutch Politics at the Amsterdam Debating Center Pakhuis de Zwijger

Coalitie onmogelijk? In deze landen leek dat ook zo, maar lukte het toch
Interview with Dutch commercial broadcaster RTL Nieuws

NOS Journaal
Explaining the 2021 Dutch Election results on the Dutch Publication national broadcasting NOS

Verkiezingsavond: de weerbare democratie
Explaining the 2021 Dutch Election results at the Amsterdam Debating Center Pakhuis de Zwijger

Iedere partij een eigen journaal. Welkome stemhulp of bron van desinformatie?
Interview with Argos Media Logica

Welke partijen waren het meest in beeld?
Interview with and data analysis for Dutch Newspaper NRC Handelsblad

Dutch elections: How COVID-19 salvaged Mark Rutte's bid amid scandal
Interview with and data analysis for for German international broadcaster Deutsche Welle

Wilders en Baudet groot op sociale media dankzij harde kern van fans
Interview with and data analysis for Dutch Newspaper NRC Handelsblad

Hoe de media onze stem beïnvloeden. Teruggebracht tot tweestrijd
Interview with Dutch Weekly paper Groene Amsterdammer

Propaganda in partij-journaals?
Televised interview with Dutch tv-show Propaganda on the Dutch public national broadcasting

Wat de kiezer leest, volgt, en kijkt
Interview with and data analysis for Dutch Newspaper NRC Handelsblad