The Digital Communication Methods Lab, an initiative of the RPA Communication, renewed its support to a series of innovative research projects focused on substantive and methodological development for communication science research in partnership with Amsterdam School of Communication Research (ASCoR) members.

After four successful rounds in 2018, 2019, 2020, and 2021, fourteen projects have been selected to receive funding for 2022 and complement ongoing activities at the lab.


AI in communication

Machines and Overconfidence: Antecedents, Extent, and Correction

by dr. Sonia Jawaid Shaikh
Artificial intelligence (AI)-enabled technologies are increasingly being used by humans to make decisions across a variety of settings. The basic idea underlying this technological setup is to provide humans with some kind of machine-based recommendation (e.g. employability score, risk score) which can be utilized in making a judgment or decision. An important consideration in these circumstances has to do with overconfidence i.e., the extent to which humans systematically overestimate accuracy of their decisions and precision of their knowledge. Overconfidence negatively affects various organizational outcomes. However, it remains unclear how and to what extent it evolves when human decision-making is influenced by machine recommendations. This project investigates antecedents, extent, and correction of overconfidence within the context of machine-driven recommendations for decision-making. A series of experiments on a virtual platform will investigate how interaction with AI affects overconfidence and also explore design-based solutions to reduce it.


Automated content analysis

The robot or the brain? Building a classifier for visual news frames of Artificial Intelligence

by dr. Irina Lock
Anecdotal evidence shows that news articles visualize AI repeatedly as stylized humanoid robots or brains, speaking to technology’s anthropomorphization. While AI frames have been studied in news texts, content analyses of AI images are lacking. The way news media visually frame AI purports multiple sociotechnical imaginaries of how the reader is supposed to envision the future. However, we miss systematic knowledge about how news media visually frames AI. This project uses images from open source and commercial editorial image databases to build a classifier that categorizes pre-defined frames in images of AI to be applied to analyses of news or social media.


The Comment Relevance Detector

by dr. Marthe Möller and dr. Susanne Baumgartner
The past years have seen a rise in studies investigating how user comments influence the experiences of social media users. The various studies that have been conducted on this topic so far all seem to be based on the same assumption, namely that comments are relevant in the sense that they actually discuss the main content that they accompany (e.g., a YouTube video, Instagram image). The present project aims to test this assumption by creating a tool that can detect the relevance of comments (i.e., whether or not a comment discusses the main content that it accompanies). Using comments written in response to music videos posted on YouTube, we will train a machine that can automatically classify comments. Scholars can then use this machine to verify the assumption that the comments that they study are relevant (and hence, can influence how viewers experience social media content).


Validity of computational attitude and attitude strength measures for social media data

by dr. Joanna Strycharz and Joseph Yun, Ph.D. (University of Pittsburgh)
Studying attitudes has been crucial in communication and advertising theory development; measurement of attitudes has had a substantial impact on several contexts, including research on advertising effectiveness and consumer reactanceIn recent research, it has been acknowledged that while attitudes are important for beliefs and behavior, strong attitudes have a greater impact on individual’s intentions and behaviors. Thus, both attitude and attitude strength take an important role in communication and advertising research. In the proposed study, we aim to investigate how attitude and attitude strength measurements can be improved in the context of digital communication.


Understanding Climate Polarization and Depolarization Dynamics

by dr. Christel van Eck, dr. Anne Kroon, dr. Damian Trilling
While increasingly more studies focus on online climate change polarization dynamics, research on ‘processes’ of polarization (instead of ‘states’ of polarization) and research on depolarization dynamics is largely overlooked. Hence, the current study will investigate online climate change polarization and depolarization dynamics, by analyzing Dutch comment interactions about climate change on Youtube and Twitter. A sample of comments will be manually annotated by crowd coders based on the following concepts: (a) users’ global warming stance; (b) escalation; and (c) identity labeling. Using these annotations, we will train a BERT supervised classifier to predict class membership in a large-scale dataset of social media comments on the topic of climate change. This project will provide insight into how climate change polarization emerges, accelerates, and dissolves online.


Data Donation

Climate Skepticism, Populism & Digital Alternative Media Use

by dr. Christel van Eck and dr. Mark Boukes
Little is still known about the nature and causes of the association between climate skepticism and populism. Hence, this research will investigate whether climate skepticism is associated with populist attitudes, and whether this relationship is mediated by individuals’ use of digital alternative media. Earlier research measuring alternative media use, often relied on self-reported survey data that is prone to several biases. Therefore, we will use the “Seed Funding for Data Donation” to collect respondents’ existing digital trace data and measure their actual alternative media use. As such, the research and seed funding will contribute both to academic theory on climate skepticism and populist attitudes. Moreover, we make important steps in methodological approaches to collect data on alternative media use.


Exploring individuals’ imagined social media affordances using self-report measures and donated log-based data

by dr. Sarah Marschlich
Previous research conceived social media affordances as opportunities for action enabled by platforms technologies or as the result of users’ agency, neglecting that users act building on their perception of platform properties, gratifications, and other individual factors. To overcome the shortcomings, this research conceives affordances as the interplay between the social media platforms and the individual user, analyzing affordances in the context of organizations’ communication on social media. Combining survey, data donation, and in-depth interviews in which individuals are exposed to their actual social media usage, this project aims to shed light on the emergence of social media affordances and their consequences for user engagement, considering technological features and individual factors. The methodology allows for a much more valid and accurate measurement of social media affordances and significantly contributes to collecting digital communication data through donated log-based data and self-report measures.


Media Exposure

The influence of parasocial relationships with social media influencers on young women’s body perception, well-being, and health-related behavior. An experience sampling study

by dr. Priska Breves, dr. Sophie Boerman and dr. Nicole Liebers (University of Würzburg)
Social media influencers who post body-focused content have often been criticized for their negative impact on young women (e.g., regarding eating disorders). However, empirical research is lacking, especially concerning the long-term effects. By following and engaging with the same influencer over several weeks, followers are likely to form strong one-sided illusionary relationships. These parasocial relationships have been connected to an intensification of social comparison processes. Thus, the influencer’s impact on participants’ body perception, well-being, and health-related behavior should also be enhanced after several weeks. In our study, we want to use the Experience Sampling Method and confront participants with daily posts from the same influencer while experimentally analyzing the impact of the influencer’s thematic focus and body type.


Stimulus validity in political communication research

by dr. Bernhard Clemm
Experimental or survey research designs in political communication often require the use of information stimuli, which are supposed to represent some aspect of real-world information environments. However, researchers rarely define the target population of information, and do not explain how they achieve a valid representation of this population. This, in essence, is the problem of stimulus validity. In this project, I define stimulus validity formally in the language of estimands, estimates and inference, in close parallel to external validity. I then re-analyse and replicate several studies to illustrate what can happen if we do not pay attention to stimulus validity.


Googling Politics? The Computational Identification of Political and News-related Searches from Web Browser Histories

by dr. Damian Trilling, Marieke van Hoof, dr. Judith Möller and dr. Corine Meppelink
Search engines are crucial avenues to political information and news, but we know very little about search in practice. How frequently do people search for news and political content? What type of queries do they use? What search results do they click on? How does search differ between individuals? To this end, we need an approach to analyze real-life accounts of search behaviour: browser histories. In this project, we develop and systematically compare various (combinations of) computational approaches to automatically identify political and news-related searches in large corpora of behavioural trace data. We validate these approaches on two different samples of search histories and present a use case that answers some of the questions posed above.


Short But Still Valid: Validating One-Item Measures for Key Communication Constructs for Experience Sampling Research

by Lara Wolfers and dr. Susanne Baumgartner
With the deeper integration of digital media into everyday life, the popularity of Experience Sampling Methods (ESMs) in communication science has surged. For ESMs, it is essential to keep the length of daily questionnaires as short as possible. Thus, constructs are often assessed with one item. However, even for key communication constructs, no validated one-item measures are available. The aim of this project is to validate one-item measures for key communication constructs for use in ESM. We will identify central communication science construct, select suitable items for these constructs, and validate these items in an ESM study.


Mobile Communication

Explicating smartphone notifications: prevalence, impact and solutions

by dr. Susanne Baumgartner, dr. Sindy Sumter, dr. Jakob Ohme (Weizenbaum Institut), and Cynthia Dekker
The present study aims to investigate the interplay between push notifications and smartphone behavior, as well as the effects of restricting push notifications. By analyzing smartphone tracking data and daily self-report data, we will examine questions related to the timing of notifications, types of notifications (e.g., news vs. social media), response times, duration of smartphone use sessions, and daily digital well-being outcomes. Furthermore, we will empirically define internally versus externally triggered smartphone use, and examine the moderating role of individual characteristics (e.g., self-control). Finally, during a 3-week intervention study, we will experimentally investigate the effects of restricting notifications on users’ well-being.


Break a story: Examining the effects of Instagram Stories from news accounts on adolescents’ political learning

by dr. Susan Vermeer and dr. Linda van den Heijkant
With more than one billion monthly active users, Instagram use for news has almost doubled since 2018, and hence, overtaken Twitter, particularly among younger generations. As a result, many news organizations are trying to attract a younger audience by actively sharing news on Instagram. For instance, NOS Stories (i.e., an online news service of the Dutch public broadcaster) has created an Instagram channel to specifically inform Dutch adolescents between the ages of 13 and 18. To date, there is no experimental evidence and therefore little knowledge about the effects of Instagram use for news on political behavior and attitudes. In this study, we will therefore focus on the question: To what extent can Instagram Stories facilitate learning about politics and current events among Dutch adolescents? To answer this question, we will conduct an online field experiment. We aim to create a feasible way to investigate mobile communication, and more specifically the use of Instagram, and primarily Instagram stories, in a setting that is close to everyday Instagram use.


Virtual Reality

Let’s talk about climate change: Can virtual reality stimulate climate change conversations and climate friendly behavior?

by dr. Marijn Meijers, dr. Jeroen Lemmens, & dr. Hanneke Hendriks (Radboud University)
Climate change is posing an increasing threat to nature, animal species, and humans. To combat climate change, individuals play an important role by behaving climate friendly and by engaging in interpersonal communication regarding climate change in order to create support for societal and governmental changes. Research so far mostly focuses on stimulating climate friendly behavior, whereas stimulating interpersonal climate change communication is so far largely overlooked. The question, therefore, is: how can we stimulate people to talk about climate change? We will investigate whether a Virtual Reality experience regarding climate change stimulates interpersonal climate change communication. Furthermore, we will look into the role of emotions and arousal as underlying mechanisms.