Kasper Welbers
Biographic Data
| ID | 188718 |
|---|---|
| NAME | Kasper Welbers |
| GIVEN NAMES | Kasper |
| FAMILY NAME | Welbers |
| SIGNATURE | WELBERS K |
| AFFILIATIONS | Vrije Universiteit Amsterdam |
| ORCID | 0000-0003-2929-3815 |
| VERIFIED | Yes |
| TOTAL WORKS | 23 |
| TOTAL CITATIONS | 234 |
| AUTHOR COUNT | 23 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 7 |
Do news access pathways moderate filter bubbles? Evidence from a longitudinal analysis of data donations
News access pathways shape the informational diversity of users’ news repertoires, with distributed modes such as search and social media generally providing broader exposure than direct navigation. Yet whether these differences produce filter bubble dynamics—gradual narrowing of diversity over time—remains underevaluated. We provide a direct test using donated browsing histories from n = 179 users in the Netherlands spanning approximately 1 year…
Meaningful informed consent? How participants experience and understand data donation
Data donation makes it possible to invite participants to request and share their data from digital platforms for research purposes. While it is a user-centric approach to digital trace data collection, little is known about how participants experience and understand the data donation process. This study therefore asked twenty participants to verbalize their thoughts and actions as they went through data donation (from Google, YouTube, Facebook, …
Whose truth is it anyway? An experiment on annotation bias in times of factual opinion polarization
Information shapes citizens’ political decision-making. This process is amply studied by social scientists, for whom human annotation is a crucial instrument in their toolkit. Due to the democratization of data and the advances in NLP more data can be analyzed or classified, making these benchmarks more important than ever: An algorithm trained on biased data will reproduce and often exacerbate bias. Currently, disagreement and bias are often con…
How shared ties and journalistic cultures shape global news coverage of disruptive media events: The case of the 9/11 terror attacks
In recent decades, disruptive media events, such as major terrorist attacks, have gained increasing relevance in news coverage around the world. Despite the growing importance of such globally broadcast media events, little research to date has examined cross-national variation in event coverage or the predictors of this variation. This study examines news coverage about the 9/11 terror attacks in the United States across 51 countries to analyze …
Fulfilling data access obligations: How could (and should) platforms facilitate data donation studies
Research into digital platforms has become increasingly difficult. One way to overcome these difficulties is to build on data access rights in EU data protection law, which requires platforms to offer users a copy of their data. In data donation studies, researchers ask study participants to exercise this right and donate their data to science. However, there is increasing evidence that platforms do not comply with designated laws. We first discu…
On Measurement Validity and Language Models: Increasing Validity and Decreasing Bias with Instructions
Language models like BERT or GPT are becoming increasingly popular measurement tools, but are the measurements they produce valid? Literature suggests that there is still a relevant gap between the ambitions of computational text analysis methods and the validity of their outputs. One prominent threat to validity is hidden biases in the training data, where models learn group-specific language patterns instead of the concept researchers want to m…
What is Popular Gets More Popular? Exploring Over-Time Dynamics in Article Readership Using Real-World Log Data
Online news can be shared and promoted via social media, mobile push messages, newsletters, "most read" boxes, or the like. This can result in feedback loops, in which views attract even more views. Using full click logs for five regional newspapers in the Netherlands, spanning N views = 12,108,263 views of N articles = 17,982 articles for each minute over the course of 13 weeks, we shed light on potential feedback loops. While article placement …
Less Annotating, More Classifying: Addressing the Data Scarcity Issue of Supervised Machine Learning with Deep Transfer Learning and Bert-NLI
Supervised machine learning is an increasingly popular tool for analyzing large political text corpora. The main disadvantage of supervised machine learning is the need for thousands of manually annotated training data points. This issue is particularly important in the social sciences where most new research questions require new training data for a new task tailored to the specific research question. This paper analyses how deep transfer learni…
Linked in the dark: A network approach to understanding information flows within the Dutch Telegramsphere
Recent studies have shown that the stricter content moderation policies imposed by mainstream social networking sites (SNSs) stimulated the growth of low-moderated but relatively open discussion platforms such as Telegram. Despite Telegram’s growing popularity among (deplatformed) digital exiles, and high potential for news dissemination, information consumption, mobilization, and radicalization, little is known about information flows with respe…
Challenging the Global Cultural Conflict Narrative: An Automated Content Analysis on How PerPetrator Identity Shapes Worldwide News Coverage of Islamist and Right-Wing Terror Attacks
Recent terrorist attacks such as the Christchurch mosque attacks in 2019 renew the discussion of whether right-wing attacks are reported less negatively than Islamist attacks. To clarify this point, our study is the first to combine the selection of media inside and outside the West with a distinction between Islamist and right-wing attacks. We compare coverage given to thirty-two right-wing and forty Islamist attacks from 2015 to 2019 in nine We…
Advancing Automated Content Analysis for a New Era of Media Effects Research: The Key Role of Transfer Learning
The availability of individual-level digital trace data offers exciting new ways to study media uses and effects based on the actual content that people encountered. In this article, we argue that to really reap the benefits of this data, we need to update our methodology for automated text analysis. We review challenges for the automatic identification of theoretically relevant concepts in texts along three dimensions: format/style, language , a…
Linking event archives to news: A computational method for analyzing the gatekeeping process
Digital archives that document real-world events provide new opportunities for large-scale analyses of how news coverage represents reality. We present a method and open-source tool for linking event data to news articles, and demonstrate its application with an analysis of event and country level predictors of terrorism coverage in The Guardian from 2006 to 2018, using event data from the Global Terrorism Database (GTD). Our method builds on est…
Multiperspectival Normative Assessment: The Case of Mediated Reactions to Terrorism
This article provides a model for how communication phenomena can be normatively assessed using multiple normative perspectives simultaneously. We exemplify the procedure of multiperspectival normative assessment (MNA) using mediated reactions to terrorism as our case in point. We first identify the normative challenges related to the speed and substance of terrorism communication and the ways in which relations of solidarity are communicatively …
Reproducible Extraction of Cross-lingual Topics (rectr)
With global media content databases and online content being available, analyzing topical structures in different languages simultaneously has become an urgent computational task. Some previous studies have analyzed topics in a multilingual corpus by translating all items into a single language using a machine translation service, such as Google Translate. We argue that this method is not reproducible in the long run and proposes a new method – R…
The Negation Bias in Stereotype Maintenance: A Replication in Five Languages
Research on linguistic biases shows that stereotypic expectancies are implicitly reflected in language and thereby subtly communicated to message recipients. Research on the Negation Bias shows that the use of negations (e.g., not stupid vs. smart) is more pronounced in descriptions of stereotype-inconsistent compared with stereotype-consistent behaviors. This article reports a replication study of the original research conducted in Dutch, using …
News through a social media filter: Different perspectives on immigration in news on website and social media formats
Social media have become important news sources, prompting news organizations to create social media accounts to publish news. This requires a medium-based translation, in which social media editors must remediate news – selecting and possibly re-interpreting content – to accommodate a different audience and format. In this study we investigate this remediation for the issue of immigration, comparing the news coverage of immigration on the websit…
Social media gatekeeping: An analysis of the gatekeeping influence of newspapers’ public Facebook pages
Due to the rising importance of social media platforms for news diffusion, newspapers are relying on social media editors to promote the distribution of their news items on these platforms. In this study, we investigate how much of an impact these social media editors really have, focusing on the impact of newspapers’ public pages on Facebook. Since the actions of individual users are not visible on many platforms due to privacy consideration, we…
Presenting News on Social Media: Media logic in the communication style of newspapers on Facebook
With the rising popularity of social media as news sources, a new common format element for presenting news has emerged: in addition to the classic headline, lead and picture, news organizations add a status message when they share their news articles on social media such as Twitter and Facebook. Based on media logic theory, we argue that the communication style of these messages is likely to be more interpersonal and subjective. To investigate t…
Text Analysis in R
Computational text analysis has become an exciting research field with many applications in communication research. It can be a difficult method to apply, however, because it requires knowledge of various techniques, and the software required to perform most of these techniques is not readily available in common statistical software packages. In this teacher’s corner, we address these barriers by providing an overview of general steps and operati…
Quantitative analysis of large amounts of journalistic texts using topic modelling
The huge collections of news content which have become available through digital technologies both enable and warrant scientific inquiry, challenging journalism scholars to analyse unprecedented amounts of texts. We propose Latent Dirichlet Allocation (LDA) topic modelling as a tool to face this challenge. LDA is a cutting edge technique for content analysis, designed to automatically organize large archives of documents based on latent topics, m…
A Gatekeeper among Gatekeepers: News agency influence in print and online newspapers in the Netherlands
This paper investigates the influence of news agency Algemeen Nederlands Persbureau (ANP) on the coverage and diversity of political news in Dutch national newspapers. Using computational text analysis, we analyzed the influence on print newspapers across three years (1996, 2008, and 2013) and compared influence on print and online newspapers in 2013. Results indicate that the influence of ANP on print newspapers only increased slightly. Online n…
News selection criteria in the digital age: Professional norms versus online audience metrics
On newspaper websites, journalists can observe the preferences of the audience in unprecedented detail and for low costs, based on the audience clicks (i.e. page views) for specific news articles. This article addresses whether journalists use this information to cater to audience preferences in their news selection choices. We analyzed the print and online editions of five national newspapers from the Netherlands with a mixed-method approach. Us…
Stylistic Accommodation on an Internet Forum as Bonding: Do Posters Adapt to the Style of Their Peers
Internet forums are theorized to be important social platforms for peer influence. Current research tends to conceptualize peer influence as adoption processes, investigating whether information received from network contacts stimulate the adoption of a product, service, taste, or attitude. Accordingly, research interest is focused on the first time a product is used. In contrast, the present study investigates mutual and recurrent adaptation bet…
News selection criteria in the digital age: Professional norms versus online audience metrics
On newspaper websites, journalists can observe the preferences of the audience in unprecedented detail and for low costs, based on the audience clicks (i.e. page views) for specific news articles. This article addresses whether journalists use this information to cater to audience preferences in their news selection choices. We analyzed the print and online editions of five national newspapers from the Netherlands with a mixed-method approach. Us…
Presenting News on Social Media: Media logic in the communication style of newspapers on Facebook
With the rising popularity of social media as news sources, a new common format element for presenting news has emerged: in addition to the classic headline, lead and picture, news organizations add a status message when they share their news articles on social media such as Twitter and Facebook. Based on media logic theory, we argue that the communication style of these messages is likely to be more interpersonal and subjective. To investigate t…
Less Annotating, More Classifying: Addressing the Data Scarcity Issue of Supervised Machine Learning with Deep Transfer Learning and Bert-NLI
Supervised machine learning is an increasingly popular tool for analyzing large political text corpora. The main disadvantage of supervised machine learning is the need for thousands of manually annotated training data points. This issue is particularly important in the social sciences where most new research questions require new training data for a new task tailored to the specific research question. This paper analyses how deep transfer learni…
Text Analysis in R
Computational text analysis has become an exciting research field with many applications in communication research. It can be a difficult method to apply, however, because it requires knowledge of various techniques, and the software required to perform most of these techniques is not readily available in common statistical software packages. In this teacher’s corner, we address these barriers by providing an overview of general steps and operati…
A Gatekeeper among Gatekeepers: News agency influence in print and online newspapers in the Netherlands
This paper investigates the influence of news agency Algemeen Nederlands Persbureau (ANP) on the coverage and diversity of political news in Dutch national newspapers. Using computational text analysis, we analyzed the influence on print newspapers across three years (1996, 2008, and 2013) and compared influence on print and online newspapers in 2013. Results indicate that the influence of ANP on print newspapers only increased slightly. Online n…
Reproducible Extraction of Cross-lingual Topics (rectr)
With global media content databases and online content being available, analyzing topical structures in different languages simultaneously has become an urgent computational task. Some previous studies have analyzed topics in a multilingual corpus by translating all items into a single language using a machine translation service, such as Google Translate. We argue that this method is not reproducible in the long run and proposes a new method – R…
Social media gatekeeping: An analysis of the gatekeeping influence of newspapers’ public Facebook pages
Due to the rising importance of social media platforms for news diffusion, newspapers are relying on social media editors to promote the distribution of their news items on these platforms. In this study, we investigate how much of an impact these social media editors really have, focusing on the impact of newspapers’ public pages on Facebook. Since the actions of individual users are not visible on many platforms due to privacy consideration, we…
Whose truth is it anyway? An experiment on annotation bias in times of factual opinion polarization
Information shapes citizens’ political decision-making. This process is amply studied by social scientists, for whom human annotation is a crucial instrument in their toolkit. Due to the democratization of data and the advances in NLP more data can be analyzed or classified, making these benchmarks more important than ever: An algorithm trained on biased data will reproduce and often exacerbate bias. Currently, disagreement and bias are often con…
Challenging the Global Cultural Conflict Narrative: An Automated Content Analysis on How PerPetrator Identity Shapes Worldwide News Coverage of Islamist and Right-Wing Terror Attacks
Recent terrorist attacks such as the Christchurch mosque attacks in 2019 renew the discussion of whether right-wing attacks are reported less negatively than Islamist attacks. To clarify this point, our study is the first to combine the selection of media inside and outside the West with a distinction between Islamist and right-wing attacks. We compare coverage given to thirty-two right-wing and forty Islamist attacks from 2015 to 2019 in nine We…
Advancing Automated Content Analysis for a New Era of Media Effects Research: The Key Role of Transfer Learning
The availability of individual-level digital trace data offers exciting new ways to study media uses and effects based on the actual content that people encountered. In this article, we argue that to really reap the benefits of this data, we need to update our methodology for automated text analysis. We review challenges for the automatic identification of theoretically relevant concepts in texts along three dimensions: format/style, language , a…
Stylistic Accommodation on an Internet Forum as Bonding: Do Posters Adapt to the Style of Their Peers
Internet forums are theorized to be important social platforms for peer influence. Current research tends to conceptualize peer influence as adoption processes, investigating whether information received from network contacts stimulate the adoption of a product, service, taste, or attitude. Accordingly, research interest is focused on the first time a product is used. In contrast, the present study investigates mutual and recurrent adaptation bet…
Multiperspectival Normative Assessment: The Case of Mediated Reactions to Terrorism
This article provides a model for how communication phenomena can be normatively assessed using multiple normative perspectives simultaneously. We exemplify the procedure of multiperspectival normative assessment (MNA) using mediated reactions to terrorism as our case in point. We first identify the normative challenges related to the speed and substance of terrorism communication and the ways in which relations of solidarity are communicatively …
Stylistic Accommodation on an Internet Forum as Bonding: Do Posters Adapt to the Style of Their Peers
Internet forums are theorized to be important social platforms for peer influence. Current research tends to conceptualize peer influence as adoption processes, investigating whether information received from network contacts stimulate the adoption of a product, service, taste, or attitude. Accordingly, research interest is focused on the first time a product is used. In contrast, the present study investigates mutual and recurrent adaptation bet…
News selection criteria in the digital age: Professional norms versus online audience metrics
On newspaper websites, journalists can observe the preferences of the audience in unprecedented detail and for low costs, based on the audience clicks (i.e. page views) for specific news articles. This article addresses whether journalists use this information to cater to audience preferences in their news selection choices. We analyzed the print and online editions of five national newspapers from the Netherlands with a mixed-method approach. Us…
Quantitative analysis of large amounts of journalistic texts using topic modelling
The huge collections of news content which have become available through digital technologies both enable and warrant scientific inquiry, challenging journalism scholars to analyse unprecedented amounts of texts. We propose Latent Dirichlet Allocation (LDA) topic modelling as a tool to face this challenge. LDA is a cutting edge technique for content analysis, designed to automatically organize large archives of documents based on latent topics, m…
A Gatekeeper among Gatekeepers: News agency influence in print and online newspapers in the Netherlands
This paper investigates the influence of news agency Algemeen Nederlands Persbureau (ANP) on the coverage and diversity of political news in Dutch national newspapers. Using computational text analysis, we analyzed the influence on print newspapers across three years (1996, 2008, and 2013) and compared influence on print and online newspapers in 2013. Results indicate that the influence of ANP on print newspapers only increased slightly. Online n…
Text Analysis in R
Computational text analysis has become an exciting research field with many applications in communication research. It can be a difficult method to apply, however, because it requires knowledge of various techniques, and the software required to perform most of these techniques is not readily available in common statistical software packages. In this teacher’s corner, we address these barriers by providing an overview of general steps and operati…
Social media gatekeeping: An analysis of the gatekeeping influence of newspapers’ public Facebook pages
Due to the rising importance of social media platforms for news diffusion, newspapers are relying on social media editors to promote the distribution of their news items on these platforms. In this study, we investigate how much of an impact these social media editors really have, focusing on the impact of newspapers’ public pages on Facebook. Since the actions of individual users are not visible on many platforms due to privacy consideration, we…
Presenting News on Social Media: Media logic in the communication style of newspapers on Facebook
With the rising popularity of social media as news sources, a new common format element for presenting news has emerged: in addition to the classic headline, lead and picture, news organizations add a status message when they share their news articles on social media such as Twitter and Facebook. Based on media logic theory, we argue that the communication style of these messages is likely to be more interpersonal and subjective. To investigate t…
News through a social media filter: Different perspectives on immigration in news on website and social media formats
Social media have become important news sources, prompting news organizations to create social media accounts to publish news. This requires a medium-based translation, in which social media editors must remediate news – selecting and possibly re-interpreting content – to accommodate a different audience and format. In this study we investigate this remediation for the issue of immigration, comparing the news coverage of immigration on the websit…
Reproducible Extraction of Cross-lingual Topics (rectr)
With global media content databases and online content being available, analyzing topical structures in different languages simultaneously has become an urgent computational task. Some previous studies have analyzed topics in a multilingual corpus by translating all items into a single language using a machine translation service, such as Google Translate. We argue that this method is not reproducible in the long run and proposes a new method – R…
The Negation Bias in Stereotype Maintenance: A Replication in Five Languages
Research on linguistic biases shows that stereotypic expectancies are implicitly reflected in language and thereby subtly communicated to message recipients. Research on the Negation Bias shows that the use of negations (e.g., not stupid vs. smart) is more pronounced in descriptions of stereotype-inconsistent compared with stereotype-consistent behaviors. This article reports a replication study of the original research conducted in Dutch, using …
Linking event archives to news: A computational method for analyzing the gatekeeping process
Digital archives that document real-world events provide new opportunities for large-scale analyses of how news coverage represents reality. We present a method and open-source tool for linking event data to news articles, and demonstrate its application with an analysis of event and country level predictors of terrorism coverage in The Guardian from 2006 to 2018, using event data from the Global Terrorism Database (GTD). Our method builds on est…
Multiperspectival Normative Assessment: The Case of Mediated Reactions to Terrorism
This article provides a model for how communication phenomena can be normatively assessed using multiple normative perspectives simultaneously. We exemplify the procedure of multiperspectival normative assessment (MNA) using mediated reactions to terrorism as our case in point. We first identify the normative challenges related to the speed and substance of terrorism communication and the ways in which relations of solidarity are communicatively …
Linked in the dark: A network approach to understanding information flows within the Dutch Telegramsphere
Recent studies have shown that the stricter content moderation policies imposed by mainstream social networking sites (SNSs) stimulated the growth of low-moderated but relatively open discussion platforms such as Telegram. Despite Telegram’s growing popularity among (deplatformed) digital exiles, and high potential for news dissemination, information consumption, mobilization, and radicalization, little is known about information flows with respe…
Challenging the Global Cultural Conflict Narrative: An Automated Content Analysis on How PerPetrator Identity Shapes Worldwide News Coverage of Islamist and Right-Wing Terror Attacks
Recent terrorist attacks such as the Christchurch mosque attacks in 2019 renew the discussion of whether right-wing attacks are reported less negatively than Islamist attacks. To clarify this point, our study is the first to combine the selection of media inside and outside the West with a distinction between Islamist and right-wing attacks. We compare coverage given to thirty-two right-wing and forty Islamist attacks from 2015 to 2019 in nine We…
Advancing Automated Content Analysis for a New Era of Media Effects Research: The Key Role of Transfer Learning
The availability of individual-level digital trace data offers exciting new ways to study media uses and effects based on the actual content that people encountered. In this article, we argue that to really reap the benefits of this data, we need to update our methodology for automated text analysis. We review challenges for the automatic identification of theoretically relevant concepts in texts along three dimensions: format/style, language , a…
How shared ties and journalistic cultures shape global news coverage of disruptive media events: The case of the 9/11 terror attacks
In recent decades, disruptive media events, such as major terrorist attacks, have gained increasing relevance in news coverage around the world. Despite the growing importance of such globally broadcast media events, little research to date has examined cross-national variation in event coverage or the predictors of this variation. This study examines news coverage about the 9/11 terror attacks in the United States across 51 countries to analyze …
Fulfilling data access obligations: How could (and should) platforms facilitate data donation studies
Research into digital platforms has become increasingly difficult. One way to overcome these difficulties is to build on data access rights in EU data protection law, which requires platforms to offer users a copy of their data. In data donation studies, researchers ask study participants to exercise this right and donate their data to science. However, there is increasing evidence that platforms do not comply with designated laws. We first discu…
On Measurement Validity and Language Models: Increasing Validity and Decreasing Bias with Instructions
Language models like BERT or GPT are becoming increasingly popular measurement tools, but are the measurements they produce valid? Literature suggests that there is still a relevant gap between the ambitions of computational text analysis methods and the validity of their outputs. One prominent threat to validity is hidden biases in the training data, where models learn group-specific language patterns instead of the concept researchers want to m…
What is Popular Gets More Popular? Exploring Over-Time Dynamics in Article Readership Using Real-World Log Data
Online news can be shared and promoted via social media, mobile push messages, newsletters, "most read" boxes, or the like. This can result in feedback loops, in which views attract even more views. Using full click logs for five regional newspapers in the Netherlands, spanning N views = 12,108,263 views of N articles = 17,982 articles for each minute over the course of 13 weeks, we shed light on potential feedback loops. While article placement …
Less Annotating, More Classifying: Addressing the Data Scarcity Issue of Supervised Machine Learning with Deep Transfer Learning and Bert-NLI
Supervised machine learning is an increasingly popular tool for analyzing large political text corpora. The main disadvantage of supervised machine learning is the need for thousands of manually annotated training data points. This issue is particularly important in the social sciences where most new research questions require new training data for a new task tailored to the specific research question. This paper analyses how deep transfer learni…
Whose truth is it anyway? An experiment on annotation bias in times of factual opinion polarization
Information shapes citizens’ political decision-making. This process is amply studied by social scientists, for whom human annotation is a crucial instrument in their toolkit. Due to the democratization of data and the advances in NLP more data can be analyzed or classified, making these benchmarks more important than ever: An algorithm trained on biased data will reproduce and often exacerbate bias. Currently, disagreement and bias are often con…
Do news access pathways moderate filter bubbles? Evidence from a longitudinal analysis of data donations
News access pathways shape the informational diversity of users’ news repertoires, with distributed modes such as search and social media generally providing broader exposure than direct navigation. Yet whether these differences produce filter bubble dynamics—gradual narrowing of diversity over time—remains underevaluated. We provide a direct test using donated browsing histories from n = 179 users in the Netherlands spanning approximately 1 year…
Meaningful informed consent? How participants experience and understand data donation
Data donation makes it possible to invite participants to request and share their data from digital platforms for research purposes. While it is a user-centric approach to digital trace data collection, little is known about how participants experience and understand the data donation process. This study therefore asked twenty participants to verbalize their thoughts and actions as they went through data donation (from Google, YouTube, Facebook, …
Computer Science (18 works) · Political science (13 works) · Sociology (13 works) · Social Media and Politics (12 works) · Media studies (10 works) · Media Studies and Communication (8 works) · Advertising (7 works) · Business (7 works) · Computational and Text Analysis Methods (7 works) · Internet privacy (6 works)