Ms S.A.M. (Susan) Vermeer MSc
Faculty of Social and Behavioural Sciences
CW : Political Communication & Journalism
Nieuwe Achtergracht 166 Room number: C8.00
1001 NG Amsterdam
News for you! News consumption in a world of news sites, algorithms, and social media.
Who is exposed to what kind of news? Citizens, especially younger adults, are increasingly and predominantly using online and social media to get informed about the world around them. They are often directed to news via their social networks (e.g., Facebook) and via algorithmic news recommender systems. By analysing citizens in an online media ecosystem, this project tackles the question how content features, consumer features and context features interact in shaping news exposure and, ultimately, political interest and political participation. By doing so, we aim to better understand news use, the existence of echo chambers and filter bubbles, and their effect in the evolving media landscape.
- Vermeer, S. (Author). (2018). A supervised machine learning method to classify Dutch-language news items. Software, Retrieved from https://figshare.com/articles/A_supervised_machine_learning_method_to_classify_Dutch-language_news_items/7314896/1
- Vermeer, S., Araujo, T. B., van Noort, G., & Bernritter, S. F. (2017). Getting a handle on webcare: Comparing automated content analysis techniques to detect eWOM messages. Abstract from ICORIA, Ghent, Belgium.
- Vermeer, S., Araujo, T. B., van Noort, G., & Bernritter, S. F. (2017). Webcare as a well-oiled machine: A machine learning approach to identify eWOM messages that require a webcare response. Abstract from Etmaal 2017: , Tilburg , Netherlands.
- No ancillary activities