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About the database ScholarIQanswers from OpenAlex & ORCID
How has Mark Boukes's publication output changed over time?
ScholarIQpublication output · 2015–2025
Output grew0% over the shown period — from 1 works in 2015 to 1 in 2025.
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2015201620172018201920212025
What are the most-cited papers on Mark Boukes?
ScholarIQmost cited works
The Validity of Sentiment Analysis: Comparing Manual Annotation, Crowd-Coding, Dictionary Approaches, and Machine Learning Algorithms
Wouter van Atteveldt, Mariken Anna Catharina Geertruida van der Velden, Mark Boukes
S193040567. 2021396 CitationsOPEN ACCESS
News Avoidance during the Covid-19 Crisis: Understanding Information Overload
Kiki de Bruin, Yael de Haan, Rens Vliegenthart, Sanne Kruikemeier, Mark Boukes
Digital Journalism. 2021155 CitationsOPEN ACCESS
The Softening of Journalistic Political Communication: A Comprehensive Framework Model of Sensationalism, Soft News, Infotainment, and Tabloidization
Lukas Otto, Isabella Glogger, Mark Boukes
S103253184. 2016139 CitationsOPEN ACCESS
What’s the Tone? Easy Doesn’t Do It: Analyzing Performance and Agreement Between Off-the-Shelf Sentiment Analysis Tools
Mark Boukes, Bob van de Velde, Theo Araujo, Rens Vliegenthart
S193040567. 2019136 CitationsOPEN ACCESS
Linking Survey and Media Content Data: Opportunities, Considerations, and Pitfalls
Claes H. de Vreese, Mark Boukes, Andreas Schuck, Rens Vliegenthart, L. Bos, Yph Lelkes
S193040567. 2017126 CitationsOPEN ACCESS
Related on ScholarIQ
Georgetown University
Institution
The Validity of Sentiment Analysis: Comparing Manual Annotation, Crowd-Coding, Dictionary Approaches, and Machine Learning Algorithms
Paper
News Avoidance during the Covid-19 Crisis: Understanding Information Overload
Paper
The Softening of Journalistic Political Communication: A Comprehensive Framework Model of Sensationalism, Soft News, Infotainment, and Tabloidization
Paper
What’s the Tone? Easy Doesn’t Do It: Analyzing Performance and Agreement Between Off-the-Shelf Sentiment Analysis Tools
Paper
Linking Survey and Media Content Data: Opportunities, Considerations, and Pitfalls
Paper