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Ecstasy use discussion in Dutch current affairs TV programs. A methodological exploration of Automatic Speech Recognition metadata

Authors: van der Molen, Berrie Jens;

Ecstasy use discussion in Dutch current affairs TV programs. A methodological exploration of Automatic Speech Recognition metadata

Abstract

The Netherlands is known for a lenient party drug policy climate and for high ecstasy (MDMA) use prevalence. In 2020, ecstasy use prevalence in The Netherlands was higher than in any other European country. This topic deserves investigation, as recently the question whether the illegal yet widely used party drug should be regulated instead of banned is recurring in political, public and scientific contexts. In this paper, recent Dutch current affairs television programs are analyzed to untangle the reputation of ecstasy in The Netherlands. Research about ecstasy in historical media debates has shown that Automatic Speech Recognition or ASR (speech-to-text) enrichment can be used to explore radio debates in a way that is comparable to how newspaper debates can be researched using Optical Character Recognition metadata, offering great potential for cross-media public debate research: topics can be researched in their socio-historical context across print news and radio news. Now, the CLARIAH Media Suite is unlocking the Dutch digitized public television archive for similar research with searchable ASR metadata. The television programs can be analyzed using techniques such as keyword search, timeline visualization and word frequency lists. This raises a methodological question to go with the question about ecstasy’s reputation: how can the coverage of ecstasy use in a fundamentally visual data archive be effectively explored with search techniques that are based exclusively on the spoken word? Answers are sought by comparing the results of close analysis of relevant television programs with the findings based on ASR metadata analysis.

Research fellowship 'Exploring ASR-enriched Television Debates' is funded by CLARIAH (www.clariah.nl)

Related Organizations
Keywords

Digital Humanities, Ecstasy, Television Studies, Public Debate Analysis, Automatic Speech Recognition

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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