Commenting on local politics: An analysis of YouTube video comments for local government videos
Coats, Steven
Asociacion Espanola de Linguistica de Corpus
Coats, S. (2024). Commenting on local politics: An analysis of YouTube video comments for local government videos. Research in corpus linguistics 13(1), 1-25. https://doi.org/10.32714/ricl.13.01.02
https://creativecommons.org/licenses/by/4.0/
Research in Corpus Linguistics is a fully open access journal. All content is freely and immediately accessible to readers under a liberal CC-BY license.
https://creativecommons.org/licenses/by/4.0/
Research in Corpus Linguistics is a fully open access journal. All content is freely and immediately accessible to readers under a liberal CC-BY license.
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202409256058
https://urn.fi/URN:NBN:fi:oulu-202409256058
Tiivistelmä
Abstract
This study compares the content of transcripts of videos uploaded by local governments with the comments on those videos, utilizing three transformer-model-based techniques: summarization of the discourse content of video transcripts, topic modeling of summarized transcripts, and sentiment analysis of transcripts and of comments. The analysis shows that some types of video content, for example those dealing with music or education, are more likely to attract positive comments than content related to policing or government meetings. In addition to their potential relevance for local government outreach, the study may represent a viable exploratory method for comparison of online video content and written comments in the context of computational social science analyses of user interaction and commenting behavior.
This study compares the content of transcripts of videos uploaded by local governments with the comments on those videos, utilizing three transformer-model-based techniques: summarization of the discourse content of video transcripts, topic modeling of summarized transcripts, and sentiment analysis of transcripts and of comments. The analysis shows that some types of video content, for example those dealing with music or education, are more likely to attract positive comments than content related to policing or government meetings. In addition to their potential relevance for local government outreach, the study may represent a viable exploratory method for comparison of online video content and written comments in the context of computational social science analyses of user interaction and commenting behavior.
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