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Automated Generation of Latent Topics on Emerging Technologies from YouTube Video Content

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dc.contributor.author Daniel, Clinton
dc.contributor.author Dutta, Kaushik
dc.date.accessioned 2017-12-28T00:53:16Z
dc.date.available 2017-12-28T00:53:16Z
dc.date.issued 2018-01-03
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50109
dc.description.abstract Topic modeling has been widely adopted by researchers for a variety of different research problems that involve the mining of text corpora to generate a latent set of topics. Specifically, the Latent Dirichlet Allocation (LDA) algorithm is well documented within academic literature in terms of its application and automated topic generation from data sources such as blogs, social media, and other text collections. YouTube now offers access to over a billion auto-generated video transcript documents that have been recorded and posted to its social platform. The availability of this data offers an opportunity for researchers to investigate a variety of topics that are being discussed and posted to the platform. Specifically, we will study, using the LDA algorithm, discussions related to emerging technologies that have been posted on YouTube to better understand what latent topics can be auto-generated and what kind of methodology can be used to analyze this data.
dc.format.extent 9 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Data Analytics, Data Mining and Machine Learning for Social Media
dc.subject Social Media Analytics, Topic Modeling, Machine Learning, YouTube
dc.title Automated Generation of Latent Topics on Emerging Technologies from YouTube Video Content
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2018.222
Appears in Collections: Data Analytics, Data Mining and Machine Learning for Social Media


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