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Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis

2020

With the growth of online social network platforms and applications, large amounts of textual user-generated content are created daily in the form of comments, reviews, and short-text messages. As a result, users often find it challenging to discover useful information or more on the topic being discussed from such content. Machine learning and natural language processing algorithms are used to analyze the massive amount of textual social media data available online, including topic modeling techniques that have gained popularity in recent years. This paper investigates the topic modeling subject and its common application areas, methods, and tools. Also, we examine and compare five frequen…

Topic modelshort textInformation retrievalSocial networkbusiness.industryLatent semantic analysisComputer scienceRandom projectiontopic modelingUser-generated contentSubject (documents)Context (language use)Latent Dirichlet allocationlcsh:QA75.5-76.95symbols.namesakeArtificial Intelligenceonline social networkssymbolsMethodslcsh:Electronic computers. Computer sciencenatural language processingbusinessuser-generated contentFrontiers in Artificial Intelligence
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