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Text Analytics: Present, Past and Future Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Topic Modeling of Twitter Conversations: The Case of the National University of Colombia

Authors : Eliana Sanandres, Raimundo Abello, Camilo Madariaga

Published in: Text Analytics

Publisher: Springer International Publishing

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Abstract

Topic modeling provides a useful method for finding symbolic representations of ongoing social events, which represent claims about the shape of social reality, its causes and the responsibility for action such causes imply. It has received special attention among social researchers in the last decade. During this time, Twitter has acted as the most common platform for people to share narratives about social events. This study proposes Latent Dirichlet Allocation (LDA) based topic modeling of Twitter conversations to determine the topics shared on Twitter about the financial crisis in the National University of Colombia. We downloaded all tweets that included the hashtag #CrisisUNAL (UNAL is the Spanish acronym for National University of Colombia) using the Twitter API interface and analyzed over 45,000 tweets published between 2011 and 2015. The results illustrate the strength of topic modeling for analyzing large text corpora and provide a way to study new emerging information that people share on Twitter.

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previous chapter Where Are the Social Sciences Going to? The Case of the EU-Funded SSH Research Projects
next chapter Analyzing Occupational Safety Culture Through Mass Media Monitoring
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Metadata
Title
Topic Modeling of Twitter Conversations: The Case of the National University of Colombia
Authors
Eliana Sanandres
Raimundo Abello
Camilo Madariaga
Copyright Year
2020
Book
Text Analytics

Print ISBN: 978-3-030-52679-5

Electronic ISBN: 978-3-030-52680-1

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-52680-1_19

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