This workshop introduces two user-friendly applications, namely Language Variation Suite and Interactive Text Mining Suite, that allow researchers visually explore and statistically analyze language data. Written in R with Shiny app, these applications not only provide a web interactive interface, they also allow researchers implement state-of-the-art statistical methods, such as cluster analysis, topic modeling, inferential trees and mixed model logistic regressions.
33. Introduction
Language
Variation
Suite
Visual
Analytics for
Digital
Humanities
Interactive
Text Mining
Suite
Conclusion
References
Digital Humanity Manifesto 2.0 (2009) and Berry
(2011)
1st Wave: “The first wave of digital humanities work was
quantitative, mobilizing the search and retrieval
powers of the database, automating corpus
linguistics, stacking hypercards into critical
arrays”
2nd Wave: “The second wave is qualitative, interpretive”,
concentrating on new tools for creating and
curating digital repositories (Berry, 2011)
3rd Wave: Concentration on the computationality, search,
retrieval and analysis originated in
humanity-based work
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54. Introduction
Language
Variation
Suite
Visual
Analytics for
Digital
Humanities
Interactive
Text Mining
Suite
Conclusion
References
References I
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Cambridge University Press
[2] Bentivoglio, Paola and Mercedes Sedano. 1993. Investigaci´on socioling¨u´ıstica: sus m´etodos aplicados a
una experiencia venezolana. Bolet´ın de Ling¨u´ıstica 8. 3-35
[3] Gries, Stefan Th. 2015. Quantitative designs and statistical techniques. In Douglas Biber Randi
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University Press
[4] Jockers, Matthew. 2014. Text Analysis with R for Students of Literature. Quantitative Methods in the
Humanities and Social Sciences. Springer International Publishing, Cham
[5] Labov, W. 1966. The Social Stratification of English in New York City. Washington: Center for Applied
Linguistics
[6] Moretti, Franco. 2005. Graphs, Maps, Trees: Abstract Models for a Literary History. Verso
[7] Oelke, Daniella, Dimitrios Kokkinakis, and Mats Malm. 2012. Advanced visual analytics methods for
literature analysis. Proceedings of the 6th EACL Workshop on Language Technology for Cultural
Heritage, Social 561Sciences, and Humanities, pages 3544
[8] Passarotti, Marco, Barbara McGillivray, and David Bamman. “A Treebank-based Study on Latin Word
Order.” In proceedings of 16th International Colloquium on Latin Linguistics, At Uppsala, Sweden.
2013, 340–352
[9] Schnapp, Jeffrey, and Peter Presner. 2009. Digital Humanities Manifesto 2.0.
[10] http://blog.kandu.com/post/57065268403/book-reading-gif
[11] http://cdn.business2community.com/wp-content/uploads/2014/09/archives01.jpg
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