Following our earlier session on quantitative textual analysis, Sophie Mützel will introduce us to applications of topic models. Originally, developed in computer science, machine learning, and natural language processing, topic models have recently gained increased attention in digital humanities, but also in the social sciences. Based on a particular probabilistic distribution, topic model algorithms cluster together words into "topics" without a priori coding by analysts. Topic modeling thus can be used as a tool to discover themes in large collections of documents.
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Wzbaktiv
2012
Collective volumes
Becker, Rolf/Solga, Heike (Hg.) (2012): Soziologische Bildungsforschung. Kölner Zeitschrift für Soziologie und Sozialpsychologie, Sonderheft 52. Wiesbaden: Springer VS, 503 S.
Articles in reviewed journals
Buis, Maarten L. (2012): "Stata Tip 112. Where Did My p-Values Go? (Part 2)". In: The Stata Journal, Vol. 12, No. 4, S. 759-760.
Dieckhoff, Martina/Steiber, Nadia (2012): "Institutional Reforms and Age-graded Labour Market Inequalities in Europe". In: International Journal of Comparative Sociology, Vol. 53, No. 2, S. 97-119.
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Staff member of the
fon
romy.brunner [at] wzb.eu
room
A 006
Tuesday, 11 June 2013
Subtitle
Co:Sta Presentation by Sophie Mützel (WZB)
Description
Tuesday, 11 June 2013
Start: 1:00 pm