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A Macroanalytic View of Swedish Literature using Topic Modeling.

Conference contribution
Authors Dimitrios Kokkinakis
Mats Malm
Published in Corpus Linguistics 2013 : abstract book (Lancaster) / edited by Andrew Hardie and Robbie Love
Publication year 2013
Published at Department of Literature, History of Ideas, and Religion
Department of Swedish
Language en
Links ucrel.lancs.ac.uk/cl2013/doc/CL2013...
Subject categories Language Technology (Computational Linguistics), Computational linguistics

Abstract

New research opportunities are plentiful for digital and literature scholars who are currently faced with increasingly large portions of large digitized archives produced during the last decades. Conventional methods of analysis involving a so called close reading view are not enough. Distant reading or macroanalysis is proposed instead, as a better, viable and more pragmatic alternative to the traditional methods of analyzing e.g., literature. According to this view, understanding literature is not accomplished by studying individual texts, but by aggregating and analyzing massive amounts of data. Therefore, applying macroanalytic methods and technologies is a priority among many research groups in the humanities worldwide. In this paper we explore topic modeling, an increasingly popular statistical method used for uncovering themes, topics and patterns in large amounts of text. We use available topic modeling software and, as empirical data, the content of the Swedish literature bank, a constantly growing body of Swedish fiction corpus from the 18th and 19th century. We present preliminary results on a sample of this corpus and discuss how humanistic research can be conducted through this type of computation, as a means to identify potential issues of interest e.g., for historians.

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