Texts are among the most relevant data sources for social scientists, and traditionally researchers adopt qualitative methods for dealing with them. Yet, new computer aided techniques offer promising methodological avenues for scholars, which can now deal with big corpora of texts. One of the techniques that recently gained more relevance is Topic Modelling, which permits extracting bag of words which co-occur often in texts. While Topic Modelling was fruitfully used in sociology and management, existing software for performing it requires coding skills, and are not user friendly. In this paper we present MITAO, a new graphic-based, user friendly, open source software for performing topic modelling and other analysis on textual data.

MITAO: A User Friendly and Modular Software for Topic Modelling

Ferri, Paolo;Heibi, Ivan;Pareschi, Luca;Peroni, Silvio
2020

Abstract

Texts are among the most relevant data sources for social scientists, and traditionally researchers adopt qualitative methods for dealing with them. Yet, new computer aided techniques offer promising methodological avenues for scholars, which can now deal with big corpora of texts. One of the techniques that recently gained more relevance is Topic Modelling, which permits extracting bag of words which co-occur often in texts. While Topic Modelling was fruitfully used in sociology and management, existing software for performing it requires coding skills, and are not user friendly. In this paper we present MITAO, a new graphic-based, user friendly, open source software for performing topic modelling and other analysis on textual data.
2020
Ferri, Paolo; Heibi, Ivan; Pareschi, Luca; Peroni, Silvio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/778658
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