Luca Pinto

Structural Topic Model for Social and Political Sciences

Are you already subscribed?
Login to check whether this content is already included on your personal or institutional subscription.

Abstract

The study of what social and political actors say and write can improve our understanding of political conflict and social interactions. To this purpose, scholars have developed several automated content methods to analyse large collections of texts. This note focuses on the structural topic model: a machine learning technique aimed at identifying topics in large-scale text collections with extensions that facilitate the inclusion of document-level metadata.

Keywords

  • Automated Content Analysis
  • Big Data
  • Data Science
  • Statistical Analysis of Texts
  • Topic Model

Preview

Article first page

What do you think about the recent suggestion?

Trova nel catalogo di Worldcat