Efficiently exploiting all sources of information such as labeled instances, classes'
representation, and relations of them has a high impact on the performance of Multi-Label …

In this paper, we propose an approach for cross-lingual topical coding of sentences from
electoral manifestos of political parties in different languages. To this end, we exploit …

Political text scaling aims to linearly order parties and politicians across political dimensions
(eg, left-to-right ideology) based on textual content (eg, politician speeches or party …

Many tasks in text-based computational social science (CSS) involve the classification of
political statements into categories based on a domain-specific codebook. In order to be …

General political topics, like social security and foreign affairs, recur in electoral manifestos
across countries. The Comparative Manifesto Project collects and manually codes …

Election manifestos document the intentions, motives, and views of political parties. They are
often used for analysing a party's fine-grained position on a particular issue, as well as for …

Many pledges are made in the course of an election campaign, forming important corpora
for political analysis of campaign strategy and governmental accountability. At present, there …

With the rise of computational social science, many scholars utilize data analysis and natural
language processing tools to analyze social media, news articles, and other accessible data …

Election manifestos document the intentions, motives, and views of political parties. They are
often used for analysing party policies and positions on various issues, as well as for …

Probabilistic topic models are powerful methods to uncover hidden thematic structures in
text by projecting each document into a low dimensional space spanned by a set of topics …