Digital humanities scholars strongly need a corpus exploration method that provides topics
easier to interpret than standard LDA topic models. To move towards this goal, here we …

In this paper we present TopFish, a multilevel computational method that integrates topic
detection and political scaling and shows its applicability for a temporal aspect analysis of …

In recent years a common trend characterised by the adoption of text mining methods for the
study of digital sources emerged in digital humanities, often in opposition to traditional …

Social sciences and Humanities research is often based on large textual corpora, that it
would be unfeasible to read in detail. Natural Language Processing (NLP) can identify …

Entity disambiguation is extremely important in knowledge construction. The word
representation model ignores the influence of the ordering between words on the sentence …

The goal of this thesis is to understand the impact that the transition from analogue to born-
digital sources will have on the way historians collect, analyse and select primary evidences …

In recent years, the Latent Dirichlet allocation (LDA) topic model (Blei, Ng, and Jordan,
2003) has become one of the most employed text mining techniques (Meeks and Weingart …