Giovanni Moretti

ALCIDE: Extracting and visualising content from large document collections to support humanities studies

Abstract The application of research practices and methodologies from the Information and Communication Technologies to Humanities studies is having a great impact on the way humanities research is being conducted. However, although many applications have been developed to automatically analyse document collections from the historical or the literary domain, they often fail to provide a real support to scholars because of their inherent complexity: technical skills are often required to use them and to inspect their output. On the other hand, some systems are more user-friendly, but present basic analyses and are limited to the needs of a specific research community. In order to overcome the aforementioned limitations, we developed ALCIDE ( Analysis of Language and Content In a Digital Environment ), a web-based platform designed to assist humanities scholars in navigating and analysing large quantities of textual data such as historical sources and literary works. This suite of tools combines advanced text processing techniques with intuitive visualisations of the output to serve a broad range of research questions, which no other comparable tool can address in a single platform. Textual corpora can be inspected and compared along five semantic dimensions: who, where, when, what and how. Such dimensions in different combinations allow targeting many key questions of different humanities disciplines, as shown in the five use cases presented.

Comparing two methods for crowdsourcing speech transcription

This paper presents the results of an experimental study conducted with the aim of comparing two methods for crowdsourcing speech transcription that incorporate two different quality control mechanisms (i.e. explicit versus implicit) and that are based on two different processes (i.e. parallel versus iterative). In the Gold Standard method the same speech segment is transcribed in parallel by multiple contributors whose reliability is checked with respect to some reference transcriptions provided by experts. On the other hand, in the Dual Pathway method two independent groups of contributors work on the same set of transcriptions refining them in an iterative way until they converge, and thus eliminating the need to have reference transcriptions and to check transcription quality in a separate phase. These two methods were tested on about half an hour of broadcast news speech and for two different European languages, namely German and Italian. Both methods obtained good results in terms of Word Error Rate (WER) and compare well with the word disagreement rate of experts on the same data.

Towards sentiment analysis for historical texts

This article presents the integration of sentiment analysis in ALCIDE, an online platform for historical content analysis. A prior polarity approach has been applied to a corpus of Italian historical texts, and a new lexical resource has been developed with a semi-automatic mapping starting from two English lexica. This article also reports on a first experiment on contextual polarity using both expert annotators and crowdsourced contributors. The long-term goal of our research is to create a system to support historical studies, which is able to analyse the sentiment in historical texts and to discover the opinion about a topic and its change over time.

The New Release of CORPS: A Corpus of Political Speeches Annotated with Audience Reactions

In this paper we present the new release of CORPS CORpus of tagged Political Speeches that contains transcripts of political speeches tagged with audience reactions, such as APPLAUSE or LAUGHTER. The corpus has been built with the goal of allowing automatic processing of the stored data. These tags signal hot-spots about persuasive communication and can be usefully employed in many theoretical and applied fields, providing insights well beyond those of traditional word-count approaches. After introducing the main characteristics of the corpus and some quantitative descriptions, we discuss possible uses of this resource.

A Knowledge Management Architecture for Digital Cultural Heritage

The increasing demand of technological facilities for galleries, museums, and archives has led to the need for designing practical and effective solutions for managing the digital life cycle of cultural heritage collections. These facilities have to support users in addressing several challenges directly related to the creation, management, preservation, and visualization of digital collections. Such challenges include, for example, the support for a collaborative management of the produced information, their curation from a multilingual perspective to break the language barriers and make collections available to different stakeholders, and the development of services for exposing structured version of data both to users and machines. Platforms satisfying all of these requirements have to support curators activities and, at the same time, provide facilities for engaging the virtual consumers of the produced data. In this article, we propose a description of an abstract architecture for managing digital collections built on a set of components, services, and APIs able to address the challenges mentioned previously. An instantiation of this architecture is discussed, and we present a use case concerning the management of a digital archive of verbo-visual art. Lessons learned from this experience are reported to outline future activities.