A position paper describes goals of a specific project. Sponsorship is required. A fine description of all packages is useful to understand complementariy of each contribution in the framework of the project.

Linguistic Fingerprints on Translation's Lens

J.D. Porter ; Yulia Ilchuk ; Quinn Dombrowski.
What happens to the language fingerprints of a work when it is translated into another language? While translation studies has often prioritized concepts of equivalence (of form and function), and of textual function, digital humanities methodologies can provide a new analytical lens onto ways that stylistic traces of a text's source language can persist in a translated text. This paper presents initial findings of a project undertaken by the Stanford Literary Lab, which has identified distinctive grammatical features in short stories that have been translated into English. While the phenomenon of "translationese" has been well established particularly in corpus translation studies, we argue that digital humanities methods can be valuable for identifying specific traits for a vision of a world atlas of literary style.

Extracting Keywords from Open-Ended Business Survey Questions

Barbara McGillivray ; Gard Jenset ; Dominik Heil.
Open-ended survey data constitute an important basis in research as well as for making business decisions. Collecting and manually analysing free-text survey data is generally more costly than collecting and analysing survey data consisting of answers to multiple-choice questions. Yet free-text data allow for new content to be expressed beyond predefined categories and are a very valuable source of new insights into people's opinions. At the same time, surveys always make ontological assumptions about the nature of the entities that are researched, and this has vital ethical consequences. Human interpretations and opinions can only be properly ascertained in their richness using textual data sources; if these sources are analyzed appropriately, the essential linguistic nature of humans and social entities is safeguarded. Natural Language Processing (NLP) offers possibilities for meeting this ethical business challenge by automating the analysis of natural language and thus allowing for insightful investigations of human judgements. We present a computational pipeline for analysing large amounts of responses to open-ended questions in surveys and extract keywords that appropriately represent people's opinions. This pipeline addresses the need to perform such tasks outside the scope of both commercial software and bespoke analysis, exceeds the performance to state-of-the-art systems, and performs this task in a transparent way that allows for scrutinising and exposing […]