NLP

The main goal of machine translation has been to convey the correct content. Stylistic considerations have been at best secondary. We show that as a consequence, the output of three commercial machine translation systems (Bing, DeepL, Google) make …

Geotagged Twitter data allows us to investigate correlations of geographic language variation, both at an interlingual and intralingual level. Based on data-driven studies of such relationships, this paper investigates regional variation of language …

When interacting with each other, we motivate, advise, inform, show love or power towards our peers. However, the way we interact may also hold some indication on how successful we are, as people often try to help each other to achieve their goals. …

Recently, Natural Language Processing (NLP) has witnessed an impressive progress in many areas, due to the advent of novel, pretrained contextual representation models. In particular, Devlin et al. (2019) proposed a model, called BERT (Bidirectional …

Incorporating Demographic Factors into Natural Language Processing Models

Mixed methods for analyzing political parties’ promises to voters during election campaigns

MONItoring Coverage, Attitudes and Accessibility of Italian measures in response to COVID-19

Devising Metrics for Assessing Echo Chambers, Incivility, and Intolerance on Twitter

Recently, Peterson et al. provided evidence of the benefits of using probabilistic soft labels generated from crowd annotations for training a computer vision model, showing that using such labels maximizes performance of the models over unseen data. …

Identifying deceptive online reviews is a challenging tasks for Natural Language Processing (NLP). Collecting corpora for the task is difficult, because normally it is not possible to know whether reviews are genuine. A common workaround involves …