Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic
Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media
The paper focuses on a large collection of Dutch tweets from the Netherlands to get an insight into the perception and reactions of users during the early months of the COVID-19 pandemic. We focused on five major user communities of users: government and health organizations, news media, politicians, the general public and conspiracy theory supporters, investigating differences among them in topic dominance and the expressions of emotions. Through topic modeling we monitor the evolution of the conversation about COVID-19 among these communities. Our results indicate that the national focus on COVID-19 shifted from the virus itself to its impact on the economy between February and April. Surprisingly, the overall emotional public response appears to be substantially positive and expressing trust, although differences can be observed in specific group of users.
Neural Machine Translation for English–Kazakh with Morphological Segmentation and Synthetic Data
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
This paper presents the systems submitted by the University of Groningen to the English– Kazakh language pair (both translation directions) for the WMT 2019 news translation task. We explore the potential benefits of (i) morphological segmentation (both unsupervised and rule-based), given the agglutinative nature of Kazakh, (ii) data from two additional languages (Turkish and Russian), given the scarcity of English–Kazakh data and (iii) synthetic data, both for the source and for the target language. Our best submissions ranked second for Kazakh→English and third for English→Kazakh in terms of the BLEU automatic evaluation metric.
Reliable Discourse Markers for Contrast Relations
Proceedings of the Eight International Conference on Computational Semantics