… model architectures underlying our experiments in cross-lingual sentiment analysis in the
pharmaceutical domain: Translation Pipeline and Crosslingual Projection. Both of them are …

… evaluate crosslingual sentence understanding, where models have to be trained in one
language and tested in different ones. We evaluate several approaches to cross-lingual learning …

… developing sentiment analysis models that predict sentiment at a more fine-grained level
than at the level of a complete document. A paradigm coined as Aspect-based Sentiment Anal…

… quantitative text analysis. Responding to the unique challenges research faces in
multilingual analysis, we provide a systematic overview of multilingual text analysis methods …

… -level cross-lingual sentiment classification. While some works focus on aspect-level sentiment
analysis, they may not address the challenges of cross-domain sentiment classification. …

… Using this data and machine translation models, we can learn cross-lingual sentence-level …
In this work, we perform sentiment analysis of code-mixed text. Our choice of this tasks is moti…

… cross-lingual models: multilingual BERT and XLM RoBERTa. We fine-tune the models for
part-of-speech tagging and sentiment analysis … typology than sentiment analysis and that the …

Multilingual sentence embeddings capture rich semantic information not only for measuring
similarity between texts but also for catering to a broad range of downstream cross-lingual …

… In contrast, the approach we consider in this paper effectively enables zero-shot cross-lingual
transfer in sentiment analysis without the need for external bilingual resources. …

… Cross-lingual sentiment analysis Cross-lingual sentiment analysis consists in using annotated
data in a source language (almost always English) to compensate for the lack of labelled …