This paper describes the creation and annotation of a dataset consisting of 250 English and Spanish app store reviews from Google’s Play Store with Appraisal features. This is one of the most influential linguistic frameworks for the analysis of evaluation and opinion in discourse due to its insightful descriptive features. However, it has not been extensively applied in NLP in spite of its potential for the classification of the subjective content of these reviews. We describe the dataset, the annotation scheme and guidelines, the agreement studies, the annotation results and their impact on the characterisation of this genre.

In this paper we present current work on the design and validation of a linguistically-motivated annotation model of modality in English and Spanish in the context of the MULTINOT project. Our annotation model captures four basic modal meanings and their subtypes, on the one hand, and provides a fine-grained characterisation of the syntactic realisations of those meanings in English and Spanish, on the other. We validate the modal tagset proposed through an agreement study performed on a bilingual sample of four hundred sentences extracted from original texts of the MULTINOT corpus, and discuss the difficult cases encountered in the annotation experiment. We also describe current steps in the implementation of the proposed scheme for the large-scale annotation of the bilingual corpus using both automatic and manual procedures.