Using lexical level information in discourse structures for Basque
            sentiment analysis

Alkorta, Jon; Gojenola, Koldo; Iruskieta, Mikel; Taboada, Maïté

doi:10.18653/v1/w17-3606

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…The co-official languages, however, have almost none. The authors are aware of a small discourse-related sentiment corpus available in Basque (Alkorta et al, 2015), as well as a stance corpus in Catalan (Bosco et al, 2016). These resources, however, are limited in size and scope.…”

Section: Related Workmentioning

confidence: 99%

MultiBooked: A Corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification

Barnes¹,

Lambert²,

Badía³

2018

Preprint

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While sentiment analysis has become an established field in the NLP community, research into languages other than English has been hindered by the lack of resources. Although much research in multi-lingual and cross-lingual sentiment analysis has focused on unsupervised or semi-supervised approaches, these still require a large number of resources and do not reach the performance of supervised approaches. With this in mind, we introduce two datasets for supervised aspect-level sentiment analysis in Basque and Catalan, both of which are under-resourced languages. We provide high-quality annotations and benchmarks with the hope that they will be useful to the growing community of researchers working on these languages.

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Section: Related Workmentioning

confidence: 99%

MultiBooked: A Corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification

Barnes¹,

Lambert²,

Badía³

2018

Preprint

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“…This first RST parser for Basque represents a step forward to the use of discourse information in summarisation , sentiment analysis (Alkorta et al, 2017) and in many other advanced tasks.…”

Section: Results and Future Workmentioning

confidence: 99%

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Iruskieta¹,

Braud²

2019

Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019

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Development of discourse parsers to annotate the relational discourse structure of a text is crucial for many downstream tasks. However, most of the existing work focuses on English, assuming a quite large dataset. Discourse data have been annotated for Basque, but training a system on these data is challenging since the corpus is very small. In this paper, we create the first parser based on RST for Basque, and we investigate the use of data in another language to improve the performance of a Basque discourse parser. More precisely, we build a monolingual system using the small set of data available and investigate the use of multilingual word embeddings to train a system for Basque using data annotated for another language. We found that our approach to building a system limited to the small set of data available for Basque allowed us to get an improvement over previous approaches making use of many data annotated in other languages. At best, we get 34.78 in F1 for the full discourse structure. More data annotation is necessary in order to improve the results obtained with these techniques. We also describe which relations match with the gold standard, in order to understand these results.

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“…This first RST parser for Basque represents a step forward to the use of discourse information in summarisation (Atutxa et al, 2017), sentiment analysis (Alkorta et al, 2017) and in many other advanced tasks.…”

Section: Results and Future Workmentioning

confidence: 99%

Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019

2019

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This overview summarizes the main contributions of the accepted papers at the 2019 workshop on Discourse Relation Parsing and Treebanking (DISRPT 2019). Co-located with NAACL 2019 in Minneapolis, the workshop's aim was to bring together researchers working on corpus-based and computational approaches to discourse relations. In addition to an invited talk, eighteen papers outlined below were presented, four of which were submitted as part of a shared task on elementary discourse unit segmentation and connective detection.

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Using lexical level information in discourse structures for Basque sentiment analysis

Cited by 5 publications

References 12 publications

MultiBooked: A Corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification

MultiBooked: A Corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification

Untitled

Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019

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