Targeted aspect-based sentiment analysis for Lithuanian social media reviews

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Collection:
Mokslo publikacijos / Scientific publications
Document Type:
Knygos dalis / Part of the book
Language:
Anglų kalba / English
Title:
Targeted aspect-based sentiment analysis for Lithuanian social media reviews
Authors:
In the Book:
Human language technologies - the Baltic perspective : proceedings of the 9th international conference, Baltic HLT 2020 / edited by Andrius Utka, Jurgita Vaičenonienė, Jolanta Kovalevskaitė, Danguolė Kalinauskaitė. Amsterdam: IOS Press, 2020. P. 32-38. (Frontiers in artificial intelligence and applications)
Subject Category:
LT
Žiniasklaida / Mass media; Socialinis mokslas / Social science.
Summary / Abstract:

ENThe paper presents research results for solving the task of targeted aspect-based sentiment analysis in the specific domain of Lithuanian social media reviews. Methodology, system architecture, relevant NLP tools and resources are described, finalized by experimental results showing that our solution is suitable for solving targeted aspect-based sentiment analysis tasks for under-resourced, morphologically rich and flexible word order languages. Keywords. Targeted aspect-based sentiment analysis, entity recognition, deep learning, social media. [From the publication]

DOI:
10.3233/FAIA200599
ISBN:
9781643681160
Subject:
Sociologija / Sociology
Permalink:
https://www.lituanistika.lt/content/103487
Updated:
2023-12-22 18:05:14
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