{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pars-absa-an-aspect-based-sentiment-analysis","title":"Pars-ABSA: an Aspect-based Sentiment Analysis dataset for Persian","arxiv_id":"1908.01815","date":"2019-07-26","proceeding":null,"authors":["Taha Shangipour Ataei","Kamyar Darvishi","Soroush Javdan","Behrouz Minaei-Bidgoli","Sauleh Eetemadi"],"abstract":"Due to the increased availability of online reviews, sentiment analysis had been witnessed a booming interest from the researchers. Sentiment analysis is a computational treatment of sentiment used to extract and understand the opinions of authors. While many systems were built to predict the sentiment of a document or a sentence, many others provide the necessary detail on various aspects of the entity (i.e. aspect-based sentiment analysis). Most of the available data resources were tailored to English and the other popular European languages. Although Persian is a language with more than 110 million speakers, to the best of our knowledge, there is a lack of public dataset on aspect-based sentiment analysis for Persian. This paper provides a manually annotated Persian dataset, Pars-ABSA, which is verified by 3 native Persian speakers. The dataset consists of 5,114 positive, 3,061 negative and 1,827 neutral data samples from 5,602 unique reviews. Moreover, as a baseline, this paper reports the performance of some state-of-the-art aspect-based sentiment analysis methods with a focus on deep learning, on Pars-ABSA. The obtained results are impressive compared to similar English state-of-the-art.","url_abs":"https://arxiv.org/abs/1908.01815v3","url_pdf":"https://arxiv.org/pdf/1908.01815v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"pars-absa-an-aspect-based-sentiment-analysis","repo_url":"https://github.com/Titowak/Pars-ABSA","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"aspect-based-sentiment-analysis-1","task_name":"Aspect-Based Sentiment Analysis"},{"task_slug":"aspect-based-sentiment-analysis","task_name":"Aspect-Based Sentiment Analysis (ABSA)"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"}],"methods":[],"datasets_introduced":[{"slug":"pars-absa","name":"Pars-ABSA","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}