A Cross-Validation Study of Turkish Sentiment Analysis Datasets and Tools
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866916513340981248 |
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| author | Çakıcı, Şevval Karaduman, Dilara Çırlan, Mehmet Akif Hürriyetoğlu, Ali |
| author_facet | Çakıcı, Şevval Karaduman, Dilara Çırlan, Mehmet Akif Hürriyetoğlu, Ali |
| contents | In recent years, sentiment analysis has gained increasing significance, prompting researchers to explore datasets in various languages, including Turkish. However, the limited availability of Turkish datasets has led to their multifaceted usage in different studies, yielding diverse outcomes. To overcome this challenge, a rigorous review was conducted of research articles published between 2012 and 2022. 31 studies were listed, and 23 Turkish datasets obtained from publicly available sources and email requests used in these studies were collected. We labeled these 31 studies using a taxonomy. We provide a map of sentiment analysis datasets according to this taxonomy in Turkish over 10 years. Moreover, we run state-of-the-art sentiment analysis tools on these datasets and analyzed performance across popular Turkish sentiment datasets. We observed that the performance of the sentiment analysis tools significantly depends on the characteristics of the target text. Our study fosters a more nuanced understanding of sentiment analysis in the Turkish language. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_05964 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Cross-Validation Study of Turkish Sentiment Analysis Datasets and Tools Çakıcı, Şevval Karaduman, Dilara Çırlan, Mehmet Akif Hürriyetoğlu, Ali Computation and Language In recent years, sentiment analysis has gained increasing significance, prompting researchers to explore datasets in various languages, including Turkish. However, the limited availability of Turkish datasets has led to their multifaceted usage in different studies, yielding diverse outcomes. To overcome this challenge, a rigorous review was conducted of research articles published between 2012 and 2022. 31 studies were listed, and 23 Turkish datasets obtained from publicly available sources and email requests used in these studies were collected. We labeled these 31 studies using a taxonomy. We provide a map of sentiment analysis datasets according to this taxonomy in Turkish over 10 years. Moreover, we run state-of-the-art sentiment analysis tools on these datasets and analyzed performance across popular Turkish sentiment datasets. We observed that the performance of the sentiment analysis tools significantly depends on the characteristics of the target text. Our study fosters a more nuanced understanding of sentiment analysis in the Turkish language. |
| title | A Cross-Validation Study of Turkish Sentiment Analysis Datasets and Tools |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2412.05964 |