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http://hdl.handle.net/20.500.12188/29462| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Nikolova, Dragana | en_US |
| dc.contributor.author | Mircheva, Georgina | en_US |
| dc.contributor.author | Zdravevski, Eftim | en_US |
| dc.date.accessioned | 2024-02-18T17:11:55Z | - |
| dc.date.available | 2024-02-18T17:11:55Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | http://hdl.handle.net/20.500.12188/29462 | - |
| dc.publisher | Springer Nature Switzerland | en_US |
| dc.title | Application of Traditional and Deep Learning Algorithms in Sentiment Analysis of Global Warming Tweets | en_US |
| dc.type | Proceeding article | en_US |
| dc.relation.conference | 9th EAI International Conference on Smart Objects and Technologies for Social Good | en_US |
| dc.identifier.doi | 10.1007/978-3-031-52524-7_4 | - |
| dc.identifier.url | https://link.springer.com/content/pdf/10.1007/978-3-031-52524-7_4 | - |
| item.fulltext | No Fulltext | - |
| item.grantfulltext | none | - |
| crisitem.author.dept | Faculty of Computer Science and Engineering | - |
| crisitem.author.dept | Faculty of Computer Science and Engineering | - |
| Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers | |
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