Methodological Approach for Messages Classification on Twitter Within E-Government Area
| dc.contributor.author | Stoica, Eduard Alexandru | |
| dc.contributor.author | Ozyirmidokuz, Esra Kahya | |
| dc.contributor.author | Uyar, Kumru | |
| dc.contributor.author | Pitic, Antoniu Gabriel | |
| dc.date.accessioned | 2025-02-24T16:34:14Z | |
| dc.date.available | 2025-02-24T16:34:14Z | |
| dc.date.issued | 2018 | |
| dc.department | Nuh Naci Yazgan | |
| dc.description | 25th International Economic Conference of Sibiu -- IECS 2018 -- 11 May 2018 through 12 May 2018 -- Sibiu -- 273659 | |
| dc.description.abstract | The constant growth in the numbers of Social Media users is a reality of the past few years. Companies, governments and researchers focus on extracting useful data from Social Media. One of the most important things we can extract from the messages transmitted from one user to another is the sentiment—positive, negative or neutral—regarding the subject of the conversation. There are many studies on how to classify these messages, but all of them need a huge amount of data already classified for training, data not available for Romanian language texts. We present a case study in which we use a Naïve Bayes classifier trained on an English short text corpus on several thousand Romanian texts. We use Google Translate to adapt the Romanian texts and we validate the results by manually classifying some of them. © 2018, Springer Nature Switzerland AG. | |
| dc.description.sponsorship | TUBITAK 1003 Project, (116E676) | |
| dc.identifier.doi | 10.1007/978-3-030-01878-8_30 | |
| dc.identifier.endpage | 361 | |
| dc.identifier.isbn | 978-303001877-1 | |
| dc.identifier.issn | 2198-7246 | |
| dc.identifier.scopus | 2-s2.0-85126260806 | |
| dc.identifier.scopusquality | Q4 | |
| dc.identifier.startpage | 355 | |
| dc.identifier.uri | https://doi.org/10.1007/978-3-030-01878-8_30 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14440/556 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Springer Science and Business Media B.V. | |
| dc.relation.ispartof | Springer Proceedings in Business and Economics | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_Scopus_20250201 | |
| dc.subject | Naïve Bayes classifier | |
| dc.subject | Social media | |
| dc.subject | Text classification | |
| dc.title | Methodological Approach for Messages Classification on Twitter Within E-Government Area | |
| dc.type | Conference Object |
