Methodological Approach for Messages Classification on Twitter Within E-Government Area

Stoica E. A., KAHYA ÖZYİRMİDOKUZ E., UYAR K., Pitic A. G.

25th International Economic Conference of Sibiu, IECS 2018, Sibiu, Romanya, 11 - 12 Mayıs 2018, ss.355-361 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1007/978-3-030-01878-8_30
  • Basıldığı Şehir: Sibiu
  • Basıldığı Ülke: Romanya
  • Sayfa Sayıları: ss.355-361
  • Anahtar Kelimeler: Naïve Bayes classifier, Social media, Text classification
  • Erciyes Üniversitesi Adresli: Evet

Özet

© 2018, Springer Nature Switzerland AG.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.