A Web Search Enhanced Feature Extraction Method for Aspect-Based Sentiment Analysis for Turkish Informal Texts

Kama B., ÖZTÜRK M., KARAGÖZ P., TOROSLU İ. H., Ozay O.

18th International Conference on Data Warehousing and Knowledge Discovery (DAWAK), Porto, Portekiz, 6 - 08 Eylül 2016, cilt.9829, ss.225-238 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 9829
  • Doi Numarası: 10.1007/978-3-319-43946-4_15
  • Basıldığı Şehir: Porto
  • Basıldığı Ülke: Portekiz
  • Sayfa Sayıları: ss.225-238
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

In this article, a new unsupervised feature extraction method for aspect-based sentiment analysis is proposed. This method improves the performance of frequency based feature extraction by using an online search engine. Although frequency based feature extraction methods produce good precision and recall values on formal texts, they are not very successful on informal texts. Our proposed algorithm takes the features of items suggested by frequency based feature extraction methods, then, eliminates the features which do not co-occur with the item, whose features are sought, on the Web. Since the proposed method constructs the candidate feature set of the item from the Web, it is domain-independent. The results of experiments reveal that for informal Turkish texts, much higher performance than frequency based method is achieved.