@inproceedings{40e44f0eee2544198de7a7baa22ecf3b,
title = "Sentiment Analysis of Hotel Reviews in Greek: A Comparison of Unigram Features",
abstract = "Web 2.0 has become a very useful information resource nowadays, as people are strongly inclined to express online their opinion in social media, blogs and review sites. Sentiment analysis aims at classifying documents as positive or negative according to their overall expressed sentiment. In this paper, we create a sentiment classifier applying Support Vector Machines on hotel reviews written in Modern Greek. Using a unigram language model, we compare two different methodologies and the emerging results look very promising.",
keywords = "Information retrieval, Machine learning, Natural language processing, Sentiment analysis, Text mining",
author = "George Markopoulos and George Mikros and Anastasia Iliadi and Michalis Liontos",
note = "Publisher Copyright: {\textcopyright} 2015, Springer International Publishing Switzerland.; 1st International Conference on Cultural Tourism in a Digital Era, IACuDiT 2014 ; Conference date: 30-05-2014 Through 01-06-2014",
year = "2015",
doi = "10.1007/978-3-319-15859-4_31",
language = "English",
isbn = "9783319158587",
series = "Springer Proceedings in Business and Economics",
publisher = "Springer Science and Business Media B.V.",
pages = "373--383",
editor = "Vicky Katsoni",
booktitle = "Cultural Tourism in a Digital Era - 1st International Conference IACuDiT, 2014",
address = "Germany",
}