Int. J. Adv. Eng. Pure Sci. 2021, ASYU 2020 Special Issue: 28-34 DOI: 10.7240/jeps.896515 Corresponding Author: Ahmet ELBİR, Tel: 02123835757, e-posta: aelbir@yildiz.edu.tr Submitted: 14.03.2021, Revised: 13.12.2021, Accepted: 13.12.2021 RESEARCH ARTICLE / ARAŞTIRMA MAKALESİ Aspect Based Opinion Mining on Hotel Reviews Otel Değerlendirmeleri Üzerinde Hedef Tabanlı Fikir Madenciliği Semih DURMAZ 1 , Yunus Emre DEMİR 1 , Ahmet ELBİR 1 , İbrahim Onur SIĞIRCI 1 , Banu DİRİ 1 1 Yıldız Teknik Üniversitesi, Bilgisayar Mühendisliği Bölümü, 34220, İstanbul, Türkiye Abstract Users often use online reviews to assess the quality of hotels according to their various attributes. In this study, a sentiment analysis of online reviews has been conducted using eleven attributes the most frequently reviewed pertaining to hotels. Using this analysis, users’ overall assessments of hotels have been determined and summarized from reviews left for a group of various hotels. To identify words with similar meanings to the eleven predetermined hotel attributes, the Word2Vec method has been employed. Additionally, the FastText method has been used to detect words containing spelling errors. The sentiment analysis of the comments has been made by using three different methods belonging to two different approaches. These methods are VADER method as dictionary-based approach, BERT and RoBERTa as machine learning approaches. Using these methods, the reviews have been evaluated in three categories as positive, negative, and neutral, and the quality score has been calculated. In addition, a software with a user-friendly graphical interface has been implemented in an effort to easily use all the methods used in this study. Keywords: opinion mining, sentiment analysis, aspect based, social media, hotel reviews. Öz Kullanıcılar, çevrimiçi yorumları kullanarak otelleri çeşitli özelliklerine göre değerlendirmektedirler. Bu çalışmada; oteller ile ilgili yorumlar içerisinde hakkında en çok değerlendirme yapılan on bir özellik belirlenmiş ve bu özellikleri içeren yorumların duygu analizleri yapılmıştır. Bu sayede otelin bir niteliği hakkında yapılan yorumlardan kullanıcıların genel görüşü tespit edilmiş ve özetlenmiştir. Çalışmada belirlenen on bir özelliği temsil edecek benzer anlamlı kelimelerin tespiti için Word2Vec ve yazım hataları içeren kelimelerin tespiti için FastText yöntemi kullanılmıştır. Yorumların duygu analizi, iki ayrı yaklaşıma ait üç farklı yöntem kullanılarak yapılmıştır. Birincisi, sözlük tabanlı yaklaşımlardan VADER, ikincisi makine öğrenmesi yaklaşımlarından BERT ve RoBERTa'dır. Bu yöntemler ile yorumlar; olumlu, olumsuz ve nötr olmak üzere üç kategoride karşılaştırmalı olarak değerlendirilerek nitelik skoru hesaplanmıştır. Buna ek olarak, bu çalışma kapsamında kullanılan tüm yöntemleri kolay bir şekilde uygulamak için açık kaynaklı ve kullanıcı dostu bir grafik ara yüze sahip yazılım gerçeklenmiştir. Anahtar Kelimeler: fikir madenciliği, duygu analizi, hedef tabanlı, sosyal medya, otel yorumları . I. INTRODUCTION With the advent of technology and the increasing importance of the internet in human life, people’s habits have undergone substantial change. Processes that previously required significant effort have been facilitated by the Internet and technology. Especially, reservations and shopping can be done quickly through the internet. The Internet also triggers people’s desire to share experiences. This situation has vastly increased the number of comments on the internet. In the past, visitors to places would write their opinions in guestbooks. These guestbooks had to be read in order to learn more about past visitors’ experiences and include information on cleanliness, food quality, and other details. However, technology has enabled people to carry out such activities on a different platform. To this end, most establishments, in particular hotels and restaurants, have now transferred these operations onto the internet. In addition to online booking systems, online review systems have been put into place by establishments to ensure customers and visitors can continue to leave reviews. By using review systems, people can easily express their good or bad opinions regarding any establishment. While these reviews have an important place in terms of guiding future customers, they are also of great importance to a company to assess itself from the customer’s perspective. The sheer volume of comments shared on the internet makes it difficult to read and evaluate all of them. As a result, sentiment analysis studies are used to determine the sentiments contained in massive comment datasets. Sentiment analysis is defined as the classification and interpretation of various sentiments contained in texts.