DUYGU ve GÖRÜŞ MADENCİLİĞİ: SON GELİŞMELER ve 3. HAVALİMANI İÇİN BİR UYGULAMA

Öteden beri insanoğlunun karar verme süreçlerinde başkalarının görüş ve yorumlarına başvurması değişmeyen bir durumdur. Bilgiye hızlıca erişimin akıllı telefonlar, tabletler ve bilgisayarlarla yapıldığı günümüz Büyük Veri Çağı’nda özellikle internet ortamlarında her konu hakkında görüşler, bilgiler ve yorumlar paylaşılmaktadır. Bu bilgi, görüş ve yorumlardan hem kişisel hem kurumsal bazda faydalı bilgiler çıkarsamak amacıyla kullanılan Metin Madenciliği son yıllarda en çok araştırılan konulardan biri haline geline gelmiştir. Metin Madenciliği zamanla çeşitli alanlara ayrılmış ve Görüş madenciliği veya Duygu Analizi alanları ortaya çıkmıştır. Günümüzde insanlar sosyal medya araçlarını, blogları, forumları sadece bilgi ve düşünce paylaşmak için kullanmakla kalmayıp, internet üzerinden satın alıp kullandıkları ürün/hizmet ile alakalı bilgileri de bu ortamlar aracılığıyla değerlendirmektedir. Bu çalışma İstanbul’daki Atatürk ve Sabiha Gökçen havalimanlarını kullanan yabancı müşterilerin bir internet sitesinde yaptıkları yorumları Görüş ve Duygu Madenciliği ile analiz etmeyi ve İstanbul’da kurulmuş olan 3. Havalimanı işletmecileri için bir çıkarsama sunmayı amaçlamaktadır. Analizler sonucu insanların kalabalıktan, pahalılıktan, kabalıktan, kayıp bavullardan, zorluklardan ve uçuş rötarlarından şikâyet ettikleri anlaşılmaktadır.

SENTIMENT AND OPINION MINING: RECENT ISSUES AND AN APPLICATION FOR THE THIRD AIRPORT

It is an unchanging situation that human being asks others’ opinions and comments during the process of decision making. In today’s Big Data Age, where the fast access to information is easily made with smartphones, tablets and computers; opinions, information and comments are shared on every topic, especially on the internet. Text Mining which is used to extract useful information from views and comments for both personal and institutional basis has become one of the most researched subjects in recent years. Text Mining has been divided into different areas over time, and the topics of Opinion Mining or Sentiment Analysis have emerged. Today, people not only use social media tools, blogs, forums to share information and ideas but also use those platforms to evaluate the products/services which they purchased over the internet. This study aims to analyse comments of foreign customers who used airports of Atatürk and Sabiha Gökçen in Istanbul. Opinion Mining and Sentiment Analysis will present an inference for the operator of the 3rd Airport in Istanbul. As a result of the analysis, it is understood that people complain about the crowd, the expensive, the rude, the lost baggage, the difficulties and the flight delays.

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AGUWA Celestine, OLYA, Mohammad Hessam, & MONPLAISIR, Leslie (2017), Modeling of fuzzy-based voice of customer for business decision analytics, Knowledge-Based Systems, 125, 136-145.
BOUMANS, Jelle W, & TRILLING, Damian (2016), Taking stock of the toolkit: An over-view of relevant automated content analysis approaches and techniques for digital journalism scholars, Digital journalism, 4(1), 8-23.
CAMBRIA, Erik, SCHULLER, Björn, XIA, Yunqing, & HAVASI, Catherine (2013), New avenues in opinion mining and sentiment analysis, IEEE Intelligent Systems, 28(2), 15-21.
ÇETİN, Fatih Samet, & ERYİĞİT, Gülşen (2018), Türkçe Hedef Tabanlı Duygu Analizi İçin Alt Görevlerin İncelenmesi–Hedef Terim, Hedef Kategori Ve Duygu Sınıfı Belirleme, Bilişim Teknolojileri Dergisi, 11(1), 43-56.
ELİAÇIK, Alpaslan Burak, & ERDOĞAN, Nadia (2015), Mikro Bloglardaki Finans Toplu-lukları için Kullanıcı Ağırlıklandırılmış Duygu Analizi Yöntemi. Paper presented at the UYMS.
ERYİĞİT, Gülşen (2014), ITU Turkish NLP web service. Paper presented at the Proceedings of the Demonstrations at the 14th Conference of the European Chapter of the Association for Computational Linguistics.
FEINERER, Ingo (2013), Introduction to the tm Package Text Mining in R. Accessible en ligne: http://cran. r-project. org/web/packages/tm/vignettes/tm. pdf.
GENC-NAYEBI, Necmiye, & ABRAN, Alain (2017), A systematic literature review: Opi-nion mining studies from mobile app store user reviews, Journal of Systems and Software, 125, 207-219.
JIN, Jian, LIU, Ying, JI, Ping, & LIU, Hongguang (2016), Understanding big consumer opinion data for market-driven product design, International Journal of Production Research, 54(10), 3019-3041.
KOÇAK, Bahri Baran, POLAT, Inci, & KOÇAK, Cem Burak, Twitter Kullanıcılarının Havayolu Pazarına Yönelik Duygu Kutuplarının Belirlenmesi: Bir Fikir Madenciliği Örneği, PressAcademia Procedia, 2(1), 684-691.
LIU, Bing (2012), Sentiment analysis and opinion mining, Synthesis lectures on human language technologies, 5(1), 1-167.
MÄNTYLÄ, Mika V, GRAZIOTIN, Daniel, & KUUTILA, Miikka (2018), The evolution of sentiment analysis—A review of research topics, venues, and top cited papers. Computer Science Review, 27, 16-32.
PANG, Bo, & LEE, Lillian (2008), Opinion mining and sentiment analysis, Foundations and Trends® in Information Retrieval, 2(1–2), 1-135.
PIRYANI, Rajesh, MADHAVI, D, & SINGH, Vivek Kumar (2017), Analytical mapping of opinion mining and sentiment analysis research during 2000–2015, Information Processing & Management, 53(1), 122-150.
RAVI, Kumar, & RAVI, Vadlamani (2015), A survey on opinion mining and sentiment analysis: tasks, approaches and applications, Knowledge-Based Systems, 89, 14-46.
RAVI, Kumar, RAVI, Vadlamani, & PRASAD, P Sree Rama Krishna (2017), Fuzzy formal concept analysis based opinion mining for CRM in financial services, Applied Soft Computing, 60, 786-807.
RUSHDI-SALEH, Mohammed, MARTÍN-VALDIVIA, M Teresa, UREÑA-LÓPEZ, L Alfonso, & PEREA-ORTEGA, José M. (2011), Bilingual experiments with an arabic-english corpus for opinion mining, Paper presented at the Proceedings of the International Conference Recent Advances in Natural Language Processing 2011.
SILGE, Julia, & ROBINSON, David (2016), tidytext: Text mining and analysis using tidy data principles in r, The Journal of Open Source Software, 1(3), 37.
SINGH, Abhinav, & TUCKER, Conrad S. (2017), A machine learning approach to product review disambiguation based on function, form and behavior classification. Decision Support Systems, 97, 81-91.
VINODHINI, G, & CHANDRASEKARAN, RM. (2017), A sampling based sentiment mining approach for e-commerce applications, Information Processing & Management, 53(1), 223-236.
WELBERS, Kasper, VAN ATTEVELDT, Wouter, & BENOIT, Kenneth (2017), Text analysis in R, Communication Methods and Measures, 11(4), 245-265.
XU, Xun, WANG, Xuequn, LI, Yibai, & HAGHIGHI, Mohammad (2017), Business intelli-gence in online customer textual reviews: Understanding consumer perceptions and influential factors, International Journal of information management, 37(6), 673-683.
YAMAN, Tutku Tuncalı (2018), Measuring Effects of Post-truth in Urban Archaeology: Istanbul Case, 8th International Symposium on Information Management in a Changing World, Ankara, Turkey, 2018.
YILDIRIM, Metin, & YÜKSEL, Cenk Arsun, Sosyal Medya İle Hisse Senedi Fiyatının Günlük Hareket Yönü Arasındaki İlişkinin İncelenmesi: Duygu Analizi Uygulamasi, Uluslararası İktisadi ve İdari İncelemeler Dergisi, 33-44.
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