Sentiment analysis in Turkish

Download
2009
Eroğul, Umut
Sentiment analysis is the automatic classification of a text, trying to determine the attitude of the writer with respect to a specific topic. The attitude may be either their judgment or evaluation, their feelings or the intended emotional communication. The recent increase in the use of review sites and blogs, has made a great amount of subjective data available. Nowadays, it is nearly impossible to manually process all the relevant data available, and as a consequence, the importance given to the automatic classification of unformatted data, has increased. Up to date, all of the research carried on sentiment analysis was focused on English language. In this thesis, two Turkish datasets tagged with sentiment information is introduced and existing methods for English are applied on these datasets. This thesis also suggests new methods for Turkish sentiment analysis.

Suggestions

Sentiment analysis of Turkish political columns with transfer learning
Kaya, Mesut; Toroslu, İsmail Hakkı; Fidan, Güven; Department of Computer Engineering (2013)
Sentiment Analysis aims to determine the attitude (sense, emotion, opinion etc.) of a speaker or a writer with respect to a specified topic by automatically classifying a textual data. With the recent explosive growth of the social media content on theWeb, people post reviews of products on merchant sites and express their views about almost anything in their personal blogs, pages at social network sites like Facebook, Twitter, and Blogger. Therefore, sentiment analysis has become a major area of interest i...
Improvement of corpus-based semantic word similarity using vector space model
Esin, Yunus Emre; Alpaslan, Ferda Nur; Department of Computer Engineering (2009)
This study presents a new approach for finding semantically similar words from corpora using window based context methods. Previous studies mainly concentrate on either finding new combination of distance-weight measurement methods or proposing new context methods. The main di fference of this new approach is that this study reprocesses the outputs of the existing methods to update the representation of related word vectors used for measuring semantic distance between words, to improve the results further. ...
Natural language query processing in ontology based multimedia databases
Aygül, Filiz Alaca; Çiçekli, Fehime Nihan; Department of Computer Engineering (2010)
In this thesis a natural language query interface is developed for semantic and spatio-temporal querying of MPEG-7 based domain ontologies. The underlying ontology is created by attaching domain ontologies to the core Rhizomik MPEG-7 ontology. The user can pose concept, complex concept (objects connected with an “AND” or “OR” connector), spatial (left, right . . . ), temporal (before, after, at least 10 minutes before, 5 minutes after . . . ), object trajectory and directional trajectory (east, west, southe...
Exploiting information extraction techniques for automatic semantic annotation and retrieval of news videos in Turkish
Küçük, Dilek; Yazıcı, Adnan; Department of Computer Engineering (2011)
Information extraction (IE) is known to be an effective technique for automatic semantic indexing of news texts. In this study, we propose a text-based fully automated system for the semantic annotation and retrieval of news videos in Turkish which exploits several IE techniques on the video texts. The IE techniques employed by the system include named entity recognition, automatic hyperlinking, person entity extraction with coreference resolution, and event extraction. The system utilizes the outputs of th...
Cross-lingual information retrieval on Turkish and English texts
Boynueğri, Akif; Birtürk, Ayşe Nur; Department of Computer Engineering (2010)
In this thesis, cross-lingual information retrieval (CLIR) approaches are comparatively evaluated for Turkish and English texts. As a complementary study, knowledge-based methods for word sense disambiguation (WSD), which is one of the most important parts of the CLIR studies, are compared for Turkish words. Query translation and sense indexing based CLIR approaches are used in this study. In query translation approach, we use automatic and manual word sense disambiguation methods and Google translation ser...
Citation Formats
U. Eroğul, “Sentiment analysis in Turkish,” M.S. - Master of Science, Middle East Technical University, 2009.