Affiliation:
1. Educational Sciences, Educational Measurement and Evaluation, Akdeniz University , Antalya, Turkey
2. Department of Turkish Education, Akdeniz University , Antalya, Turkey
Abstract
Abstract
Dictionary-based sentiment analysis is a text mining application that allows comments about the sentimental states of the text or documents through the sentimental poles of the words. In recent years, it has become quite popular in many disciplines such as trade, health, education, usage for various purposes. It is applied in many languages depending on the sentiment dictionaries, which are the main component, are created. Unlike inflectional languages such as English and German, the number of dictionary-based sentiment analysis studies using the Turkish language, which is a sequencing language, is very limited. When the literature of sentiment analysis is examined separately in terms of the material used; it is seen that the number of studies on long-format literary texts, which have been functioning as sentiment transmission throughout history, is also quite limited. In the light of these knowledges, a comprehensive method of creating a domain-specific sentiment dictionary and applying dictionary-based sentiment analysis on Turkish texts is proposed in the R software.
Publisher
Oxford University Press (OUP)
Subject
Computer Science Applications,Linguistics and Language,Language and Linguistics,Information Systems
Reference32 articles.
1. Emotional Sequencing and Development in Fairy Tales
2. Modern Türk Hikâyeciliğinde Ömer Seyfettin Etkisi;Aydemir;Balıkesir Üniversitesi Sosyal Bilimler Dergisi,2005
3. Heaps’ Law and Heaps functions in tagged texts: evidences of their linguistic relevance;Chacoma;Royal Society of Open Science,2020
4. SentiTurkNet: a Turkish polarity lexicon for sentiment analysis;Dehkhargani;Language Resources and Evaluation,2016
5. Techniques and applications for sentiment analysis;Feldman;Communications of the ACM,2013
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