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Yayın Web service translating content into Turkish sign language(Institute of Electrical and Electronics Engineers Inc., 2020-10-12) Gümüşçekiçci, Gizem; Ezerceli, Özay; Tek, Faik BorayThe essential communication tool for people with hearing loss is sign language. It is way more efficient for their communication. Existing systems for translating the text into sign language are offline and not practical. In this study, we propose a web service-based solution for online translation of content into Turkish Sign Language. We implemented the system and tested it using 32 sentences of 189 words as inputs. The correct word translation rate was 81.74% for the media or audio inputs and the correct word translation for the text inputs was 81.09% The results show the feasibility of the solution and the potential for improvements.Yayın Turkish sentiment analysis: a comprehensive review(Yildiz Technical University, 2024-08) Altınel Girgin, Ayşe Berna; Gümüşçekiçci, Gizem; Birdemir, Nuri CanSentiment analysis (SA) is a very popular research topic in the text mining field. SA is the process of textual mining in which the meaning of a text is detected and extracted. One of the key aspects of SA is to analyze the body of a text to determine its polarity to understand the opinions it expresses. Substantial amounts of data are produced by online resources such as social media sites, blogs, news sites, etc. Due to this reason, it is impossible to process all of this data without automated systems, which has contributed to the rise in popularity of SA in recent years. SA is considered to be extremely essential, mostly due to its ability to analyze mass opinions. SA, and Natural Language Processing (NLP) in particular, has become an overwhelmingly popular topic as social media usage has increased. The data collected from social media has sourced numerous different SA studies due to being versatile and accessible to the masses. This survey presents a comprehensive study categorizing past and present studies by their employed methodologies and levels of sentiment. In this survey, Turkish SA studies were categorized under three sections. These are Dictionary-based, Machine Learning-based, and Hybrid-based. Researchers can discover, compare, and analyze properties of different Turkish SA studies reviewed in this survey, as well as obtain information on the public dataset and the dictionaries used in the studies. The main purpose of this study is to combine Turkish SA approaches and methods while briefly explaining its concepts. This survey uniquely categorizes a large number of related articles and visualizes their properties. To the best of our knowledge, there is no such comprehensive and up-to-date survey that strictly covers Turkish SA which mainly concerns analysis of sentiment levels. Furthermore, this survey contributes to the literature due to its unique property of being the first of its kind.
