WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/6

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Publication Index: search.filters.publicationIndex.ScopusSubject: search.filters.subject.Bilgisayar Bilimleri, Yazılım Mühendisliği

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  • Article
    Citation - WoS: 4
    Citation - Scopus: 5
    Qualitative and Artificial Intelligence-Based Sentiment Analysis of Turkish Tweets Related To Schizophrenia
    (Turkiye Sinir ve Ruh Sagligi dernegi, 2023) Dikec, Gul; Oban, Volkan; Usta, Mirac Baris
    Objective: The aim of this study was to qualitatively examine Turkish tweets about schizophrenia in respect of stigmatization and discrimination within a one-month period and to conduct emotional analysis using artificial intelligence applications. Method: Using the keyword 'schizophrenia,' Turkish tweets were gathered from the Python Tweepy application between December 19, 2020 and January 18, 2021. Features were extracted using the Bidirectional Encoder Representations from Transformers (BERT) method and artificial neural networks and tweets were classified as positive, neutral, or negative. Approximately 5% of the tweets were qualitatively analyzed, constituting those most frequently liked and retweeted. Results: The study found that, of the total of 3406 schizophrenia-related messages shared in Turkey over a period of one-month, 2996 were original, and were then retweeted a total of 1823 times, and liked by 25,413 people. It was determined that 63.4% of the tweets shared about schizophrenia contained negative emotions, 28.7% were neutral, and 7.71% expressed positive emotions. Within the scope of the qualitative analysis, 145 tweets were examined and classified under four main themes and two sub-themes; namely, news about violent patients, insult (insulting people in interpersonal relationships, insulting people in the news), mockery, and information. Conclusion: The results of this study showed that the Turkish tweets about schizophrenia, which were emotionally analyzed using artificial intelligence were found often to contain negative emotions. It was also seen that Twitter users used the term schizophrenia, not in a medical sense but to insult and make fun of individuals, frequently shared the news that patients were victims or perpetrators of violence, and the messages shared by professional branch organizations or mental health professionals were primarily for conveying information to the public.
  • Article
    Design and Implementation of a Low Cost and Portable Tactile Stimulator Br
    (Tubitak Scientific & Technological Research Council Turkey, 2022) Kazma, Coskun; Levent, Vecdi Emre; Cardak, Merve; Aydin, Nizamettin
    When central nervous system has a problem, somatic area I and II respond to stimulation differently. Therefore, it is possible to identify some of the central nervous diseases when somatosensory on the fingertip is stimulated and responses are recorded and analyzed. We designed a system to stimulate the mechanoreceptors on fingertips. It is composed of a mechanical system for fingertip stimulation, an embedded controller, a control computer, and a software to control overall operation. During test, mechanoreceptors are stimulated according to the test protocols. Individuals' answers are recorded to be evaluated by the developed software. In this study, several design approaches for embedded controller were also examined and an FPGA based controller with the same functionality but higher performance was implemented. A test procedure was performed on 51 individuals at the department of pediatric psychiatry in a hospital, to investigate whether the sex has an effect on attention deficit and hyperactivity disorder.