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Lifelong bilingualism and mechanisms of neuroprotection in Alzheimer dementia. ...
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Human drone interaction in delivery of medical supplies: A scoping review of experimental studies
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In: PLoS One (2022)
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Regional Alteration within the Cerebellum and the Reorganization of the Cerebrocerebellar System following Poststroke Aphasia
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In: Neural Plast (2022)
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The Recovery Mechanism of Standardized Aphasia in Intelligent Medical Treatment
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In: Contrast Media Mol Imaging (2022)
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Guideline adherence in speech and language therapy in stroke aftercare. A health insurance claims data analysis
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In: PLoS One (2022)
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Sentimental Analysis of Twitter Users from Turkish Content with Natural Language Processing
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In: Comput Intell Neurosci (2022)
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Abstract:
Artificial Intelligence has guided technological progress in recent years; it has shown significant development with increased academic studies on Machine Learning and the high demand for this field in the sector. In addition to the advancement of technology day by day, the pandemic, which has become a part of our lives since early 2020, has led to social media occupying a larger place in the lives of individuals. Therefore, social media posts have become an excellent data source for the field of sentiment analysis. The main contribution of this study is based on the Natural Language Processing method, which is one of the machine learning topics in the literature. Sentiment analysis classification is a solid example for machine learning tasks that belongs to human-machine interaction. It is essential to make the computer understand people emotional situation with classifiers. There are a limited number of Turkish language studies in the literature. Turkish language has different types of linguistic features from English. Since Turkish is an agglutinative language, it is challenging to make sentiment analysis with that language. This paper aims to perform sentiment analysis of several machine learning algorithms on Turkish language datasets that are collected from Twitter. In this research, besides using public dataset that belongs to Beyaz (2021) to get more general results, another dataset is created to understand the impact of the pandemic on people and to learn about public opinions. Therefore, a custom dataset, namely, SentimentSet (Balli 2021), was created, consisting of Turkish tweets that were filtered with words such as pandemic and corona by manually marking as positive, negative, or neutral. Besides, SentimentSet could be used in future researches as benchmark dataset. Results show classification accuracy of not only up to ∼87% with test data from datasets of both datasets and trained models, but also up to ∼84% with small “Sample Test Data” generated by the same methods as SentimentSet dataset. These research results contributed to indicating Turkish language specific sentiment analysis that is dependent on language specifications.
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Keyword:
Research Article
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URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007140/
https://doi.org/10.1155/2022/2455160
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The Effectiveness of Transcranial Magnetic Stimulation (TMS) Paradigms as Treatment Options for Recovery of Language Deficits in Chronic Poststroke Aphasia
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In: Behav Neurol (2022)
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A cortical network processes auditory error signals during human speech production to maintain fluency
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In: PLoS Biol (2022)
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Social Media Analytics for Pharmacovigilance of Antiepileptic Drugs
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In: Comput Math Methods Med (2022)
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Quantitative Evaluation of Vocabulary Emotional Color in Language Teaching
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In: Occup Ther Int (2022)
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Cognitive Advantages of Multilingual Learning on Metalinguistic Awareness, Working Memory and L1 Lexicon Size: Reconceptualization of Linguistic Giftedness from a DMM Perspective
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In: J Cogn (2022)
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Canadian Occupational Performance Measure: Benefits and Limitations Highlighted Using the Delphi Method and Principal Component Analysis
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In: Occup Ther Int (2022)
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Determining the applicability of the RSNA radiology lexicon (RadLex) in high-grade glioma MRI reporting—a preliminary study on 20 consecutive cases with newly diagnosed glioblastoma
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In: BMC Med Imaging (2022)
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Framing South Asian politics: An analysis of Indian and Pakistani English print media discourses regarding Kartarpur corridor
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In: PLoS One (2022)
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Translation as a political action: reframing ‘the deal of the century’ in the translations of the BBC
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In: Heliyon (2022)
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Machine Learning Technique to Detect and Classify Mental Illness on Social Media Using Lexicon-Based Recommender System
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In: Comput Intell Neurosci (2022)
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Discomfort, pain and stiffness: what do these terms mean to patients? A cross-sectional survey with lexical and qualitative analyses
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In: BMC Musculoskelet Disord (2022)
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Effects of word familiarity and receptive vocabulary size on speech-in-noise recognition among young adults with normal hearing
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In: PLoS One (2022)
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Identification and Classification of Depressed Mental State for End-User over Social Media
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In: Comput Intell Neurosci (2022)
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Relation between acquisition of lexical concept and joint attention in children with autism spectrum disorder without severe intellectual disability
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In: PLoS One (2022)
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