Digital Platforms and Media Use: An Exploratory Research on Trust, Gender Stereotypes and Bias in Turkey

Ceren Saran
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Abstract

Media use and news consumption occur throughout digital platforms as a rising trend worldwide. These digital infrastructures serve as channels through which users access content and as gatekeepers that curate the content figured by algorithmic selection. Thus, this research is designed to step inside the digital media use and aims to understand what kind of stereotypes and biases users face in digital platforms. To that end, a group of international university students from Turkey were interviewed about their experiences from several digital platforms. Accordingly, the participants were asked about the preferred source of the news, whether they trust the content they encounter on platforms, the stereotypes they face in their social media use, the most disturbing content in terms of bias and discrimination, if they feel free on their social media accounts, the awareness about the concepts “stereotypes”, “representation”, “algorithmic selection”, “algorithmic bias”. The research has shown that gender is the most common category of stereotype, followed by political, religious, nationality, and social class. In parallel with the concept of intersectionality, it has been observed that other forms of social discrimination are also encountered along with gender on digital platforms.
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数字平台与媒体使用:土耳其信任、性别陈规定型观念和偏见的探索性研究
通过数字平台使用媒体和消费新闻已成为全球范围内不断上升的趋势。这些数字基础设施既是用户获取内容的渠道,也是通过算法选择对内容进行策划的守门人。因此,本研究旨在深入了解数字媒体的使用情况,旨在了解用户在数字平台上面临什么样的成见和偏见。为此,我们采访了一组来自土耳其的留学生,了解他们在多个数字平台上的使用体验。他们被问及首选的新闻来源、是否信任在平台上遇到的内容、在使用社交媒体时面临的成见、在偏见和歧视方面最令人不安的内容、在社交媒体账户上是否感到自由,以及对 "成见"、"代表性"、"算法选择"、"算法偏见 "等概念的认识。研究表明,性别是最常见的刻板印象类别,其次是政治、宗教、国籍和社会阶层。与交叉性概念并行的是,研究还发现,在数字平台上,除了性别歧视,还存在其他形式的社会歧视。
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