algorithm knowledge of users plays a crucial role in avoiding them from algorithm bias in recommendation systems. Gender of users has been found to correlate with algorithm bias, but also leaving behind a question of ...
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algorithm knowledge of users plays a crucial role in avoiding them from algorithm bias in recommendation systems. Gender of users has been found to correlate with algorithm bias, but also leaving behind a question of whether this relationship can be described by algorithm knowledge. By using Weibo as an example system, we clarify the aforementioned question from a digital divide theory perspective. We combine a traditional method (questionnaire) with a deep learning computational method to explain algorithm bias in two sequential studies. Our findings suggest that algorithm knowledge solely works for men while fails to protect women. Who users follow helps determine what information they are exposed to on Weibo, and this renders female users' algorithm knowledge useless. This work provides a valuable perspective on algorithm bias: we view algorithm bias as a new digital divide and contribute to the understanding of gender differences by applying the digital divide perspective. Methodologically, we contribute by integrating traditional and computational methods to explain algorithm bias from a folk theory perspective.
algorithms have become almost ubiquitous on the internet. They shape the way internet users engage with internet services across diverse online domains and what outcomes they obtain from their internet uses. While sch...
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algorithms have become almost ubiquitous on the internet. They shape the way internet users engage with internet services across diverse online domains and what outcomes they obtain from their internet uses. While scholars have extensively studied the societal implications of algorithms in the digital world, only a few studies investigated the relationship between digital inequalities and algorithm awareness and knowledge. Little is known about how ubiquity of internet access and disparities in skills affect algorithm awareness and knowledge of internet users, and how they affect their internet uses and outcomes. To fill this important gap, this study presents and tests an explanatory model to assert how algorithm awareness and knowledge are related to the three levels of digital inequalities. The data were collected with a face-to-face survey (response rate = 54%) on a representative sample of internet users (N = 802) in Slovenia in 2022. Results of path analysis confirmed the sequential paths between the three levels of digital inequalities, suggesting that ubiquity of internet access strongly determines internet skills and internet uses, which in turn affect tangible internet outcomes. While ubiquity of internet access affected only algorithm awareness, internet skills predicted both algorithm awareness and knowledge. Importantly, algorithm knowledge was a significant determinant of internet uses. Age, education, and income moderated some of the relationships in the model. Overall, the study demonstrates that research on digital inequalities and related interventions need to address algorithm awareness and knowledge, and also consider how social inequalities among internet users shape them.
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