Motahhare Eslami

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Our daily digital life is full of algorithmically selected content such as social media feeds, recommendations and personalized search results. These algorithms have great power to shape users' experiences, yet users are often unaware of their presence. Whether it is useful to give users insight into these algorithms' existence or functionality and how such(More)
The rise in prevalence of algorithmically curated feeds in online news and social media sites raises a new question for designers, critics, and scholars of media: how aware are users of the role of algorithms and filters in their news sources? This paper situates this problem within the history of design for interaction, with an emphasis on the contemporary(More)
Social media feeds, personalized search results and recommendations are examples of algorithmically curated content in our daily digital Life. While the algorithms that curated this content have great power to shape users' experiences, they are mostly hidden behind the interface, leaving users unaware of their presence. Whether it is helpful to give users(More)
The spread of information cascades over social networks forms the diffusion networks. The latent structure of diffusion networks makes the problem of extracting diffusion links difficult. As observing the sources of information is not usually possible, the only available prior knowledge is the infection times of individuals. We confront these challenges by(More)
Search systems in online social media sites are frequently used to find information about ongoing events and people. For topics with multiple competing perspectives, such as political events or political candidates, bias in the top ranked results significantly shapes public opinion. However, bias does not emerge from an algorithm alone. It is important to(More)
Many online platforms use curation algorithms that are opaque to the user. Recent work suggests that discovering a filtering algorithm's existence in a curated feed influences user experience, but it remains unclear how users reason about the operation of these algorithms. In this qualitative laboratory study, researchers interviewed a diverse,(More)
Managing friendship relationships is challenging due to the growing number of people in online social networks (OSNs). While grouping friends sometimes mitigates this challenge, the burden of manual grouping still prevents OSNs users to create groups widely for privacy control, selective sharing and filtering. In this paper, we present an automated friend(More)
Managing friendship relationships in social media is challenging due to the growing number of people in online social networks (OSNs). To deal with this challenge, OSNs' users may rely on manually grouping friends with personally meaningful labels. However, manual grouping can become burdensome when users have to create multiple groups for various purposes(More)
Awareness of bias in algorithms is growing among scholars and users of algorithmic systems. But what can we observe about how users discover and behave around such biases? We used a cross-platform audit technique that analyzed on-line ratings of 803 hotels across three hotel rating platforms and found that one site's algorithmic rating system biased ratings(More)
While today many online platforms employ complex algorithms to curate content, these algorithms are rarely highlighted in interfaces, preventing users from understanding these algorithms' operation or even existence. Here, we study how knowledgeable users are about these algorithms, showing that providing insight to users about an algorithm's existence or(More)