Amirhossein Aleyasen

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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)
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)
Documentaries are meant to tell a story, that is, to create memory, imagination and sharing (Rose, 2012). Moreover, documentaries aim to lead to change in people's knowledge and/ or behavior (Barrett & Leddy, 2008). How can we know if a documentary has achieved these goals? We report on a research project where we have been developing, applying and(More)
Documentaries are meant to tell a story, i.e. to create memory, imagination and sharing (Rose, 2012). More specifically, the goal with social justice documentaries is to motivate change in people's knowledge and/ or behavior (Barrett & Leddy, 2008). How can we know if a production has achieved these goals? And how early in the life cycle of a film project(More)
• Common Approach and status quo: – Big data: frequency counts of screenings and viewers – Thick data: small-scale, in-depth interviews with focus groups – Science: psychological effects of media on individuals – Strong need for comprehensive, empirical, rigorous impact assessment 3 Our Questions • How can we know if a documentary or media product has what(More)
This paper illustrates how data pre-processing choices about author name disambiguation can affect research findings about scholarly networks and hypotheses about underlying social mechanisms. We have analyzed three big scholarly datasets that were disambiguated algorithmically and via two common initial-based disambiguation methods; namely first-initial(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)
Finding similar or strongly related entities in a graph database is a fundamental problem in data management and analytics with applications in similarity query processing, entity resolution , and pattern matching. Similarity search algorithms usually leverage the structural properties of the data graph to quantify the degree of similarity or relevance(More)
In addition to visiting popular sites such as Facebook and Google, web users often visit more modest sites, such as those operated by bloggers, or by local organizations such as schools. Such sites, which we call "Just Plain Sites" (JPSs), are likely to inadvertently present greater privacy risks than highly popular sites, because they are unable to afford(More)