Exploring the filter bubble

Nguyen, Tien Thanh; Hui, Pik-Mai; Harper, F. Maxwell; Terveen, Loren; Konstan, Joseph A.

doi:10.1145/2566486.2568012

Cited by 330 publications

(76 citation statements)

References 12 publications

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“…Or they combine both approaches (hybrid recommender systems; Burke, 2002). Nguyen, Hui, Harper, Terveen, and Konstan (2014) found mixed results when they analysed the effects of a movie rating page's collaborative filtering-based recommender system on its users' range of interests. The users' average movie diversity decreased over time, but the effect was stronger for those users that did not usually follow the recommendations than for those who did frequently click the recommended links.…”

Section: Agent-based Modellingmentioning

confidence: 99%

The triple‐filter bubble: Using agent‐based modelling to test a meta‐theoretical framework for the emergence of filter bubbles and echo chambers

Geschke¹,

Lorenz

Holtz

2018

British J Social Psychol

161

117

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Filter bubbles and echo chambers have both been linked recently by commentators to rapid societal changes such as Brexit and the polarization of the US American society in the course of Donald Trump's election campaign. We hypothesize that information filtering processes take place on the individual, the social, and the technological levels (triple‐filter‐bubble framework). We constructed an agent‐based modelling (ABM) and analysed twelve different information filtering scenarios to answer the question under which circumstances social media and recommender algorithms contribute to fragmentation of modern society into distinct echo chambers. Simulations show that, even without any social or technological filters, echo chambers emerge as a consequence of cognitive mechanisms, such as confirmation bias, under conditions of central information propagation through channels reaching a large part of the population. When social and technological filtering mechanisms are added to the model, polarization of society into even more distinct and less interconnected echo chambers is observed. Merits and limits of the theoretical framework, and more generally of studying complex social phenomena using ABM, are discussed. Directions for future research such as ways of comparing our simulations with actual empirical data and possible measures against societal fragmentation on the three different levels are suggested.

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Section: Agent-based Modellingmentioning

confidence: 99%

The triple‐filter bubble: Using agent‐based modelling to test a meta‐theoretical framework for the emergence of filter bubbles and echo chambers

Geschke¹,

Lorenz

Holtz

2018

British J Social Psychol

161

117

View full text Add to dashboard Cite

show abstract

“…Blacklisted Use #1 -Enhanced Filter Bubble: While there is some debate in the literature about where and when filter bubbles exist (e.g. [59]), most scholars agree on the negative impacts of filter bubbles that do exist (e.g. [16,65,68,77]).…”

Section: Avoiding Negative Impactsmentioning

confidence: 99%

Out of Site

Alarcon

Espinosa

et al. 2018

Proc. ACM Hum.-Comput. Interact.

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GrabYourWallet, #boycottNRA and other online boycott campaigns have attracted substantial public interest in recent months. However, a number of significant challenges are preventing online boycotts from reaching their potential. In particular, complex webs of brands and subsidiaries can make it difficult for participants to conform to the goals of a boycott. Similarly, participants and organizers have limited visibility into a boycott's progress. This affects their ability to use sociotechnical innovations from social computing to incentivize participation. To address these challenges, this paper makes a system contribution: a new boycott tool called Out of Site. Out of Site uses lightweight automation to remove obstacles to successful online boycotts. We describe the design challenges associated with Out of Site and report results from two phases of deployment with the GrabYourWallet and Stop Animal Testing boycott communities. Our findings highlight the potential of boycott-assisting technologies and inform the design of this new class of technologies. Finally, like is the case for many systems in social computing, while we designed Out of Site for pro-social uses, there are a number of easily predictable ways in which the system can be leveraged for anti-social purposes (e.g. exacerbating filter bubble issues, empowering boycotts of businesses owned by racial, ethnic, and religious minorities). As such, we developed for this project a new, very straightforward design approach that treats preventing these anti-social uses as a top-tier design concern. This approach stands in contrast to the status quo of ignoring potential anti-social uses and/or considering them to be a secondary design priority. We discuss how our simple approach may help other research projects reduce their potential negative impacts with minimal burden.

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“…Online recommender systems -built on algorithms that attempt to predict which products or services potential customers will most enjoy consuming -are one family of technologies that potentially suffer from this effect. 236 According to Schroeder, impersonal laws or regularities derived from purchase histories translated in algorithms leave less and less room for individuality. 237 The attempt of retailing company Target to identify customers in early stages of pregnancy based on their purchasing behaviour is probably one of the best known examples that show how analytics can pose serious privacy risks.…”

Section: Normalisationmentioning

confidence: 99%

Lists of Ethical, Legal, Societal and Economic Issues of Big Data Technologies

et al. 2017

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Data-driven innovation is deeply transforming society and the economy. Although there are potentially enormous economic and social benefits this innovation also brings new challenges for individual and collective privacy, security, as well as democracy and participation. The main objective of the CSA e-SIDES is to complement the research on privacy-preserving big data technologies, by analyzing, mapping and clearly identifying the main societal and ethical challenges emerging from the adoption of big data technologies, conforming to the principles of responsible research and innovation; setting up and organizing a sustainable dialogue between industry, research and social actors, as well as networking with the main Research and Innovation Actions and Large Scale Pilots and other framework program projects interested in these issues. It will investigate stakeholders' concerns, and collect their input, framing these results in a clear conceptual framework showing the potential trade-offs between conflicting needs and providing a basis to validate privacy-preserving technologies. It will prepare and widely disseminate community shared conclusions and recommendations highlighting the best way to ultimately build confidence of citizens and businesses towards big data and the data economy. Second, the legal perspective focuses on the lists of human rights derived from the European Convention on Human Rights (ECHR) and the EU Charter of Fundamental Rights (the EU Charter), which together constitute the main legal framework for the EU in the field of human rights. The rights of particular relevance in the context of big data technologies are the rights to private and family life, personal data protection, freedom of expression and information, freedom of assembly and association, nondiscrimination, fair trial and consumer protection. By analysing the normative scope of each of these human rights, looking at both legislation and case law of the European courts and the way in which big data technologies challenge different aspects of each human right at stake, the legal part distils the list of the most relevant issues at the nexus of big data technologies and human rights in the EU. The legal issues identified are: lack of transparency, vagueness of the concept of harm, accountability, proportionality, establishing a regulatory framework and the role of private actors in applying fundamental rights.Third, the societal perspective makes use of the extensive literature on Societal Impact Assessments (SIA). The analysis of literature was combined with a review of research project propositions and complemented by discussions at two workshops. Societal impact is very generally understood as changes to one or more of a number of elements of social life: people's way of life, their culture, their community, their political systems, their environment, their health and well-being, their personal and property and their fears and aspirations. The societal issues are mapped by examining different actors and distinctions between thes...

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Exploring the filter bubble

Cited by 330 publications

References 12 publications

The triple‐filter bubble: Using agent‐based modelling to test a meta‐theoretical framework for the emergence of filter bubbles and echo chambers

The triple‐filter bubble: Using agent‐based modelling to test a meta‐theoretical framework for the emergence of filter bubbles and echo chambers

Out of Site

Lists of Ethical, Legal, Societal and Economic Issues of Big Data Technologies

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