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Open AccessJournal ArticleDOI

Ageism in the era of digital platforms

Andrea Rosales, +1 more
- 25 Jun 2020 - 
- Vol. 26, pp 1074-1087
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TLDR
This article analyzes some tools that are frequently embedded on digital platforms from an old-age perspective, in order to increase awareness of the different ways in which ageism works.
Abstract
Ageism is the most invisible form of discrimination While there is some awareness of gender, racial, and socioeconomic discrimination on digital platforms, ageism has received less attention This article analyzes some tools that are frequently embedded on digital platforms from an old-age perspective, in order to increase awareness of the different ways in which ageism works We will firstly look at how innovation teams, following homophilic patterns, disregard older people Secondly, we will show how ageism tends to be amplified by the methods often used on digital platforms And thirdly, we will show how corporate values contradict the usability issues that mainly affect people with a low level of (digital) skills, which is more common among older people Counterbalancing the abusive power control of the corporations behind digital platforms and compensating for the underrepresentation of groups in less favorable situations could help to tackle such discrimination

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Mobile Communication and Society: A Global Perspective

TL;DR: This theoretically hybrid, statistically significant, and culturally sensitive book achieves a sustained sociological understanding of the cell phone in a global context through an important study spanning three continents, and asking fundamental questions about the social effects of wireless communication.
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The datafied society, studying culture through data

TL;DR: Schafer and van Es as discussed by the authors argue that studying culture through data comes with independence and rigour in the scientific debate related to the study of culture through the data, and that the advantages of data-based approaches are limited.
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The Enabling Role of ICT to Mitigate the Negative Effects of Emotional and Social Loneliness of the Elderly during COVID-19 Pandemic.

TL;DR: In this paper, a qualitative exploration method based on four focus groups with elderly people aged 60 years or older and three in-depth personal interviews with experts in education of the elderly were carried out to understand the impact of use of ICT on the emotional well-being of elderly people during their confinement.
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Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults

TL;DR: In this paper , the authors introduce a conceptual model that outlines intersecting pathways of technology development that can produce and reinforce digital ageism in AI systems and also describe the broader ethical and legal implications and considerations for future directions in digital ageisms research to advance knowledge in the field and deepen our understanding of how ageism is fostered by broader cycles of injustice.
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Not Too Old for TikTok: How Older Adults Are Reframing Aging

Reuben Ng, +1 more
- 05 May 2022 - 
TL;DR: This paper explored how older adults use TikTok to engage in discourses on old age and found that nearly 3 in 4 videos featured older adults "defying age stereotypes" (71%), 18% featured them "making light of age-related vulnerabilities" (18%), and 11% involved older adults calling out ageism (11%).
References
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Journal ArticleDOI

Birds of a Feather: Homophily in Social Networks

TL;DR: The homophily principle as mentioned in this paper states that similarity breeds connection, and that people's personal networks are homogeneous with regard to many sociodemographic, behavioral, and intrapersonal characteristics.
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Critical questions for big data

TL;DR: The era of Big Data has begun as discussed by the authors, where diverse groups argue about the potential benefits and costs of analyzing genetic sequences, social media interactions, health records, phone logs, government records, and other digital traces left by people.

Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification

TL;DR: It is shown that the highest error involves images of dark-skinned women, while the most accurate result is for light-skinned men, in commercial API-based classifiers of gender from facial images, including IBM Watson Visual Recognition.
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Private traits and attributes are predictable from digital records of human behavior

TL;DR: It is shown that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender.
Journal ArticleDOI

Big Data, new epistemologies and paradigm shifts:

TL;DR: The authors examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines.
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