Results 181 to 190 of about 6,721 (260)

Developing a critical caste analysis within information science and technology: A research review: An Annual Review of Information Science and Technology (ARIST) paper

open access: yesJournal of the Association for Information Science and Technology, EarlyView.
Abstract Caste—an ascriptive social hierarchy in South Asia and its diaspora—is a globalized phenomenon. Recent caste‐based discrimination, particularly in technology companies and anti‐caste efforts to address it, has compelled academia, policy, and the technology industry to better understand contemporary mechanics of caste.
Nayana Kirasur, Britt Paris
wiley   +1 more source

Affective dimensions in the information behavior of forcibly displaced people: A literature review. An Annual Review of Information Science and Technology (ARIST) paper

open access: yesJournal of the Association for Information Science and Technology, EarlyView.
Abstract This review analyzed 241 scholarly articles published between 2010 and 2025 in information science venues to examine how affect shapes refugees' information behavior during forced migration and to identify additional contextual factors. It identifies seven affective dimensions: anxiety, shame and stigma, grief and loss, frustration, (mis)trust,
Maja Krtalić, Lilach Alon
wiley   +1 more source

What is user engagement? revisited: A comprehensive review of the concept of user engagement from 2010 to 2025. An Annual Review of Information Science and Technology (ARIST) paper

open access: yesJournal of the Association for Information Science and Technology, EarlyView.
Abstract User engagement (UE) has long been proposed as a holistic framework for understanding user‐technology interactions and a mediator for outcomes of digital technology use, such as learning, health behavior change, information acquisition, and social connectivity.
Heather L. O'Brien
wiley   +1 more source

Principal Component‐Based Classification of Blazar Candidates of Uncertain Type in the 4FGL/LAT

open access: yesAstronomische Nachrichten, EarlyView.
ABSTRACT We adopted principal component analysis (PCA), linear discriminant analysis (LDA), and support vector machines (SVM), to study classification for a sample of 2708 Fermi blazars: 1142 BL Lac objects (BLLs), 759 flat spectrum radio quasars (FSRQs), and 807 blazar candidates of uncertain type (BCUs).
Wen‐Xin Yang   +13 more
wiley   +1 more source

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