Results 101 to 110 of about 46,435 (264)

Data, not documents: Moving beyond theories of information‐seeking behavior to advance data discovery

Journal of the Association for Information Science and Technology, Volume 76, Issue 4, Page 649-664, April 2025.
Abstract Many theories of human information behavior (HIB) assume that information objects are in text document format. This paper argues four important HIB theories are insufficient for describing users' search strategies for data because of assumptions about the attributes of objects that users seek.
Anthony J. Million, Jeremy York, Sara Lafia, Libby Hemphill   +3 more
wiley   +1 more source

ChatGPT for complex text evaluation tasks

Journal of the Association for Information Science and Technology, Volume 76, Issue 4, Page 645-648, April 2025.
Abstract ChatGPT and other large language models (LLMs) have been successful at natural and computer language processing tasks with varying degrees of complexity. This brief communication summarizes the lessons learned from a series of investigations into its use for the complex text analysis task of research quality evaluation.
Mike Thelwall
wiley   +1 more source

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

Journal 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

Journal 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

Critical questions for documenting collections as data: Provocations from developing datasheets for web archives datasets

Journal of the Association for Information Science and Technology, EarlyView.
Abstract Scholarship on documentation of datasets is increasingly concerned with capturing the context, socio‐technical processes, and decisions shaping data. “Datasheets for datasets” is a recent approach developed by researchers in machine learning that foregrounds transparency and uncovering bias through data documentation.
Emily Maemura, Helena Byrne
wiley   +1 more source

Conceptualizing algorithmic inequality and future agenda. An annual review of information science and technology (ARIST) paper

Journal of the Association for Information Science and Technology, EarlyView.
Abstract The issue of inequality caused by algorithms, termed ‘algorithmic inequality’, has recently attracted scholarly attention in many disciplines due to its profound implications for society. While the body of literature on algorithmic inequality has grown, there remains a lack of comprehensive understanding of its nature, drivers, and impact ...
Shiwei Jia, Jia Tina Du, Hui Yan
wiley   +1 more source

Unsupervised machine learning for multi‐system adverse event pattern detection in pharmacovigilance: A proof‐of‐concept analysis of fluoroquinolone reports in FAERS

British Journal of Clinical Pharmacology, EarlyView.
. Aims Traditional pharmacovigilance detects single drug–event associations but cannot readily characterize multi‐system adverse‐event patterns such as fluoroquinolone‐associated disability. We evaluated unsupervised machine learning for this purpose, using fluoroquinolones as an exemplar.
Niaz Chalabianloo, Sheikh S. Abdullah, Kamran Sedig, Flory T. Muanda   +3 more
wiley   +1 more source

Accelerating green heterocyclic synthesis: Convergence of AI, automation, and sustainable chemistry

Bulletin of the Korean Chemical Society, EarlyView.
Green heterocyclic synthesis and data‐driven tools such as AI, high‐throughput experimentation, continuous flow, and self‐driving laboratories have developed largely in parallel. This review connects them and asks how green metrics such as E‐factor and PMI might serve as explicit optimization targets rather than post‐hoc measures, toward sustainable ...
Noor Aisyah Ahmad Shah, Amirreza Mottafegh, Su‐Hyun Yoo, Jongwoon Kim, Minseon Byeon, Juhwan Noh, Yea‐Lee Lee, Jin Suk Myung, Gwang‐Noh Ahn   +8 more
wiley   +1 more source

Engineering programmable peptide hydrogels for chronic refractory wounds: A mechanism‐driven framework

BMEMat, EarlyView.
To break the self‐perpetuating pathology of chronic wounds, we propose a mechanism‐driven engineering framework for peptide‐based hydrogels. This review elucidates a hierarchical strategy—from molecular design to intelligent, multi‐functional systems—that enables these programmable biomaterials to dynamically intervene in key pathological loops and ...
Xiaoyu Lv, Xinyi Chao, Jiamin Zhang, Jianfeng Liu   +3 more
wiley   +1 more source

Sustaining Circular Innovation Under Volatile Market Conditions: The Critical Role of Industry Platforms

Business Strategy and the Environment, EarlyView.
ABSTRACT While industry platforms are widely recognized as enablers of circular innovation, we still know little about how they evolve to scale and sustain innovation as economic conditions tighten and circular economy funding schemes become more selective.
Eva Qi Wang, Julia A. Fehrer, Jonathan J. Baker, Roderick J. Brodie   +3 more
wiley   +1 more source