{"title":"Information retrieval or document retrieval? Terminological confusions and unrealistic goals in information science, exemplified in relation to generative artificial intelligence","authors":"Birger Hjørland","doi":"10.1002/asi.70057","DOIUrl":"https://doi.org/10.1002/asi.70057","url":null,"abstract":"<p>ChatGPT and related technologies have revived an old issue in information science (IS) concerning information retrieval (IR) versus document retrieval. Since 1950, the term IR has primarily been used as a misnomer for document retrieval. This problematic terminology reflects a desire to go beyond documents and provide, in response to user queries, not lists of documents but direct answers. Only with the emergence of large language models such as ChatGPT has the goal of directly informing users appeared to many as justifiable in relation to IR. Such models, however, still depend on input in the form of documents. A basic problem with large language models is their inability to establish a valid connection between their answers and the sources on which they are based. Whereas scholarly norms dictate that all claims be explicitly supported by the sources and arguments used, this cannot be done satisfactorily by ChatGPT, which represents a fundamental limitation of this technology. Neglecting the documentary basis in all forms of IR is naïve, and the core concept in IS should be understood as document retrieval. Recognizing this distinction is essential for enabling users to maintain control over the search and to perform “source criticism.”</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 5","pages":"714-726"},"PeriodicalIF":4.3,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://asistdl.onlinelibrary.wiley.com/doi/epdf/10.1002/asi.70057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Carolina Pradier, Lucía Céspedes, Vincent Larivière
{"title":"How multilingual is scholarly communication? Mapping the global distribution of languages in publications and citations","authors":"Carolina Pradier, Lucía Céspedes, Vincent Larivière","doi":"10.1002/asi.70055","DOIUrl":"https://doi.org/10.1002/asi.70055","url":null,"abstract":"<p>Language is a major source of systemic inequities in science, particularly among scholars whose first language is not English. Studies have examined scientists' linguistic practices in specific contexts; few, however, have provided a global analysis of multilingualism in science. Using two major bibliometric databases (OpenAlex and Dimensions), we provide a large-scale analysis of linguistic diversity in science, considering both the language of publications (<i>N</i> = 87,577,942) and of cited references (<i>N</i> = 1,480,570,087). For the 1990–2023 period, we find that only Indonesian, Portuguese, and Spanish have expanded at a faster pace than English. Country-level analyses show that this trend is due to the growing strength of the Latin American and Indonesian academic circuits. Our results also confirm the same-language preference phenomenon (particularly for languages other than English), the strong connection between multilingualism and bibliodiversity, and that social sciences and humanities are the least English-dominated fields. Our findings suggest that policies recognizing the value of both national-language and English-language publications have had a concrete impact on the distribution of languages in the global field of scholarly communication.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 5","pages":"699-713"},"PeriodicalIF":4.3,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://asistdl.onlinelibrary.wiley.com/doi/epdf/10.1002/asi.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Information behavior patterns and subjective digital well-being: An exploratory study on perceptions of adults living in Germany","authors":"Leyla Dewitz","doi":"10.1002/asi.70060","DOIUrl":"https://doi.org/10.1002/asi.70060","url":null,"abstract":"<p>This exploratory study examines patterns of digital information behaviors such as information seeking, use, sharing, evaluation, avoidance, and curation to determine how they relate to subjective digital well-being. To explore adults' personal views on their digital well-being, conceptualized here as subjective digital well-being, this study examines individuals' emotional responses to specific lived experiences with digital information. Semi-structured online interviews were conducted with 19 participants aged 18 to 67. The interviews incorporated activities with visual elements in Miro to stimulate reflection. Deductive and inductive coding were applied during analysis. The findings revealed that depending on the individual's experiential context, digital information behaviors elicit positive, negative, and ambivalent emotional responses, which affect subjective digital well-being. For example, information avoidance can be an intuitive or strategic response to manage information (over)load and regulate negative emotions, supporting digital well-being. Furthermore, curating digital information collections constitutes a means of regaining or sustaining subjective digital well-being. The study adds to theoretical knowledge that agency and self-regulation function as scaffolding mechanisms in digital information seeking, sharing, use, and evaluation, enabling individuals to build information resilience in digital enviornments, which in turn contributes to achieving and sustaining subjective digital well-being.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 5","pages":"727-746"},"PeriodicalIF":4.3,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://asistdl.onlinelibrary.wiley.com/doi/epdf/10.1002/asi.70060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial intelligence use and scientific innovation","authors":"Yuanyuan Liu, Yundong Xie, Xiaobei Shen, Dengsheng Wu","doi":"10.1002/asi.70043","DOIUrl":"https://doi.org/10.1002/asi.70043","url":null,"abstract":"<p>The rapid advancement of artificial intelligence (AI) technologies is profoundly reshaping scientific research and accelerating its progress. While prior studies have explored AI applications across various disciplines, an understanding of whether AI use contributes to scientific innovation remains limited. In this study, we propose the AI use score, a novel metric that quantifies the extent of AI use in scientific research. It includes two key dimensions: a term-based score, derived from the presence of AI-related terms in titles and abstracts, and a knowledge-based score, based on citations to AI-related literature in reference lists. Our findings reveal that AI use is positively and significantly associated with both scientific disruption and novelty, with this relationship being particularly pronounced in STEM disciplines. The association between term-based AI use and scientific innovation has steadily intensified over time. Notably, combining both dimensions of AI use shows the strongest correlation with innovative outcomes. Specifically, term-based AI use is more strongly linked to disruptive innovation, while knowledge-based AI use is more closely associated with scientific novelty. Furthermore, we uncover the mechanism of how AI use influences scientific innovation by exploring the text similarity of publications.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 5","pages":"682-698"},"PeriodicalIF":4.3,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"How does information resource value of AI-generated content emerge? An exploratory study from the user evaluation perspective","authors":"Yu Zhu, Chenyu Li, Jiyuan Ye","doi":"10.1002/asi.70061","DOIUrl":"https://doi.org/10.1002/asi.70061","url":null,"abstract":"<p>AI-generated content (AIGC), a novel information resource, has seen an irreversible growth trend in the information ecosystem. However, most prior AIGC studies focus on technological adoption and static evaluation, while little attention has been paid to the value emergence and value-added processes of AIGC at the information resource level. This study employed in-depth, semi-structured interviews with 22 experienced AIGC users and utilized content analysis to examine the factors influencing users' perceived value of AIGC, identify value-added processes, and explore the underlying mechanisms. Based on these findings, we propose the AIGC-Value-Added Framework, delineating four user-AIGC interaction phases: value exposure, value forming, value anchoring, and value realization, which collectively enhance the resource value of AIGC. This study introduces an integrative framework for understanding how value emerges and is added to AIGC as an information resource, thereby enriching the Library and Information Science literature on information value-adding practices in the AIGC context and offering stakeholders practical insights for optimizing AIGC leverage.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 5","pages":"747-764"},"PeriodicalIF":4.3,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A diary study of information-intensive work tasks in the modern workplace: Investigating task descriptions and task processes","authors":"Afeng Wang, Yiming Zhao, Feicheng Ma","doi":"10.1002/asi.70037","DOIUrl":"https://doi.org/10.1002/asi.70037","url":null,"abstract":"<p>The work-task-based framework offers a cohesive perspective for understanding workplace information behavior, guiding empirical exploration of information engagement in modern work environments. This study investigates both task descriptions and task processes of information-intensive work tasks through diaries and follow-up interviews to capture authentic user experiences. Data from 52 work tasks across diverse organizations reveal that the most frequent topics include <i>Reference</i>, <i>Business</i>, <i>Science</i>, <i>Society</i>, and <i>Computers</i>, with Intellectual and Decision/Solution product types being predominant. Performers typically begin with moderate or high work task knowledge. On average, each work task involves 2.5 seeking tasks and 5.3 search tasks. Seeking tasks are mainly linked to resolution-oriented information use, while search tasks rely on external sources for factual resolution and verification. Work task topics, product, prior knowledge, subtasks, and duration significantly influence source selection and information use. As work tasks progress, the number of search tasks and clarification use decreases, whereas resolution and verification use increase. These findings refine theoretical models of task-driven information behavior and provide practical insights for designing adaptive information systems and AI tools to better support evolving work task processes and enhance work performance.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 5","pages":"663-681"},"PeriodicalIF":4.3,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Repetition and modality in information trustworthiness judgments: Investigating the illusory truth effect in multimodal health information environments","authors":"Shaoxiong Fu, Jinling Song, Xiaoyu Chen","doi":"10.1002/asi.70046","DOIUrl":"https://doi.org/10.1002/asi.70046","url":null,"abstract":"<p>The illusory truth effect, in which repeated exposure increases trust regardless of accuracy, poses significant challenges to the perceived trustworthiness of health information in digital environments. Although repetition is known to enhance cognitive fluency, little is known about how different modalities influence this effect. Drawing on cognitive fluency and dual-coding theories, this research investigates how repetition and modality interact to shape trustworthiness judgments of health information. Three online experiments were conducted to examine users' perceived trustworthiness of health information across different conditions. Experiment 1 the effect of repetition on messages varying in truthfulness (true vs. false) and familiarity (familiar vs. unfamiliar). Experiments 2 and 3 examined the role of modality (text-only, text-and-image, short video) and cross-modal repetition. Results show that, in the text-only condition, an unfamiliar true message is perceived as more trustworthy than other information. Repetition significantly increases perceived trustworthiness in text-and-image and short video formats, albeit with diminishing returns after two exposures. Cross-modal repetition further amplifies such trustworthiness effects. These findings extend theoretical understanding of the illusory truth effect in multimodal health information environments and offer practical insights for designing interventions to reduce the spread of misinformation on social media.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 4","pages":"640-658"},"PeriodicalIF":4.3,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147570221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Can artificial intelligence debunk health misinformation more effectively than humans? A three-dimensional persuasion analysis","authors":"Xinyu Ji, Xing Zhang","doi":"10.1002/asi.70049","DOIUrl":"https://doi.org/10.1002/asi.70049","url":null,"abstract":"<p>Health misinformation presents significant challenges to public well-being, making effective debunking strategies crucial. While artificial intelligence (AI) shows potential in generating debunking texts, its persuasiveness compared to human-generated content remains underexplored. Drawing on Aristotle's three modes of persuasion, this study investigated the persuasive effectiveness of AI versus human-generated health debunking texts through three complementary studies. Our findings reveal a novel pattern: AI-generated texts significantly outperformed human texts in pathos (emotional appeal) and logos (logical argument) but underperformed in ethos (credibility), with all three dimensions serving as significant mediators of persuasiveness. More importantly, we demonstrate that source labeling effects are not uniform. While “AI-written” labels reduced perceived persuasiveness for both AI and human texts, this algorithmic aversion was attenuated when argument quality (logos) was made salient. These findings advance persuasion theory by revealing that classical rhetoric operates differently for AI versus human sources and that algorithmic aversion is context-dependent rather than universal. The results offer both theoretical insights into human-AI communication and practical guidance for deploying AI in health misinformation mitigation.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 4","pages":"563-579"},"PeriodicalIF":4.3,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147566139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Narrating affect: Archives, affect, and the construction of identity","authors":"Li Su, Zhiying Lian","doi":"10.1002/asi.70065","DOIUrl":"https://doi.org/10.1002/asi.70065","url":null,"abstract":"<p>This paper examines how affect operates within grassroots archival practices as both a structuring force in curatorial work and an outcome of audience engagement. Focusing on identity formation and collective memory in community-based, non-institutional archives, the study integrates structuration theory and affect theory through a qualitative case study of the Picun Culture and Arts Museum of Migrant Labourers (PCAMML) in China. Drawing on thematic analysis of the interviews with the curator, exhibition narratives, and visitor responses from guestbooks and social media (2011–2025), the study traces the circulation of affect across curatorial motivation, narrative design, and audience reception. Findings identify three interrelated affective layers: curatorial motivations shaped by exclusion, longing, and hope; exhibition narratives structured to guide affective progression from injury to collective agency; and visitor responses characterized by resonance, recognition, and imaginative mobilization. Affect is shown to function not as a transmissible emotion but as a relational and structural force that mediates between embodied experience and social meaning. By conceptualizing community archives as affective infrastructures, this study extends archival affect theory beyond Western contexts and demonstrates how grassroots archives enable marginalized communities to negotiate belonging, reclaim historical presence, and cultivate cultural agency. The findings suggest the need to expand archival evaluation and collaboration frameworks to account for affective and experiential dimensions of archival practice.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 4","pages":"596-609"},"PeriodicalIF":4.3,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147566132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The diverging effect of prestige and experience on the use of artificial intelligence knowledge","authors":"Nannan Zhao, Linzhuo Li","doi":"10.1002/asi.70068","DOIUrl":"https://doi.org/10.1002/asi.70068","url":null,"abstract":"<p>This paper examines the relationship between scientists' experience and prestige and their use of artificial intelligence (AI) knowledge. Analyzing citation patterns from 5 million papers (1990–2024) citing AI literature and 1.1 million authors, we find that prestige positively correlates with citing highly visible AI work, while experience shows the opposite pattern. This divergence persists both within and beyond Computer Science contexts. We interpret these findings as suggesting that prestige is associated with social mechanisms linked to knowledge convergence toward mainstream work, while experience may be associated with knowledge diversity. These findings also reveal concerning concentration trends in AI knowledge utilization and inform strategies for more effective scientific knowledge use.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"77 4","pages":"580-595"},"PeriodicalIF":4.3,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147568647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}