Journal of the Association for Information Science and Technology最新文献_第5页

Artificial intelligence use and scientific innovation 人工智能应用与科学创新

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-04-02 Epub Date: 2025-11-28 DOI: 10.1002/asi.70043

Yuanyuan Liu, Yundong Xie, Xiaobei Shen, Dengsheng Wu

{"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":"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.","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}

引用次数: 0

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-04-02

引用次数: 0

How does information resource value of AI-generated content emerge? An exploratory study from the user evaluation perspective 人工智能生成内容的信息资源价值如何显现？用户评价视角下的探索性研究

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-04-02 Epub Date: 2026-02-12 DOI: 10.1002/asi.70061

Yu Zhu, Chenyu Li, Jiyuan Ye

{"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":"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.","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}

引用次数: 0

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-04-02

引用次数: 0

A diary study of information-intensive work tasks in the modern workplace: Investigating task descriptions and task processes 现代工作场所信息密集型工作任务的日记研究：调查任务描述和任务过程

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-04-02 Epub Date: 2025-11-14 DOI: 10.1002/asi.70037

Afeng Wang, Yiming Zhao, Feicheng Ma

{"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":"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 Reference, Business, Science, Society, and Computers, 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.","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}

引用次数: 0

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-03-06

引用次数: 0

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-03-06

引用次数: 0

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-03-05

引用次数: 0

Repetition and modality in information trustworthiness judgments: Investigating the illusory truth effect in multimodal health information environments 信息可信度判断的重复与模态：多模态健康信息环境中的虚幻真实效应研究

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-03-05 Epub Date: 2025-12-29 DOI: 10.1002/asi.70046

Shaoxiong Fu, Jinling Song, Xiaoyu Chen

{"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":"10.1002/asi.70046","url":null,"abstract":"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.","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}

引用次数: 0

Can artificial intelligence debunk health misinformation more effectively than humans? A three-dimensional persuasion analysis 人工智能能比人类更有效地揭穿健康错误信息吗？三维说服分析

IF 4.3 2区管理学

Journal of the Association for Information Science and Technology Pub Date : 2026-03-05 Epub Date: 2026-01-16 DOI: 10.1002/asi.70049

Xinyu Ji, Xing Zhang

{"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":"10.1002/asi.70049","url":null,"abstract":"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.","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}

引用次数: 0