Time: Friday, 21/Mar/2025: 9:00am - 10:00am |
Location: Room 3 - Luddy 1104 |
AI Literature Review Systems: An Analysis of Performance, Affordances and Outputs for a Complex Topic in the Social Sciences
iSchool, University of Missouri, Columbia, MO, USA, United States of America
Introduction. Artificial intelligence has the potential to revolutionize the way that scholars produce work, including through the creation of literature reviews using free or low-cost systems. Despite the importance of the literature review, AI-powered tools to create literature reviews are understudied at present.
Method. To address this gap, four specialized tools were assessed. The complex area of study chosen was e-reading in English and Spanish, a field where differences are evident in the two languages. Systems were prompted to write a literature review of 500-1000 words, and the resulting outputs were analyzed based on the requirements for reviews of the literature.
Results. Although none of the systems allowed for all the identified criteria to be addressed, Scite allowed many criteria to be met and was able to produce text in Spanish as well as in English. The remaining three systems investigated, Jenni.ai, OpenRead, and Wisio, performed less favorably.
Conclusion(s). AI-powered systems show incredible promise, with one unstudied area being the creation of scholarly reviews of the literature. Although the kinds of research questions that might be examined in social sciences like LIS will necessarily be complex, until now little has been done to evaluate these systems.
How Does Digital Humanities Research Talk About AI?: A Bibliometric Analysis
1University of Missouri, United States of America; 2Indiana University Bloomington, United States of America
Introduction. Despite scholarly work that looked into artificial intelligence (AI)’s impact on digital humanities (DH), there has been little comprehensive investigation into how AI has been reflected and adopted in DH scholarship. This paper addresses this gap by asking: What patterns can be observed in AI integration in the DH scholarly discourse?
Method. A bibliometric analysis was conducted on 2,488 abstracts of articles published in three influential DH journals: Digital Scholarship in the Humanities, Digital Humanities Quarterly, and Journal of Cultural Analytics.
Analysis. Focusing on abstracts containing the term “AI” or “artificial intelligence,” this study conducted four analyses: (1) temporal analysis of AI mentions, (2) collocation analysis, (3) word vector analysis, and (4) topic modeling.
Results. AI has been discussed in DH scholarship well before its recent rise in prominence. The recurring themes in these discussions encompass both technological and human-centered aspects.
Conclusion(s). AI has been integral to DH, and the discourse around AI in DH reflects the field’s dual focus on technology and the humanities. The bibliometric analysis presented in this paper illustrates how information science can inform and guide methodological reflections in DH, offering new insights into the future development of the field.