Brady D. Lund
Research
My research aims to understand and address important issues at the intersection of information, data, and people, and to promote ethical and responsible practices in these fields, with an emphasis on international development.
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ResearchGate: https://www.researchgate.net/profile/Brady-Lund
Google Scholar: https://scholar.google.com/citations?user=IGZZD-UAAAAJ&hl=en&oi=ao
Publication Highlights
This paper provides an in-depth examination of the cutting-edge technology behind
ChatGPT, a highly sophisticated chatbot that has gained significant attention in recent
months. The paper is divided into three parts. The first part provides definitions of
some key concepts related to ChatGPT, such as natural language processing (NLP)
and artificial intelligence (AI), and explains how they play a role in the technology.
The second part delves into the history, technology and capabilities of Generative
Pretrained Transformer (GPT), the underlying technology of ChatGPT. It explains the concepts behind GPT, the process of its development, the scale of the program and the vast amount of data used to train it and its ability to perform a wide range of language-based tasks such as translation, question answering and text generation. The third part of the paper gives an example of ChatGPT’s abilities by providing the output of an interview with ChatGPT on the topic of how AI and GPT will impact academia and libraries. This section will explore how ChatGPT can be used to improve various library services and the ethical considerations that need to be taken into account when using it.
Chatting about ChatGPT: how may AI and GPT impact academia and libraries?
Doi link to the publisher's site: https://doi.org/10.1108/LHTN-01-2023-0009
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ChatGPT Conundrums: Probing Plagiarism and Parroting Problems in Higher Education Practices
Full-text available from the publisher's site: http://dx.doi.org/10.5860/crln.84.6.205
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The field of Natural Language Processing (NLP) has seen significant advancements in recent years, thanks in large part to the development of powerful language models such as ChatGPT. ChatGPT, short for Chat Generative Pre-trained Transformer, is a large-scale neural language model developed by OpenAI that is capable of generating human-like responses to natural language input. With its impressive performance on a range of language tasks, ChatGPT has quickly become one of the most widely used
language models in NLP research and application. The preceding paragraph showcases ChatGPT’s capabilities, as it was composed and formatted entirely using artificial intelligence (AI). Clearly, ChatGPT holds tremendous power when it comes to writing-based tasks. As noted in a recent C&RL News article by Christopher Cox and Elias Tzoc, ChatGPT, and similar large language model technologies, have the potential to be disruptive technologies, significantly affecting not just academic libraries but higher education as a whole. In this article, we aim to explore some of these potential issues and propose a few possibilities for how we, as information professionals, may be able to help address them as they emerge.
Review of k-means and k-medoids clustering
Doi link to the publisher's site: http://dx.doi.org/10.1108/PMM-05-2021-0026
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Purpose This literature review explores the definitions and characteristics of cluster analysis, a machine-learning technique that is frequently implemented to identify groupings in big datasets and its applicability to library and information science (LIS) research. This overview is intended for researchers who are interested in expanding their data analysis repertory to include cluster analysis, rather than for existing experts in this area. Design/methodology/approach. A review of LIS articles included
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Social media is an important component of a university’s marketing plan. It has become one of the most efficient and cost-effective avenues for reaching a large, targeted population, which makes knowledge of how to attract more followers and interactions important in the competitive world of higher education. This study investigates the quantitative relationships between universities’ Facebook
pages and interactions (reactions, comments, and shares) and a variety of university attributes (year the university was established, number of students enrolled at university, etc.) using Pearson Correlation and ANOVA tests. Findings indicate several attributes that hold moderate-to-strong correlations with
Facebook followers and interactions. This study identifies several areas for
further investigation.
Universities engaging social media users
Doi link to the publisher's site: https://doi.org/10.1080/08841241.2019.1641875
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The evolution and shift of research topics and methods in library and information science
Doi link to the publisher's site: https://doi.org/10.1002/asi.24474
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in the Library and Information Source (EBSCO) database that employ cluster analysis is performed. An overview of cluster analysis in general (how it works from a statistical standpoint, and how it can be performed by researchers), the most popular cluster analysis techniques and the uses of cluster analysis in LIS is presented. Findings The number of LIS studies that employ a cluster analytic approach has grown from about 5 per year in the early 2000s to an average of 35 studies per year in the mid- and late-2010s. The journal Scientometrics has the most articles published within LIS that use cluster analysis (102 studies). Scientometrics is the most common subject area to employ a cluster analytic approach (152 studies). The findings of this review indicate that cluster analysis could make LIS research more accessible by providing an innovative and insightful process of knowledge discovery. Originality/value This review is the first to present cluster analysis as an accessible data analysis approach, specifically from an LIS perspective.
Employing approaches adopted from studies of library and information science (LIS) research trends performed by Järvelin et al., this content analysis systematically examines the evolution and distribution of LIS research topics and data collection methods at 6-year increments from 2006 to 2018. Bibliographic data were collected for 3,422 articles published in LIS journals in the years 2006, 2012, and 2018. While the classification schemes provided in the Järvelin studies do not indicate much change, an analysis of subtopics, data sources, and keywords indicates a substantial impact of social media and data science on the discipline, which emerged at some point between the years of 2012 and 2018. These findings suggest a type of shift in the focus of LIS research, with social media and data science topics playing a role in well over one-third of articles published in 2018, compared with approximately 5% in 2012 and virtually none in 2006.
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Doi link to the publisher's site: https://doi.org/10.14254/1795-6889.2023.19-2.2
This research delves into the interplay between three pivotal literacies in the digital age–information literacy, data literacy, and privacy literacy—and the receptivity towards the adoption of emerging technology within communities, with a specific focus on the chatbot ChatGPT. The results of regression analysis indicate a positive association between the inclination to utilize ChatGPT for enhancing one's community and proficiency in information literacy and privacy literacy.
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Additional Recent Publications
Exploring the Potential Impact of Artificial Intelligence (AI) on International Students in Higher Education: Generative AI, Chatbots, Analytics, and International Student Success
Review of the Delphi method in library and information science research
The questionnaire method in systems research: an overview of sample sizes, response rates and statistical approaches utilized in studies
What Does Information Science Offer for Data Science Research?: A Review of Data and Information Ethics Literature
Read some of my recent articles:
Fear of AI, Christianity, and the Modern Library
Bothorship: AI chatbot authorship after two years
Qualitative Methods for Data Scientists
Blockchain Applications in Higher Education Based on the NIST Cybersecurity Framework
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Top Papers:
Chatting about ChatGPT: how may AI and GPT impact academia and libraries?