Hyung Wook Choi

Language evolves continuously, and the meanings of words shift as communities of practice adapt to cultural, technological, and institutional changes. This dissertation addresses a persistent gap in existing computational approaches to semantic shift: while embedding-based methods can detect when and how word meanings diverge, they rarely preserve detected shifts as structured, reusable scholarly records. The result is that semantic change is routinely identified but seldom documented in a form that supports reproducibility, longitudinal reanalysis, or integration with knowledge organization systems. To address this gap, the dissertation proposes a two-layered framework. The first layer develops computational methods for detecting semantic drift across time and domains. Building on temporally aligned Word2Vec and contextual BERT representations, the framework quantifies drift through three complementary indicators---positional change, neighborhood overlap, and fuzziness score---and models semantic evolution as gradual and potentially overlapping rather than binary. A seed-based context anchor, grounded in historically attested dictionary definitions, ensures that measured displacement reflects genuine semantic change relative to a stable, interpretable reference state. The second layer addresses documentation. Detected shifts are first abstracted into a purpose-built Versioned Semantic Shift Ontology (VERSO), which represents semantic change as domain-level conceptual objects independent of specific pipelines or file formats. These VERSO records are then embedded within a PROV-O-compliant provenance layer that links semantic states through versioning and derivation relations, preserving the full lineage of conceptual change and enabling auditing, reanalysis, and cumulative extension. An interactive visualization system, TRACE, renders VERSO--PROV-O records as navigable sense genealogies that expose branching, convergence, and provenance on demand. The framework is validated through four case studies. The analysis of network (1816--2025) traces multi-domain semantic generalization across physical, organizational, social, and computational registers. The analysis of cloud documents a focused cross-domain extension from meteorological to computing discourse, characterized by a transitional fuzziness peak followed by sense consolidation. A third case study applies the framework to a cluster of stigma-related terms in addiction discourse---junkie, addict, substance abuse, and user---demonstrating that corpus-derived drift measurements can be linked to externally dated policy events within the archival architecture, and that the same terminological cluster follows structurally distinct trajectories across registers. A fourth case study disaggregates this cluster to examine junkie as a case of partial semantic shift, in which the drug-referential sense is progressively attenuated while the bleached modifier-bearing sense expands, producing concurrent sense coexistence that neither substitution nor accumulation models adequately capture. The dissertation makes three contributions: to computational linguistics, through fuzziness-aware methods for domain-sensitive detection of gradual and overlapping semantic change; to ontology engineering, through a two-stage versioning mechanism that separates semantic abstraction from provenance tracking; and to information science, through a reproducible infrastructure that treats semantic shift as an archival object with long-term scholarly value.

Advertisements have always been a part of our cultural heritage, and this also applies to online web advertisements. Unlike print ads, there are serious technical challenges involved in archiving and successfully replaying ads displayed in web pages. To explore these challenges, we created a small dataset of 250 web ads. Ultimately, we collected and archived 279 ads, which we classified into 5 different categories: combination ads, image ads, embedded web page ads, video ads, and text‐only ads. In our sample, combination ads were the most prevalent and, not surprisingly, text‐only ads were the easiest to archive and replay. During the course of this study, we encountered five major problems in archiving and replaying the web ads. We detail the issues uncovered and provide suggestions for ameliorating the replay of some web ads, in addition to other dynamically loaded embedded web resources.

Purpose: In the current era of the coronavirus disease 2019 pandemic, the trend of sharing new research results through preprint platforms is receiving more attention from researchers than ever before. Preprints have been recognized as a primary and essential method to disseminate new findings faster than traditional publications. Therefore, it has become necessary for journals and editors to acknowledge these changes, prepare preprint policies, and notify authors accordingly. This study aimed to review the status of preprint policies of international publishers and Asian academic society journals.Methods: In total, 383 Asian academic society journals registered in Science Citation Index Expanded were selected as a dataset for analysis between December 11, 2020 and January 8, 2021. Three different parameters were investigated whether each journal had a preprint policy, whether journals allowed preprint manuscripts to be submitted, and whether preprint articles were allowed to be included in the references.Results: Among the 383 Asian academic society journals from 22 countries, only 28 journals accepted preprint manuscripts, and eight allowed the use of preprint manuscripts as references. Japan had the most journals that both had preprint policies and accepted preprint manuscripts, with 13 journals, followed by Korea with 10 journals.Conclusion: Despite the limitations of this study, the results show that editors and journal staff should understand the current preprint trend and try to prepare preprint policies that best meet the journals’ and authors’ interests.

Background: Diet-tracking mobile apps have gained increased interest from both academic and clinical fields. However, quantity-focused diet tracking (eg, calorie counting) can be time-consuming and tedious, leading to unsustained adoption. Diet quality—focusing on high-quality dietary patterns rather than quantifying diet into calories—has shown effectiveness in improving heart disease risk. The Healthy Heart Score (HHS) predicts 20-year cardiovascular risks based on the consumption of foods from quality-focused food categories, rather than detailed serving sizes. No studies have examined how mobile health (mHealth) apps focusing on diet quality can bring promising results in health outcomes and ease of adoption. Objective: This study aims to design a mobile app to support the HHS-informed quality-focused dietary approach by enabling users to log simplified diet quality and view its real-time impact on future heart disease risks. Users were asked to log food categories that are the main predictors of the HHS. We measured the app’s feasibility and efficacy in improving individuals’ clinical and behavioral factors that affect future heart disease risks and app use. Methods: We recruited 38 participants who were overweight or obese with high heart disease risk and who used the app for 5 weeks and measured weight, blood sugar, blood pressure, HHS, and diet score (DS)—the measurement for diet quality—at baseline and week 5 of the intervention. Results: Most participants (30/38, 79%) used the app every week and showed significant improvements in DS (baseline: mean 1.31, SD 1.14; week 5: mean 2.36, SD 2.48; 2-tailed t test t29=−2.85; P=.008) and HHS (baseline: mean 22.94, SD 18.86; week 4: mean 22.15, SD 18.58; t29=2.41; P=.02) at week 5, although only 10 participants (10/38, 26%) checked their HHS risk scores more than once. Other outcomes, including weight, blood sugar, and blood pressure, did not show significant changes. Conclusions: Our study showed that our logging tool significantly improved dietary choices. Participants were not interested in seeing the HHS and perceived logging diet categories irrelevant to improving the HHS as important. We discuss the complexities of addressing health risks and quantity- versus quality-based health monitoring and incorporating secondary behavior change goals that matter to users when designing mHealth apps.

BACKGROUND Diet-tracking mobile apps have gained increased interest from both academic and clinical fields. However, quantity-focused diet tracking (eg, calorie counting) can be time-consuming and tedious, leading to unsustained adoption. Diet quality—focusing on high-quality dietary patterns rather than quantifying diet into calories—has shown effectiveness in improving heart disease risk. The Healthy Heart Score (HHS) predicts 20-year cardiovascular risks based on the consumption of foods from quality-focused food categories, rather than detailed serving sizes. No studies have examined how mobile health (mHealth) apps focusing on diet quality can bring promising results in health outcomes and ease of adoption. OBJECTIVE This study aims to design a mobile app to support the HHS-informed quality-focused dietary approach by enabling users to log simplified diet quality and view its real-time impact on future heart disease risks. Users were asked to log food categories that are the main predictors of the HHS. We measured the app’s feasibility and efficacy in improving individuals’ clinical and behavioral factors that affect future heart disease risks and app use. METHODS We recruited 38 participants who were overweight or obese with high heart disease risk and who used the app for 5 weeks and measured weight, blood sugar, blood pressure, HHS, and diet score (DS)—the measurement for diet quality—at baseline and week 5 of the intervention. RESULTS Most participants (30/38, 79%) used the app every week and showed significant improvements in DS (baseline: mean 1.31, SD 1.14; week 5: mean 2.36, SD 2.48; 2-tailed t test t29=−2.85; P=.008) and HHS (baseline: mean 22.94, SD 18.86; week 4: mean 22.15, SD 18.58; t29=2.41; P=.02) at week 5, although only 10 participants (10/38, 26%) checked their HHS risk scores more than once. Other outcomes, including weight, blood sugar, and blood pressure, did not show significant changes. CONCLUSIONS Our study showed that our logging tool significantly improved dietary choices. Participants were not interested in seeing the HHS and perceived logging diet categories irrelevant to improving the HHS as important. We discuss the complexities of addressing health risks and quantity- versus quality-based health monitoring and incorporating secondary behavior change goals that matter to users when designing mHealth apps.

Purpose: The “Principles of transparency and best practice in scholarly publishing” are of increasing importance in an open science environment as a way to increase the transparency and quality of academic society journals. However, little previous research has investigated the application of this new guideline in practice. The aim of this study was to investigate the degree to which this guideline is being applied by Korean academic society– published journals listed in Journal Citation Reports.Methods: The researchers investigated the homepages of 59 Korean academic society– published journals to evaluate whether they had adopted the 33 items listed in the guideline. Based on the information available on the journals’ homepages, each item was classified as ‘yes’ or ‘no’ within the four categories of basic journal information, publication ethics, copyright and archiving information, and profit model.Results: The basic journal information category was generally well-practiced, with the exceptions of the peer review process, readership, and author fees. The copyright and licensing information category was also well-practiced, with the exception of policies on posting accepted articles with third parties and archiving items. However, most items in the publication ethics category were not well practiced, with the exception of authorship and intellectual property. All items in the profit model category were infrequently implemented.Conclusion: These findings serve as a good indicator for Korean journal editors of areas for improvement. It may be helpful to review journals’ publication policies and homepages to comply with international publishing standards.

Diet-tracking mobile apps have been effective in behavior change. At the same time, quantity-focused diet tracking (e.g., calorie counting) can be time-consuming and tedious, leading to unsustained adoption. Diet Quality—focusing on high-quality dietary patterns rather than quantifying diet into calories—has shown effectiveness in improving heart disease risk. Healthy Heart Score (HHS) predicts 20-year cardiovascular risks based on quality-focused food category consumptions, rather than detailed serving sizes. No studies have examined how mobile health apps focusing on diet quality can bring promising results on health outcomes and ease of adoption. We designed a mobile app to support the HHS informed quality-focused dietary approach by enabling users to log simplified diet quality and view its real-time impact on future heart disease risks. Users were asked to log food categories that are the main predictors of HHS. We measured the app’s feasibility and efficacy on improving individuals’ clinical and behavioral factors affecting future heart disease risks and app use. We recruited 38 overweight or obese participants at high heart disease risk, who used the app for 5 weeks and measured weight, blood sugar, and blood pressure, HHS, and Diet Score (DS) measuring diet quality at baseline and the fifth week of the intervention. The majority used the application every week (84%) and significantly improved DS and HHS at the fifth week (p<0.05), although only 10 participants (31%) checked their risk scores more than once. Other outcomes did not show significant changes. Our study showed logging simplified diet quality significantly improved dietary behavior. The participants were not interested in seeing HHS, and the participants perceived logging diet categories irrelevant to improving HHS as important. We discuss the complexities of addressing health risks, quantity vs. quality-based health monitoring, and incorporating secondary behavior change goals that matter to users when designing mobile health.

, the Directory of Open Access Journals, the Committee on Publication Ethics, and the World Association of Medical Editors declared the third version of "Principles of transparency and best practice in scholarly publishing" to ensure transparency and quality in journal publications. This study is aimed at assessing the guidelines from the journals' websites manually. Methods: In this study, three researchers investigate the homepages of 781 academic society-published journals that are registered in the Science Citation Index Expanded and whether these journals are effectively adopting these new guidelines. In this paper, 33 items from the guidelines are examined. The 33 items are rearranged into four different categories: basic journal information; publication ethics; copyright and archiving information; and profit model. The researchers count yes or no after checking the adopting status on the journal homepage and dividing into four scales: 0% to 25% for is rarely practiced, 26% to 50% for is poorly practiced, 51% to 75% for is adequately practiced, and 76% to 100% for is well practiced. Results: Of the 33 items, 10 are found to be poorly or rarely practiced, including readership, data sharing, archiving policies, and profit model information. Conclusion: It could be the most up-to-date indicator of the current status of applying best practice guidelines. Society journal editors especially from Asia should evaluate their journals regarding "Principles of transparency and best practice in scholarly publishing".