Quantitative Study

Examining the Shift in Political Inclination of Korean Middle School Language Textbooks between the Independence and the Korean War (1945–1953): A Network Modeling Approach

This study leverages network modeling methodologies to examine the distribution of political inclinations in Korean middle school language textbooks from 1945 to 1953. The textbooks included in this study are 82 textbooks, where 37 of which from the U.S. military government period (1945-1948), 30 of which from the South Korean government establishment period (1948-1950), and 15 of which from the wartime period (1950-1953).

An Evaluation of GPT-4V for Transcribing the Urban Renewal Hand-Written Collection

In November 2024, OpenAI released GPT- 4V(ision), which includes Optical Character Recognition (OCR) capabilities. Given that much of the data curation, processing, and cleaning can be managed through user-friendly prompts (i.e., chat), we aim to conduct an initial assessment of GPT-4V’s effectiveness in transcribing hand-written documents from the urban renewal collection. If GPT-4V can accurately digitize hand-written documents through carefully crafted prompts, it could become a valuable tool for nonexperts in transcribing historical documents on a large scale.

Aggregate-Level Analysis of Information Behavior: A Study of Public Library Book Circulation

Information behavior research to date has mainly focused specific cases or representative surveys at the individual level, because each individual has unique contexts that shape their behavior. However, they have not fully benefited from aggregate-level analyses due to mainstream theories’ focus on a contextualized understanding of information. To address this gap, we adopt the theory of local information landscapes, that focuses on the material aspects of community dynamics, and analyze national-level aggregate data on book circulations in public libraries across South Korea.

AI or Authors?: A Comparative Analysis of BERT and ChatGPT’s Keyword Selection in Digital Divide Studies

Author keywords attached to academic papers are often used in intellectual structure analysis. However, the length and selection criteria for keywords vary across publications and, even some publishers do not require keywords for their articles. To explore the opportunity to overcome such keyword inconsistency issues, this study compared author keywords from papers focused on the digital divide with those extracted using the language models, BERT and ChatGPT.

Visualizing Local Information Inequality in South Korea: An AI-Based Approach Using Public Library Data

The goal of the project is to understand information inequality across geographical regions in South Korea and visualize them using an AI-backed visualization tool. Our plan, spanning three years, revolves around the development of an intuitive platform for the purpose of visualizing these disparities. During the first year, we aim to construct comprehensive metrics for assessing the level of informational inequality, based on the theory of local information landscapes (LIL theory).

The NYC311 App & Community Engagement in Coproducing Municipal Services

In the public sector, governments and the people they serve increasingly collaborate to coproduce public services. To support the coproduction of municipal services, specifically, local governments have incorporated various digital technologies into their information systems. How do digital technologies affect community residents' engagement in coproducing municipal services?

Two-sided Cultural Niches: Topic Overlap, Geospatial Correlation, and Local Group Activities on Event-based Social Networks

As event-based social networks (EBSNs) such as Meetup.com and Facebook Events gain popularity in managing local events like farmers' markets and social gatherings, they create two-sided cultural niches where event organizers and participants benefit from the platform while influencing each other. Among various factors, niche overlap, an ecological feature, has been studied as a key factor that shapes the success of online communities.

Mapping Information Ecology: Understanding the Fragmentation of Disability Service Information

As organizations and individuals provide various information to multiple systems within a region, the information becomes fragmented, making it difficult for people to access the necessary information. Individuals have limited resources to navigate all the sources and use only part of the available ones. Disability service information is further fragmented due to diverse actors, ranging from government agencies to for-profit organizations, who often provide only partial information.

How Do YouTubers Collaborate? A Preliminary Analysis of YouTubers’ Collaboration Networks

Online videos such as those streamed through YouTube are largely produced by individual users rather than traditional mass media, partly due to the incentive structure of the platforms. As part of the strategy to increase the audience, many content creators collaborate with other creators to attract subscribers and diversify their content. This behavior can be conceptualized as “coopetition” as they cooperate for their channels’ success while competing with one another for the limited pool of audience.

Towards an Expectation-Oriented Model of Public Service Quality: A Preliminary Study of NYC 311

The 311 system has been deployed in many U.S. cities to manage non-emergency civic issues such as noise and illegal parking. To assess the performance of 311-mediated public service provision, researchers developed models based on execution time and the status of execution. However, research on user satisfaction suggests that the level of individuals’ perception is asymmetric with respect to the quality of services, because negative experiences have a stronger impact on people’s dissatisfaction than positive experiences do for satisfaction.

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