Community Informatics

Data Discretion: Screen-Level Bureaucrats and Municipal Decision-Making

Public servants tasked with implementing rules or policies on the street-level often make discretionary decisions based on local context. Lipsky has labeled them street-level bureaucrats. During the COVID-19 pandemic, as most face-to-face interactions facilitated by local government moved online, many street-level decisions were moved to screens, representing the actions of who Bouvins and Zouridis refer to as screen-level bureaucrats. Discretionary decision-making among public servants continued, but much of it centered on the collection, analysis, and use of data.

Exploring Domestic Workers’ Risk Work During the COVID-19 Pandemic

While many occupations turned to remote work during the COVID-19 pandemic, domestic work by definition requires workers to enter other people’s households, and they often work in close proximity to their employers. With domestic workers proactively handling COVID19 risks as part of their already precarious jobs, there is a need for a conceptual understanding of risk management to aid this occupational group during a public health crisis.

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.

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.

“I thought I was going to die there:” Socio-political contexts and the plight of undocumented Latinx in the COVID-19 pandemic

Certain U.S. population groups have suffered higher rates of infection and mortality than whites during the COVID-19 pandemic, including Latinx. Public health officials blamed disparities on overcrowded housing and work in essential industries prior to the vaccine’s availability. This study (n=34) focuses on the intersectionality of social locations for undocumented Latinx immigrants living in a relatively affluent suburb and working in the construction and service sectors.

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.

Understanding the Present and Designing the Future of Risk Prediction IT in Fire Departments

This research will develop and design new data-driven risk prediction principles and management (DDRPM) tools that anticipate and manage a variety of community risks, which fire departments are increasingly required to respond to, including medical, fire, and safety emergencies. Today, much of their work focuses on community risk reduction (CRR), a paradigm that seeks to mitigate risks before they lead to emergencies in the first place. The CRR paradigm will leverage new data-driven risk prediction and management (DDRPM) tools to predict and respond to a variety of community risks.

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