Social networks play a crucial role in developing economies. One of their most important functions is facilitating the flow of information, particularly about the efficacy of new technologies. This dissertation explores three aspects of this research agenda. First, I study how economists can estimate the structure of a social network...
Deduplication, also referred to as "entity resolution", is a common and crucial pre-processing step in the construction of social networks. Traditional deduplication methods compare the attributes (such as name and age) of potential matching pairs to estimate a match probability for a pair. Recently research has used clustering techniques for...
Deduplication, also referred to as "entity resolution", is a common and crucial pre-processing step in the construction of social networks. Traditional deduplication methods compare the attributes (such as name and age) of potential matching pairs to estimate a match probability for a pair. Recently research has used clustering techniques for...
The increasing availability of large-scale scholarly datasets offers an unprecedented opportunity to understand the fundamental predictability, uncertainty, and dynamics of science and innovation. In this dissertation, I present some of my contributions to the science of science and innovation in three distinct but related settings, through a combination of canonical...
The rise and racial gap in maternal mortality and morbidity in the US growing public health crisis. The US maternal mortality rate is double that of peer countries such as the UK and Canada. Even more striking, Black women are 243% more likely to die from childbirth-related causes. According to...
This dissertation asks how can researchers more equitably design sociotechnical interventions to support the information work of sheltered emerging adults. Through two research studies, I explore the technology use in fulfilling the information needs among this population as well as how their environment impacts their strengths and information practices. I...
Data Science and related fields like Artificial Intelligence, Machine Learning, and Statistics provide indispensable research methods for understanding a wide variety of phenomena from large datasets. However, as methodical and empirical as these methods aim to be, there are many subjective and discretionary choices that the data scientist must make...
Our experience of the physical world is mediated by our senses, but while most people have five senses, interactions with computer systems are largely limited to the visual sense. When working with nonvisual artifacts, like sound, on computers, such artifacts are typically transformed, or re-encoded, into something visual. Determining how...
This dissertation asks how researchers can create more equitable algorithmic systems. Ultimately, this thesis explores methods and implications of representing subjects of analysis in the design and evaluation of algorithmic systems. I also unpack how algorithmic tools measure and quantify human behavior, giving heed to the potential impacts of these...
Algorithmically-driven social platforms present a challenge for self-presentation and identity management by obscuring audiences behind algorithmic mechanisms. Users are increasingly aware of this and actively adapting through folk theorization, but we do not know how users are coping with the constant change endemic to these platforms. We also do not...