Hsiu-Hsuan Yeh

Hsiu-Hsuan Yeh

Publications

Spatio-temporal Analysis of Telecommunications Data: Effects of Residential Shifts and Smartphone Adoption on Mobility Patterns and Communication Behavior

Published in Taiwan Economic Association Master's Thesis Award — Honorable Mention (Econometrics), 2025

We use over 1.5 billion anonymized call records per month spanning from August 2013 to May 2014, where more than 500,000 phone numbers are involved, to study the impacts of residential shifts (events of changing home locations) and smartphone adoption on mobility and communication behaviors. We find significant time-variant effects for residential relocations. Migrants tend to call more frequently, engage in more diverse contact relationships, and primarily interact with existing distant friends during relocation periods. These effects quickly fade to original levels or continuously evolve toward negative states, such as less diverse interactions or shorter contact distances. From a mobility perspective, residential relocations cause users to have larger exploration areas and highly unpredictable movement patterns, though these effects also shift to more predictable movement over time. The notable upward shifts (nearly static) in mobility patterns after smartphone adoption are likely due to technological assistance in unfamiliar environments. For example, movement unpredictability increases along with relatively clearer directional preferences. Our work provides evidence-based policy implications that mobile and transportation infrastructure needs are worth considering during periods when large-scale population displacements or mobile technology upgrades occur.

Recommended citation: This is my master essay.
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Automation of Text-Based Economic Indicator Construction: A Pilot Exploration on Economic Policy Uncertainty Index

Published in In Proceedings of The 33rd ACM International Conference on Information and Knowledge Management, 2024

The growing popularity of text-as-data in various domain-specific applications and research has often relied on manually selected keywords or annotations. Although labor-intensive, expensive and time-consuming, the effectiveness of these efforts is not always guaranteed, especially in the early stages of research. This predicament raises the question of the extent to which large language models (LLMs) can aid in verifying the potential of a nascent research idea. This paper seeks to explore the reliability of LLM-suggested keywords in the automatic construction of the Economic Policy Uncertainty (EPU) index. Our findings confirm that LLMs can effectively automate the construction of EPU index. Furthermore, we delve into the potential of LLMs in enhancing the indicator construction process.

Recommended citation: Hsiu-Hsuan Yeh, Yu-Lieh Huang, Ziho Park, and Chung-Chi Chen. 2024. Automation of Text-Based Economic Indicator Construction: A Pilot Exploration on Economic Policy Uncertainty Index. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM '24).
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