Category: Monthly Webinars

Abstract: Large language models (LLMs) have created unprecedented opportunities for analyzing and generating language data on a massive scale, which has the potential to transform the field of social sciences since language data play a central role in all areas.  In this talk, we present a road map for using LLMs as computational social science… Continue reading Using LLMs for Computational Social Science: Challenges and Opportunities

Abstract: Here we represent human lives in a way that shares structural similarity to language, and we exploit this similarity to adapt natural language processing techniques to examine the evolution and predictability of human lives based on detailed event sequences. We do this by drawing on a comprehensive registry dataset, which is available for Denmark… Continue reading life2vec: Life trajectories in high dimensional spaces

Abstract: This study builds on life course theory, focusing on predicting future life events (ages 56-60) based on past sequences (ages 18-55). Using the Transformer encoder-decoder framework, we treat life events as sequential data, similar to words in a sentence, to capture patterns and relationships over time. With only 11 social employment states and basic… Continue reading Applying Transformers to Predict Life Course Sequences

Abstract: Digital technologies have brought about a significant shift in the way people from different social groups participate in politics through increased information openness. However, the effects of information openness on the equality of participation remains controversial. In this paper, we argue that in developing countries, information openness empowers disadvantaged groups by reducing the cost… Continue reading Byte the Power: Information Openness Increases Participatory Equality in China

Abstract: Shifting attachments to social groups are a constant in the modern era. What accountsfor variation in the strength of group identification? Whereas prior work has emphasizedgroup-level properties and individual differences, we instead highlight the role ofpositions within network structure. Distilling insights from prior work on networks andidentity, we propose that identification strength is positively… Continue reading Locally Ensconced and Globally Integrated: How Positions in Network Structure Relate to a Language-Based Model of Group Identification

Abstract: Professor Han will present a series of her published and ongoing works that provide an overview of how unstructured big textual data can be collected and analyzed using computational social science methods in the research area of social stratification, specifically in the study of school-to-work transition. She will compare these new approaches to classical… Continue reading School-to-Work Transition in Big Data

Abstract: We propose a method for estimation and inference for bounds for heterogeneous causal effect parameters in general sample selection models where the treatment can affect whether an outcome is observed and no exclusion restrictions are available. The method provides conditional effect bounds as functions of policy relevant pre-treatment variables. It allows for conducting valid… Continue reading Heterogeneous Treatment Effect Bounds under Sample Selection with an Application to the Effects of Social Media on Political Polarization

Abstract: Guanxi research would benefit from an empirical portrayal of holistic guanxi network structures and consideration of sociologically meaningful antecedents such as one’s cultural value endorsement. This study, drawing on the reported trustworthiness of a rich array of referees in one’s guanxi network collected from the Traditional Culture and Cognitive Pattern Survey, identifies two types… Continue reading Mapping Out the Interpersonal Boundary Stones in Contemporary China: Guanxi Network Structure and Its Association with Traditional Culture Endorsement

Abstract: The COVID-19 pandemic has been a global disaster with significant impacts. In response to it, an unprecedented amount of data was generated. This data has been utilized in various ways for research and policymaking. In this webinar, Professor Ko will examine the significance of data quality from the perspective of data analytics and explores… Continue reading Data Analytics in the Public Sector: The Case of Korea’s COVID-19 Response

Abstract: What makes a video popular, what drives collective attention online, what are the commonalities and differences between clicks and transactions in a market? This talk aims to answer these three questions.  I will first discuss a physics-inspired stochastic time series model that explains and forecasts the seemingly unpredictable volumes of views over time. This… Continue reading Understanding Online Attention: from Item Popularity to Market Landscapes