News

Speaker: Kristina Lerman, Principal Scientist, University of Southern California Information Sciences Institute

Spring 2023 has been an exhilarating season for the PittCSS community! We’ve had the incredible opportunity to learn from a remarkable lineup of external speakers who graced our PittCSS seminars with their expertise and shared their research:

We are thrilled to share with you an exciting event that took place on March 23, 2023. Our members, Nefriana and Alireza, had the incredible opportunity to present their research at the University of Pittsburgh DINS Seminar Series. The seminar was attended not only by current SCI students but also by incoming PhD students who were eager to gain insights into the life of a PhD student in SCI.

Yiling’s recent work analyzed millions of research articles published over four decades to understand how yesterday’s novelty forms today’s scientific conventions, which condition the novelty-and surprise-of tomorrow’s breakthroughs.

Abstract: Computational social science leverages new data sources and computational methods to expand the “sociological imagination”, connecting individual milieus to the wider sociological conditions. Beyond extending the existing approaches, can new computational tools also help expanding the scope of our imagination? In this talk, I will talk about how simple representation learning techniques (esp. “word2vec”) can allow us to think about the text and network data in new ways. In particular, I will discuss how a subtle, less known bias in the word2vec model lets us do better ground the model.

First, this Friday’s seminar will occur at a slightly earlier time than normal: 11:45am-12:45pm. Please use the usual Zoom link.

Science is built upon scholarship consensus that changes over time. This raises the question of how revolutionary theories and assumptions are evaluated and accepted into the norm of science as the setting for the next scientific revolution. Yiling’s recent work analyzed millions of research articles published over four decades and revealed the scarcity (~2%) of highly novel work, the higher chance (25%) they disrupt existing research rather than developing it, and its long-shot nature (it takes ten years or longer to recognize a novel work, over which period only 20% scholars survived). Yiling’s work also provides one of the first computational models reformulating Uzzi Atypicality, a prominent novelty measure in the Science of Science, as the distance across the latent knowledge spaces learned by neural networks. The evolution of this knowledge space characterizes how yesterday’s novelty forms today’s scientific conventions, which condition the novelty–and surprise–of tomorrow’s breakthroughs. This paper is accepted to present at SciNLP, a community aiming to bring together researchers from diverse fields who are interested in building computational systems that extract, represent the knowledge in scientific texts, and/or provide humans better access to such knowledge.

Which colleges give their students relevant skills for the future of work? Which majors or fields of study have limited effectiveness as workforce development? Data on skills and workplace activities are essential for describing labor trends in the workforce, but data on the skills taught during workforce development—in higher education in particular—remain absent. Although studies of job postings and US Department of Labor ONET data describe both the supply and demand side of a polarized job market, few studies describe the specific skills taught to college students, who then enter the workforce as “high-skill” workers. This project will fill this gap using a novel data set of 10 million university course syllabi to empirically study the skills (e.g., ONET workplace activities) taught in courses over the last decade according to the Open Syllabus Project. This project will compare the empirical skills taught in university/college classrooms with labor data from the US Department of Labor and a data set of millions of worker resumes to assess the role of higher education in job polarization, wealth inequality, and to identify the educational foundations for adaptable workers.

We are hosting a cross-group student welcome picnic at xx Park. Some description here…

We launch the PITT Initiative on the Computational Social Science to connect to everyone who are interested in doing CSS research.