Jian Gao

Jian Gao
Northwestern University | NU · Kellogg School of Management

Doctor of Engineering

About

47
Publications
12,099
Reads
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693
Citations
Introduction
Dr. Jian Gao is currently a Research Assistant Professor at the Center for Science of Science & Innovation, Kellogg School of Management, Northwestern University. He is working in the interdisciplinary field named Computational Socioeconomics. Currently, he is interested in studying research topics in the fields of Science of Science, Computational Social Science, Network Science, and Economic Geography. Personal page: https://jianxgao.com
Featured research
Article
Full-text available
Two surveys of principal investigators conducted between April 2020 and January 2021 reveal that while the COVID-19 pandemic’s initial impacts on scientists’ research time seem alleviated, there has been a decline in the rate of initiating new projects. This dimension of impact disproportionately affects female scientists and those with young children and appears to be homogeneous across fields. These findings may have implications for understanding the long-term effects of the pandemic on scientific research.
Article
Full-text available
Quantitative understanding of relationships between students' behavioral patterns and academic performance is a significant step towards personalized education. In contrast to previous studies that mainly based on questionnaire surveys, in this paper, we collect behavioral records from 18,960 undergraduate students' smart cards and propose a novel metric, called \emph{orderness}, which measures the regularity of campus daily life (e.g., meals and showers) of each student. Empirical analysis demonstrates that academic performance (GPA) is strongly correlated with orderness. Further more, we show that orderness is an important feature to predict academic performance, which remarkably improves the prediction accuracy even at the presence of students' diligence. Based on these analyses, education administrators could better guide students' campus lives and implement effective interventions at early stage when necessary.
Article
Industrial diversification depends on spillovers from related industries and nearby regions, yet their interaction remains largely unclear. We study economic diversification in China during the period 1990-2015 and present supportive evidence on both spillover channels. We add to the literature by showing that these two channels behave as substitutes when explaining new entries and exits, and by using acceleration campaigns of high-speed rail to address some endogeneity concerns with regional spillovers. Our findings confirm the role of relatedness and geographical distance in the diffusion of economic capabilities and support the idea that improvements in transportation can facilitate the diffusion of productive capabilities. KEYWORDS economic development; industrial structure; economic complexity; spillovers; high-speed rail JEL O11, O47, O53, R11 HISTORY
Article
Disconnects between science and policy, in which important scientific insights may be missed by policymakers and bad scientific advice may infect decision-making, are a long-standing concern. Yet, our systematic understanding of the use of science in policy remains limited, partly because of the difficulty in reliably tracing the coevolution of policy and science at a large, global scale. Today, the world faces a common emergency in the COVID-19 pandemic, which presents a dynamic, uncertain, yet extraordinarily consequential policy environment across the globe. We combined two large-scale databases that capture policy and science and their interactions, allowing us to examine the coevolution of policy and science during the pandemic. Our analysis suggests that many policy documents in the COVID-19 pandemic substantially access recent, peer-reviewed, and high-impact science. And policy documents that cite science are especially highly cited within the policy domain. At the same time, there is a heterogeneity in the use of science across policy-making institutions. The tendency for policy documents to cite science appears mostly concentrated within intergovernmental organizations (IGOs), such as the World Health Organization (WHO), and much less so in national governments, which consume science largely indirectly through the IGOs. This close coevolution between policy and science offers a useful indication that a key link is operating, but it has not been a sufficient condition for effectiveness in containing the pandemic.
Article
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we will make a brief manifesto about a new interdisciplinary research field named Computational Socioeconomics, followed by detailed introduction about data resources, computational tools, data-driven methods, theoretical models and novel applications at multiple resolutions, including the quantification of global economic inequality and complexity, the map of regional industrial structure and urban perception, the estimation of individual socioeconomic status and demographic, and the real-time monitoring of emergent events. This review, together with pioneering works we have highlighted, will draw increasing interdisciplinary attentions and induce a methodological shift in future socioeconomic studies.
Additional affiliations
September 2021 - present
Northwestern University
Position
  • Professor (Assistant)
September 2019 - August 2021
Northwestern University
Position
  • PostDoc Position
September 2016 - September 2017
Massachusetts Institute of Technology
Position
  • Research Assistant

Publications

Publications (42)
Article
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we wi...
Article
Disconnects between science and policy, in which important scientific insights may be missed by policymakers and bad scientific advice may infect decision-making, are a long-standing concern. Yet, our systematic understanding of the use of science in policy remains limited, partly because of the difficulty in reliably tracing the coevolution of pol...
Article
Industrial diversification depends on spillovers from related industries and nearby regions, yet their interaction remains largely unclear. We study economic diversification in China during the period 1990-2015 and present supportive evidence on both spillover channels. We add to the literature by showing that these two channels behave as substitut...
Article
Full-text available
Two surveys of principal investigators conducted between April 2020 and January 2021 reveal that while the COVID-19 pandemic’s initial impacts on scientists’ research time seem alleviated, there has been a decline in the rate of initiating new projects. This dimension of impact disproportionately affects female scientists and those with young child...
Article
Full-text available
Quantitative understanding of relationships between students' behavioral patterns and academic performance is a significant step towards personalized education. In contrast to previous studies that mainly based on questionnaire surveys, in this paper, we collect behavioral records from 18,960 undergraduate students' smart cards and propose a novel...
Preprint
Full-text available
The great expansion of high-speed rail (HSR) in China facilitates communications and interactions among people across cities. Despite extensive literature documenting the effects of HSR on a variety of variables such as local economic development, research collaboration, tourism, and capital mobility, not much is known about how HSR affects the flo...
Article
Collective cooperation is essential to human society, and it exists in many social dilemmas. In the scenario of a collective-risk social dilemma, a group of players have to collectively contribute to a public fund to prevent the tragedy of the commons, such as dangerous climate change, because everybody will lose all their remaining money when the...
Conference Paper
Prior research on work experience diversity yields inconsistent findings regarding its effects on employment outcomes: some conclude that experience diversity discounts (e.g., Ferguson & Hasan, 2013; Zuckerman, Kim, Ukanwa, & Rittmann, 2003), whereas some highlight its benefits (e.g., Lazear, 2004; Custodio, Ferreira, & Matos, 2013). Using resume d...
Preprint
Full-text available
Extensive research has documented the immediate impacts of the COVID-19 pandemic on scientists, yet it remains unclear if and how such impacts have shifted over time. Here we compare results from two surveys of principal investigators, conducted between April 2020 and January 2021, along with analyses of large-scale publication data. We find that t...
Article
Both academia and government have shown an increasingly common interest in the relationship between the high-speed railway and socioeconomic development. This paper provides a systematic review of the recent theoretical and empirical literature on the impact of the high-speed railway on economic development. On the one hand, we summarize theoretica...
Preprint
Full-text available
Public policy must confront emergencies that evolve in real time and in uncertain directions, yet little is known about the nature of policy response. Here we take the coronavirus pandemic as a global and extraordinarily consequential case, and study the global policy response by analyzing a novel dataset recording policy documents published by gov...
Article
Full-text available
During the last two decades, two important contributions have reshaped our understanding of international trade. First, countries trade more with those with whom they share history, language, and culture, suggesting that trade is limited by information frictions. Second, countries are more likely to start exporting products that are related to thei...
Chapter
Full-text available
The improvements in data acquisition and processing capabilities, as well as artificial intelligence and statistical mechanics, have rapidly and significantly changed the methodology of social and economic research. The recent paradigm shifting of social science driven by big data and artificial intelligence provides promising and novel data-driven...
Chapter
Different from the western education system, Chinese teachers and parents strongly encourage students to have a regular lifestyle. However, due to the lack of large-scale behavioral data, the relation between living patterns and academic performance remains poorly understood. In this chapter, we analyze large-scale behavioral records of 18,960 stud...
Thesis
Full-text available
Socio-economic systems are an important branch of complex systems, which involves the complex interactions between people's economic activities and the social environment in which they live. With the constant change of cognition and behavior, people's subjective decision-making process greatly affects the operation of socio-economic systems. To acc...
Preprint
Full-text available
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development. The understanding of socioeconomic processes provides foundations to quantify global economic development, to map regional industrial structure, and to infer individual socioeconomic status. In this review, we wi...
Article
Full-text available
Novel data has been leveraged to estimate the socioeconomic status in a timely manner, however, direct comparison on the use of social relations and talent movements remains rare. In this letter, we estimate the regional economic status based on the structural features of two networks. One is the online information flow network built on the followi...
Article
Full-text available
The enrichment of data resources and the innovation of analytic methods are gradually facilitating the transformation of socioeconomics into a data-driven and quantitative discipline. As a part of quantitative human resources, the investigation of salary has a significant role on social and economic development. However, previous studies are mainly...
Preprint
Novel data has been leveraged to estimate socioeconomic status in a timely manner, however, direct comparison on the use of social relations and talent movements remains rare. In this letter, we estimate the regional economic status based on the structural features of the two networks. One is the online information flow network built on the followi...
Article
Full-text available
Accurate perception of socioeconomic status and timely identification of emergencies are critical to smart social governance, however, traditional public sector data and statistical analysis methods cannot meet the accuracy and real-time requirements. Recently, large-scale data accumulated by the private sector, with many advantages including low a...
Article
Full-text available
Height premium has been revealed by extensive literature, however, evidence from China based on large-scale data remains still lacking. In this paper, we study how height conditions salary expectations by exploring a dataset covering over 140,000 Chinese job seekers. By using graphical and regression models, we find evidence in support of height pr...
Article
Full-text available
A variety of rating-based recommendation methods have been extensively studied including the well-known collaborative filtering approaches and some network diffusion-based methods, however, social trust relations are not sufficiently considered when making recommendations. In this paper, we contribute to the literature by proposing a trust-based re...
Conference Paper
Full-text available
Collective learning in economic development has been revealed by recent empirical studies, however, investigations on how to benefit most from its effects remain still lacking. In this paper, we explore the maximization of the collective learning effects using a simple propagation model to study the diversification of industries on real networks bu...
Conference Paper
Full-text available
Link prediction aims at revealing missing and unknown information from observed network data, or predicting possible evolutions in near future. In recent years, extensive studies of link prediction algorithms have been performed on unweighted networks. However most empirical systems are necessarily to be described as weighted networks rather than s...
Article
Full-text available
China has experienced an outstanding economic expansion during the past decades, however, literature on non-monetary metrics that reveal the status of China's regional economic development are still lacking. In this paper, we fill this gap by quantifying the economic complexity of China's provinces through analyzing 25 years' firm data. First, we e...
Article
During the last decades two important contributions have reshaped our understanding of international trade. First, countries trade more with those with whom they share history, language, and culture, suggesting that trade is limited by information frictions. Second, countries are more likely to start exporting products that are similar to their cur...
Article
Full-text available
In the wake of large-scale retraction scandals, we urge scientific publishers to be more proactive in stamping out fake peer-reviewing practices. They should work with editors, authors and research institutes to implement an effective system of precautions and penalties. Fraudulent peer review can arise when editors rely on authors' recommended r...
Article
Full-text available
Recommender systems benefit us in tackling the problem of information overload by predicting our potential choices among diverse niche objects. So far, a variety of personalized recommendation algorithms have been proposed and most of them are based on similarities, such as collaborative filtering and mass diffusion. Here, we propose a novel vertex...
Article
Full-text available
With the advent of the era of big data, both the quantity and quality of economic activity related data have been enormously enriched and improved. By analyzing these large-scale data from socio-economic systems, we have the opportunity to quantify the status of economic development instantaneously and accurately with nearly no cost. In this paper,...
Article
Full-text available
With the help of information and communication technologies, studies on the overall social networks have been extensively reported recently. However, investigations on the directed Ego Communication Networks (ECNs) remain insufficient, where an ECN stands for a sub network composed of a centralized individual and his/her direct contacts. In this pa...
Article
Full-text available
Reputation is a valuable asset in online social lives and it has drawn increased attention. How to evaluate user reputation in online rating systems is especially significant due to the existence of spamming attacks. To address this issue, so far, a variety of methods have been proposed, including network-based methods, quality-based methods and gr...
Article
Full-text available
Enterprises have put more and more emphasis on data analysis so as to obtain effective management advices. Managers and researchers are trying to dig out the major factors that lead to employees' promotion and resignation. Most previous analyses were based on questionnaire survey, which usually consists of a small fraction of samples and contains b...
Article
Full-text available
Ranking problem has attracted much attention in real systems. How to design a robust ranking method is especially significant for online rating systems under the threat of spamming attacks. By building reputation systems for users, many well-performed ranking methods have been applied to address this issue. In this Letter, we propose a group-based...
Article
Full-text available
We numerically study bootstrap percolation on Kleinberg's spatial networks, in which the probability density function of a node to have a long-range link at distance $r$ scales as $P(r)\sim r^{\alpha}$. Setting the ratio of the size of the giant active component to the network size as the order parameter, we find a critical exponent $\alpha_{c}=-1$...
Article
Full-text available
We employ a bipartite network to describe an online commercial system. Instead of investigating accuracy and diversity in each recommendation, we focus on studying the influence of recommendation on the evolution of the online bipartite network. The analysis is based on two benchmark datasets and several well-known recommendation algorithms. The st...

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