Jian GaoThe University of Hong Kong | HKU · Faculty of Social Sciences
Jian Gao
Doctor of Engineering
About
50
Publications
17,808
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Introduction
Dr. Jian Gao is an Assistant Professor at the Faculty of Social Sciences, The University of Hong Kong. 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.
Additional affiliations
September 2021 - July 2024
September 2019 - August 2021
September 2016 - September 2017
Publications
Publications (50)
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...
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...
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...
Understanding how student peers influence learning outcomes is crucial for effective education management in complex social systems. The complexities of peer selection and evolving peer relationships, however, pose challenges for identifying peer effects using static observational data. Here we use both null-model and regression approaches to exami...
The rapid advancement of artificial intelligence (AI) is poised to reshape almost every line of work. Despite enormous efforts devoted to understanding AI’s economic impacts, we lack a systematic understanding of the benefits to scientific research associated with the use of AI. Here we develop a measurement framework to estimate the direct use of...
The ongoing artificial intelligence (AI) revolution has the potential to change almost every line of work. As AI capabilities continue to improve in accuracy, robustness, and reach, AI may outperform and even replace human experts across many valuable tasks. Despite enormous efforts devoted to understanding AI's impact on labor and the economy and...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
Industrial development is the process by which economies learn how to produce new products and services. But how do economies learn? And who do they learn from? The literature on economic geography and economic development has emphasized two learning channels: inter-industry learning, which involves learning from related industries; and inter-regio...
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...
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,...
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...
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...
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...
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...
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 $\alpha_{c}=-1$...
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...