Digital Commons Network^™

On The Test Accuracy And Effective Control Of The Covid-19 Pandemic: A Case Study In Singapore, Guang Cheng, Sarah Yini Gao, Yancheng Yuan, Chenxiao Zhang, Zhichao Zheng

Research Collection Lee Kong Chian School Of Business

This study examines the impact of coronavirus disease 2019 (COVID-19) test accuracy (i.e., sensitivity and specificity) on the progression of the pandemic under two scenarios of limited and unlimited test capacity. We extend the classic susceptible–exposed–infectious–recovered model to incorporate test accuracy and compare the progression of the pandemic under various sensitivities and specificities. We find that high-sensitivity tests effectively reduce the total number of infections only with sufficient testing capacity. Nevertheless, with limited test capacity and a relatively high cross-infection rate, the total number of infected cases may increase when sensitivity is above a certain threshold. Despite the potential for …

Nonignorable Missing Data, Single Index Propensity Score And Profile Synthetic Distribution Function, Xuerong Chen, Denis H. Y. Leung, Jing Qin

Research Collection School Of Economics

In missing data problems, missing not at random is difficult to handle since the response probability or propensity score is confounded with the outcome data model in the likelihood. Existing works often assume the propensity score is known up to a finite dimensional parameter. We relax this assumption and consider an unspecified single index model for the propensity score. A pseudo-likelihood based on the complete data is constructed by profiling out a synthetic distribution function that involves the unknown propensity score. The pseudo-likelihood gives asymptotically normal estimates. Simulations show the method compares favorably with existing methods.

Short Selling Etfs, Frank Weikai Li, Qifei Zhu

Research Collection Lee Kong Chian School Of Business

We provide novel evidence that arbitrageurs use exchange-traded funds (ETFs) as an avenue to circumvent short-sale constraints at the stock level. Using a large sample of U.S. equity ETF holdings, we document that shorting activity on ETFs rises with the difficulty of shorting underlying stocks. Stocks heavily shorted via their holding ETFs underperform those that are lightly shorted. The return predictability of ETF shorting is distinct from stock-level shorting measures and is concentrated among stocks that face severe arbitrage constraints. These findings suggest that ETFs allow arbitrageurs to target overpriced stocks that are otherwise difficult to short.

What Really Matters?: Characterising And Predicting User Engagement Of News Postings Using Multiple Platforms, Sentiments And Topics, Kholoud K. Aldous, Jisun An, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

This research characterises user engagement of approximately 3,000,000 news postings of 53 news outlets and 50,000,000 associated user comments during 8 months on 5 social media platforms (i.e. Facebook, Instagram, Twitter, YouTube, and Reddit). We investigate the effect of sentiments and topics on user engagement across four levels of user engagement expressions (i.e. views, likes, comments, cross-platform posting). We find that sentiments and topics differ by both news outlets and social media platforms, and both sentiments and topics by the four levels of user engagement expression. Finally, we predict a volume of four user engagement levels for given news content, …

Understanding In-App Advertising Issues Based On Large Scale App Review Analysis, Cuiyun Gao, Jichuan Zeng, David Lo, Xin Xia, Irwin King, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Context: In-app advertising closely relates to app revenue. Reckless ad integration could adversely impact app quality and user experience, leading to loss of income. It is very challenging to balance the ad revenue and user experience for app developers. Objective: Towards tackling the challenge, we conduct a study on analyzing user concerns about in-app advertisement. Method: Specifically, we present a large-scale analysis on ad-related user feedback. The large user feedback data from App Store and Google Play allow us to summarize ad-related app issues comprehensively and thus provide practical ad integration strategies for developers. We first define common ad issues …

Simultaneous Material Identification And Target Imaging With Commodity Rfid Devices, Ju Wang, Jie Xiong, Xiaojiang Chen, Hongbo Jiang, Rajesh Krishna Balan, Dingyi Fang

Research Collection School Of Computing and Information Systems

Material identification and target imaging play an important role in many applications. This paper introduces TagScan, a system that can identify the material type and image the horizontal cut of a target simultaneously with cheap commodity Radio-Frequency IDentification (RFID) devices. The key intuition is that different materials and/or target sizes cause different amounts of phase and RSS (Received Signal Strength) changes, when radio frequency (RF) signal penetrates through the target. Multiple challenges need to be addressed before we can turn the idea into a functional system, including (i) indoor environments exhibit rich multipath which breaks the linear relationship between the …

Modeling Functional Similarity In Source Code With Graph-Based Siamese Networks, Nikita Mehrotra, Navdha Agarwal, Piyush Gupta, Saket Anand, David Lo, Rahul Purandare

Research Collection School Of Computing and Information Systems

Code clones are duplicate code fragments that share (nearly) similar syntax or semantics. Code clone detection plays an important role in software maintenance, code refactoring, and reuse. A substantial amount of research has been conducted in the past to detect clones. A majority of these approaches use lexical and syntactic information to detect clones. However, only a few of them target semantic clones. Recently, motivated by the success of deep learning models in other fields, including natural language processing and computer vision, researchers have attempted to adopt deep learning techniques to detect code clones. These approaches use lexical information (tokens) …

Active Learning Of Discriminative Subgraph Patterns For Api Misuse Detection, Hong Jin Kang, David Lo

Research Collection School Of Computing and Information Systems

A common cause of bugs and vulnerabilities are the violations of usage constraints associated with Application Programming Interfaces (APIs). API misuses are common in software projects, and while there have been techniques proposed to detect such misuses, studies have shown that they fail to reliably detect misuses while reporting many false positives. One limitation of prior work is the inability to reliably identify correct patterns of usage. Many approaches confuse a usage pattern’s frequency for correctness. Due to the variety of alternative usage patterns that may be uncommon but correct, anomaly detection-based techniques have limited success in identifying misuses. We …

Emerging App Issue Identification Via Online Joint Sentiment-Topic Tracing, Cuiyun Gao, Jichuan Zeng, Zhiyuan Wen, David Lo, Xin Xia, Irwin King, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Millions of mobile apps are available in app stores, such as Apple’s App Store and Google Play. For a mobile app, it would be increasingly challenging to stand out from the enormous competitors and become prevalent among users. Good user experience and well-designed functionalities are the keys to a successful app. To achieve this, popular apps usually schedule their updates frequently. If we can capture the critical app issues faced by users in a timely and accurate manner, developers can make timely updates, and good user experience can be ensured. There exist prior studies on analyzing reviews for detecting emerging …

Post2vec: Learning Distributed Representations Of Stack Overflow Posts, Bowen Xu, Thong Hoang, Abhishek Sharma, Chengran Yang, Xin Xia, David Lo

Research Collection School Of Computing and Information Systems

Past studies have proposed solutions that analyze Stack Overflow content to help users find desired information or aid various downstream software engineering tasks. A common step performed by those solutions is to extract suitable representations of posts; typically, in the form of meaningful vectors. These vectors are then used for different tasks, for example, tag recommendation, relatedness prediction, post classification, and API recommendation. Intuitively, the quality of the vector representations of posts determines the effectiveness of the solutions in performing the respective tasks. In this work, to aid existing studies that analyze Stack Overflow posts, we propose a specialized deep …

Broken External Links On Stack Overflow, Jiakun Liu, Xin Xia, David Lo, Haoxiang Zhang, Ying Zou, Ahmed E. Hassan, Shanping Li

Research Collection School Of Computing and Information Systems

Stack Overflow hosts valuable programming-related knowledge with 11,926,354 links that reference to the third-party websites. The links that reference to the resources hosted outside the Stack Overflow websites extend the Stack Overflow knowledge base substantially. However, with the rapid development of programming-related knowledge, many resources hosted on the Internet are not available anymore. Based on our analysis of the Stack Overflow data that was released on Jun. 2, 2019, 14.2 percent of the links on Stack Overflow are broken links. The broken links on Stack Overflow can obstruct viewers from obtaining desired programming-related knowledge, and potentially damage the reputation of …

Field Study In Deploying Restless Multi-Armed Bandits: Assisting Non-Profits In Improving Maternal And Child Health, Aditya Mate, Lovish Madan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe

Research Collection School Of Computing and Information Systems

The widespread availability of cell phones has enabled non-profits to deliver critical health information to their beneficiaries in a timely manner. This paper describes our work to assist non-profits that employ automated messaging programs to deliver timely preventive care information to beneficiaries (new and expecting mothers) during pregnancy and after delivery. Unfortunately, a key challenge in such information delivery programs is that a significant fraction of beneficiaries drop out of the program. Yet, non-profits often have limited health-worker resources (time) to place crucial service calls for live interaction with beneficiaries to prevent such engagement drops. To assist non-profits in optimizing …

Automated Reverse Engineering Of Role-Based Access Control Policies Of Web Applications, Ha Thanh Le, Lwin Khin Shar, Domenico Bianculli, Lionel C. Briand, Cu Duy Nguyen

Research Collection School Of Computing and Information Systems

Access control (AC) is an important security mechanism used in software systems to restrict access to sensitive resources. Therefore, it is essential to validate the correctness of AC implementations with respect to policy specifications or intended access rights. However, in practice, AC policy specifications are often missing or poorly documented; in some cases, AC policies are hard-coded in business logic implementations. This leads to difficulties in validating the correctness of policy implementations and detecting AC defects.In this paper, we present a semi-automated framework for reverse-engineering of AC policies from Web applications. Our goal is to learn and recover role-based access …

Assessing The Psychosocial Dimensions Of Frailty Among Older Adults In Singapore: A Community-Based Cross-Sectional Study, Elliot Yeung Chong, Angela Hui-Shan Lim, Freda Cheng Yee Mah, Lyn Hui Wen Yeo, Shu Tian Ng, Huso Yi

Research Collection School of Social Sciences

Objective To examine how multiple dimensions of mental and social health, in addition to physical health, were associated with frailty among older adults. Design A door-to-door sampling household community-based survey. Setting Thirty-two public housing blocks within a residential town in Singapore's central region. Participants 497 residents aged 60 years or older from the public housing town. Outcome measures Physical frailty was assessed using the FRAIL Scale, which stands for fatigue, resistance, ambulation, illnesses and loss of weight. Physical health was assessed by multimorbidity, physical activity and functional ability; mental illness was assessed by the General Health Questionnaire (GHQ); and social …

A Mind-Wandering Account Of The Testing Effect: Does Context Variation Matter?, Sarah Shi Hui Wong, Stephen Wee Hun Lim

Research Collection School of Social Sciences

The learning benefits of retrieval practice have been linked to reduced mind-wandering, but the reasons why testing offers such an attentional advantage have scarcely been explored. Here, we investigate the extent that the inherent change in learning context during retrieval practice (i.e., interleaved study and retrieval) attenuates mind-wandering, relative to restudy (i.e., massed study). Learners (N = 120) either restudied video lectures (SSSS) or engaged in a combination of study and retrieval (SRSR). Further, they used either the same study mode – the video lecture (S) or its corresponding transcript (S′) only (i.e., SSSS or S′S′S′S′; SRSR or S′RS′R), or …

There Is A Time To Be Creative: The Alignment Between Chronotype And Time Of Day, Jana Kuehnel, Ronald Bledow, Markus Kiefer

Research Collection Lee Kong Chian School Of Business

We examine the influence of chronobiological processes on creativity, specifically the influence of a person’s chronotype. Chronotype refers to the setting of a person’s biological clock that gives rise to a distinctive pattern of sleep habits and preferred diurnal activity. We propose a synchrony effect and predict that people are creative when the external clock is aligned with their internal, biological clock. According to our model, positive mood and creative self-efficacy act as affective and cognitive mechanisms of this synchrony effect. We present three studies that test our theorizing: A quasi-experimental field study with 260 employees, a day-reconstruction study with …

Weighting Admission Scores To Balance Predictiveness-Diversity: The Pareto-Optimization Approach, Filip Lievens, Paul R. Sackett, Wilfried De Corte

Research Collection Lee Kong Chian School Of Business

Context: Although many medical schools seek to improve diversity, they grapple with the challenge of how to weight the scores of different admission methods to achieve a balance between obtaining high predictiveness and ensuring diversity in the selected student pool. Yet, in large-scale employment settings, substantial progress has been made on this front: Pareto-optimization has been introduced as an elegant statistical tool to assist decision makers in determining the weights assigned to selection methods in advance (before the selection has taken place) so that a selection system is designed to achieve an optimal balance as reflected by the trade-off that …

Investing In Low-Trust Countries: On The Role Of Social Trust In The Global Mutual Fund Industry, Massimo Massa, Chengwei Wang, Hong Zhang, Jian Zhang

Research Collection Lee Kong Chian School Of Business

We hypothesize that social trust, in mitigating contracting incompleteness, may have an important effect on the activeness and effectiveness of delegated portfolio management. Using a complete sample of worldwide open-end mutual funds, we find that trust is positively associated with the activeness of funds and that trust-related active share delivers superior performance (e.g., approximately 2% per year for cross-border investments). Moreover, "trust in the market" and "trust in managers" play important yet different roles for different types of cross-border delegated portfolio management. Our results suggest that trust acts as a fundamental building block for delegated portfolio management.

Modeling Sentiments And Preferences From Multimodal Data, Quoc Tuan Truong

Dissertations and Theses Collection (Open Access)

Online reviews are prevalent in many modern Web applications, such as e-commerce, crowd-sourced location and check-in platforms. Fueled by the rise of mobile phones that are often the only cameras on hand, reviews are increasingly multimodal, with photos in addition to textual content. In this thesis, we focus on modeling the subjectivity carried in this form of data, with two research objectives.

In the first part, we tackle the problem of detecting sentiment expressed by a review. This is a key unlocking many applications, e.g., analyzing opinions, monitoring consumer satisfaction, assessing product quality.
Traditionally, the task of sentiment analysis primarily …

Short-Term Impact Of Covid-19 On Consumption Spending And Its Underlying Mechanisms: Evidence From Singapore, Seonghoon Kim, Kanghyock Koh, Xuan Zhang

Research Collection School Of Economics

We examine the short-term impact of COVID-19 on consumption spending and labor market outcomes. Using monthly panel data of individuals mainly aged 50–70 in Singapore, we find that COVID-19 reduced consumption spending and labor market outcomes immediately after its outbreak, and its negative impact quickly evolved. At its peak, the pandemic reduced total household consumption spending by 22.8% and labor income by 5.9% in April. Probability of full-time work also went down by 1.2 pp and 6.0 pp in April and May, respectively, but employment and self-employment were only mildly affected. Our heterogeneity analysis indicates that the reduction in consumption …

A Panel Clustering Approach To Analyzing Bubble Behavior, Yanbo Liu, Peter C. B. Phillips, Jun Yu

Research Collection School Of Economics

This study provides new mechanisms for identifying and estimating explosive bubbles in mixed-root panel autoregressions with a latent group structure. A post-clustering approach is employed that combines a recursive k-means clustering al-gorithm with panel-data test statistics for testing the presence of explosive roots in time series trajectories. Uniform consistency of the k-means clustering algorithm is established, showing that the post-clustering estimate is asymptotically equivalent to the oracle counterpart that uses the true group identities. Based on the estimated group membership, right-tailed self-normalized t-tests and coefficient-based J-tests, each with pivotal limit distributions, are introduced to detect the explosive roots. The usual …

Risk Price Variation: The Missing Half Of Empirical Asset Pricing, Andrew John Patton, Brian M. Weller

Research Collection School Of Economics

Equal compensation across assets for the same risk exposures is a bedrock of asset pricing theory and empirics. Yet real-world frictions can violate this equality and create apparently high Sharpe ratio opportunities. We develop new methods for asset pricing with cross-sectional heterogeneity in compensation for risk. We extend k-means clustering to group assets by risk prices and introduce a formal test for whether differences in risk premiums across market segments are too large to occur by chance. We find significant evidence of cross-sectional variation in risk prices for almost all combinations of test assets, factor models, and time periods considered.

Modeling Factors Contributing To Dockless E-Scooter Injury Accidents In Austin, Texas, Amin Azimian, Junfeng Jiao

Research Collection College of Integrative Studies

Objective: Over the past few years, increased e-scooter ridership has raised concerns about the growing number of injury accidents involving e-scooters. Additionally, given the lack of appropriate e-scooter accident data, the extent to which built environment and socioeconomic factors affect e-scooter safety is unclear. In consideration of these issues, this study was aimed at identifying the factors contributing to the number of e-scooter injury accidents in Austin. Methods: We developed zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models on the basis of 2018 dockless e-scooter injury accident data collected from the Patch platform. The results indicated that the ZIP …

Taxation Of Automation And Artificial Intelligence As A Tool Of Labour Policy, Vincent Ooi, Glendon Goh

Research Collection Yong Pung How School Of Law

Rapid developments in automation technology pose a risk of mass displacement of human labour, resulting in the need to support and retrain displaced workers (a negative externality). We propose an “automation tax” that would slow the adoption of automation technology in appropriate circumstances, giving workers and social support systems time to adapt. This could be easily implemented through changes to the existing schedular system of depreciation/ capital allowances, reducing the uncertainty of its application and implementation costs. Such a system would be flexible enough to keep up with rapid technological developments. Two main dimensions may be adjusted to produce intended …

Crowdtc: Crowd-Powered Learning For Text Classification, Keyu Yang, Yunjun Gao, Lei Liang, Song Bian, Lu Chen, Baihua Zheng

Research Collection School Of Computing and Information Systems

Text classification is a fundamental task in content analysis. Nowadays, deep learning has demonstrated promising performance in text classification compared with shallow models. However, almost all the existing models do not take advantage of the wisdom of human beings to help text classification. Human beings are more intelligent and capable than machine learning models in terms of understanding and capturing the implicit semantic information from text. In this article, we try to take guidance from human beings to classify text. We propose Crowd-powered learning for Text Classification (CrowdTC for short). We design and post the questions on a crowdsourcing platform …

Including Everyone, Everywhere: Understanding Opportunities And Challenges Of Geographic Gender-Inclusion In Oss, Gede Artha Azriadi Prana, Denae Ford, Ayushi Rastogi, David Lo, Rahul Purandare, Nachiappan Nagappan

Research Collection School Of Computing and Information Systems

The gender gap is a significant concern facing the software industry as the development becomes more geographically distributed. Widely shared reports indicate that gender differences may be specific to each region. However, how complete can these reports be with little to no research reflective of the Open Source Software (OSS) process and communities software is now commonly developed in? Our study presents a multi-region geographical analysis of gender inclusion on GitHub. This mixed-methods approach includes quantitatively investigating differences in gender inclusion in projects across geographic regions and investigate these trends over time using data from contributions to 21,456 project repositories. …

Defectchecker: Automated Smart Contract Defect Detection By Analyzing Evm Bytecode, Jiachi Chen, Xin Xia, David Lo, John Grundy, Xiapu Luo, Ting Chen

Research Collection School Of Computing and Information Systems

Smart contracts are Turing-complete programs running on the blockchain. They are immutable and cannot be modified, even when bugs are detected. Therefore, ensuring smart contracts are bug-free and well-designed before deploying them to the blockchain is extremely important. A contract defect is an error, flaw or fault in a smart contract that causes it to produce an incorrect or unexpected result, or to behave in unintended ways. Detecting and removing contract defects can avoid potential bugs and make programs more robust. Our previous work defined 20 contract defects for smart contracts and divided them into five impact levels. According to …

Why, How, And When Divergent Perceptions Become Dysfunctional In Organizations: A Motivated Cognition Perspective, Zhanna Lyubykh, Laurie J. Barclay, Marion Fortin, Michael R. Bashshur, Malika Khakhar

Research Collection Lee Kong Chian School Of Business

Decades of research has demonstrated that people can arrive at starkly different perceptions in the same social situations. Divergent perceptions are not inherently dysfunctional. However, if divergent perceptions are not managed effectively, they can have deleterious effects that can undermine functioning in the workplace. Drawing on a motivated cognition perspective, we outline why divergent perceptions may emerge as well as overview the benefits and drawbacks of divergent perceptions in organizational contexts. Next, we highlight the complexities associated with divergent perceptions in the workplace, including why, how, and when divergent perceptions may become dysfunctional. We also showcase theoretical insights from a …

Decentralizing Money: Bitcoin Prices And Blockchain Security, Emiliano S. Pagnotta

Research Collection Lee Kong Chian School Of Business

We address the determination of bitcoin prices and decentralized security. Users forecast the transactional and resale values of holdings, pricing the risk of systemic attacks. Miners contribute resources to protect against attackers and compete for block rewards. Bitcoin's design leads to multiple equilibria: the same blockchain technology is consistent with sharply different price and security levels. Bitcoin's monetary policy can lead to welfare losses and deviations from quantity theory. Price-security feedback amplifies fundamental shocks' volatility impact and leads to boom and busts unconnected to fundamentals. We characterize how viability versus fiat currency depends on bitcoin's relative acceptability and inflation protection.

Spacs: Is It For Real Estate?, Melvyn Teo, Ronald Tan, Indran Thana, Yin Mei Lock

Perspectives@SMU

SPACs are gaining popularity but investors should do their homework