TY - JOUR T1 - Combating False Information by Sharing the Truth: A Study on the Spread of Fact-checks on Social Media JF - Information Systems Frontiers Y1 - 2022 A1 - Li,Jiexun A1 - Chang,Xiaohui KW - Business Analytics AB - Misinformation on social media has become a horrendous problem in our society. Fact-checks on information often fall behind the diffusion of misinformation, which can lead to negative impacts on society. This research studies how different factors may affect the spread of fact-checks over the internet. We collected a dataset of fact-checks in a six-month period and analyzed how they spread on Twitter. The spread of fact-checks is measured by the total retweet count. The factors/variables include the truthfulness rating, topic of information, source credibility, etc. The research identifies truthfulness rating as a significant factor: conclusive fact-checks (either true or false) tend to be shared more than others. In addition, the source credibility, political leaning, and the sharing count also affect the spread of fact-checks. The findings of this research provide practical insights into accelerating the spread of the truth in the battle against misinformation online. U2 - a U4 - 219699023872 ID - 219699023872 ER - TY - JOUR T1 - Combating Misinformation by Sharing the Truth: a Study on the Spread of Fact-Checks on Social Media JF - Information Systems Frontiers Y1 - 2022 A1 - Li,Jiexun A1 - Chang,Xiaohui KW - Business Analytics AB - Misinformation on social media has become a horrendous problem in our society. Fact-checks on information often fall behind the diffusion of misinformation, which can lead to negative impacts on society. This research studies how different factors may affect the spread of fact-checks over the internet. We collected a dataset of fact-checks in a six-month period and analyzed how they spread on Twitter. The spread of fact-checks is measured by the total retweet count. The factors/variables include the truthfulness rating, topic of information, source credibility, etc. The research identifies truthfulness rating as a significant factor: conclusive fact-checks (either true or false) tend to be shared more than others. In addition, the source credibility, political leaning, and the sharing count also affect the spread of fact-checks. The findings of this research provide practical insights into accelerating the spread of the truth in the battle against misinformation online. U2 - a U4 - 219699023872 ID - 219699023872 ER - TY - HEAR T1 - Impact of Team Size on Technological Contributions: Unpacking Disruption and Development Y1 - 2020 A1 - Chen,Jiyao A1 - Shao,Rong A1 - Fan,Shaokun A1 - Li,Jiexun KW - BIS KW - Business Analytics KW - Finance KW - Strategy & Entrepreneurship JA - AOM Annual Meeting CY - Vancouver CA U2 - c U4 - 202782855168 ID - 202782855168 ER - TY - JOUR T1 - Improving Mobile Health Apps Usage: A Quantitative Study on mPower Data of Parkinson's Disease JF - Information Technology and People Y1 - 2020 A1 - Li,Jiexun A1 - Chang,Xiaohui KW - Business Analytics AB - Purpose
The emergence of mobile health (mHealth) products has created a capability of monitoring and managing the health of patients with chronic diseases. These mHealth technologies would not be beneficial unless they are adopted and used by their target users. This study identifies key factors affecting the usage of mHealth apps based on user usage data collected from an mHealth app.

Design/methodology/approach
Using a data set collected from an mHealth app named mPower, developed for patients with Parkinson’s disease (PD), this paper investigated the effects of disease diagnosis, disease progression, and mHealth app difficulty level on app usage, while controlling for user information. App usage is measured by five different activity counts of the app.

Findings
The results across five measures of mHealth app usage vary slightly. On average, previous professional diagnosis and high user performance scores encourage user participation and engagement, while disease progression hinders app usage.

Research limitations/implications
The findings potentially provide insights into better design and promotion of mHealth products and improve the capability of health management of patients with chronic diseases.

Originality/value
Studies on the mHealth app usage are critical but sparse because large-scale and reliable mHealth app usage data are limited. Unlike earlier works based solely on survey data, this research used a large user usage data collected from an mHealth app to study key factors affecting app usage. The methods presented in this study can serve as a pioneering work for the design and promotion of mHealth technologies. VL - 34 CP - 1 U2 - a U4 - 176734351360 ID - 176734351360 ER - TY - JOUR T1 - Business Performance Prediction in Location-based Social Commerce JF - Expert Systems with Applications Y1 - 2019 A1 - Chang,Xiaohui A1 - Li,Jiexun KW - Business Analytics AB - Social commerce and location-based services provide a data platform for coexisting and competing businesses in geographical neighborhoods. Our research is aimed at mining data from such platforms to gain valuable insights for better support to strategic and operational business decisions. We develop a computational framework for predicting business performance that takes into account both intrinsic (e.g., attributes) and extrinsic (e.g., competitions) factors. Our experiments on synthetic and real datasets demonstrated superiority of a hybrid prediction model that adopts both link-based and context-based assumptions. VL - 126 U2 - a U4 - 141504974848 ID - 141504974848 ER - TY - JOUR T1 - Making Sense of Organization Dynamics Using Text Analysis. JF - Expert Systems with Applications Y1 - 2018 A1 - Li,Jiexun A1 - Wu,Zhaohui A1 - Zhu,Bin A1 - Xu,Kaiquan KW - BIS KW - Business Analytics KW - Supply Chain U2 - a U4 - 152771403776 ID - 152771403776 ER - TY - HEAR T1 - Mining Hidden Organizational Structures from Meeting Records Y1 - 2015 A1 - Li,Jiexun A1 - Wu,Zhaohui A1 - Zhu,Bin KW - BIS KW - Business Analytics KW - Supply Chain JA - INFORMS 2015 CY - Philadelphia U2 - c U4 - 125884504064 ID - 125884504064 ER - TY - HEAR T1 - Collective opinion classification: A global consistency maximization approach Y1 - 2014 A1 - Li,Jiexun A1 - Li,Xin A1 - Zhu,Bin KW - BIS KW - Business Analytics JA - The 24th Workshop on Information Technology and Systems (WITS) CY - Aukland, New Zealand U2 - c U4 - 98584274944 ID - 98584274944 ER -