Article
Communication
Mikhaila N. Calice, Luye Bao, Isabelle Freiling, Emily Howell, Michael A. Xenos, Shiyu Yang, Dominique Brossard, Todd P. Newman, Dietram A. Scheufele
Summary: The use of AI algorithms by social media platforms for curating news content has disrupted the traditional gatekeeping role of traditional news outlets. This has led to debates among US policymakers regarding platform bias and has gained traction among some voters. A survey experiment reveals that partisan cues effectively shape attitudes towards algorithmic news bias, but their effects are asymmetrical.
NEW MEDIA & SOCIETY
(2023)
Article
Biotechnology & Applied Microbiology
Miljana Tanic, Ismail Moghul, Simon Rodney, Pawan Dhami, Heli Vaikkinen, John Ambrose, James Barrett, Andrew Feber, Stephan Beck
Summary: Targeted bisulfite sequencing (TBS) is a cost-effective method for analyzing the human methylome. In this study, five commercially available TBS platforms were compared. The results showed that although all platforms produced robust and reproducible data, there were major differences in the CpG sites covered. However, these differences can be overcome using imputation. The study provides guidance on choosing TBS platforms and offers a harmonization solution for comparative analysis.
NATURE BIOTECHNOLOGY
(2022)
Review
Communication
Laura Slechten, Cedric Courtois, Lennert Coenen, Bieke Zaman
Summary: Experimental research on selective exposure on online platforms often focuses on specific parts of the information selection process, rather than the entire user-platform interaction sequence. This study, however, explores the entire process of online search, demonstrating how users and platforms influence each other in narrowing down available information. The results suggest that users can still tailor their information exposure to maintain their beliefs, despite the structural impact of varying search result rankings, highlighting the need for further expansion in online selective exposure research both conceptually and methodologically.
COMMUNICATION RESEARCH
(2022)
Article
Computer Science, Hardware & Architecture
Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton
Summary: Social platforms have broad discretion and powerful algorithms to curate user content, while absolving themselves of almost all liability associated with that content.
COMMUNICATIONS OF THE ACM
(2021)
Article
Multidisciplinary Sciences
Eunsik Bang, Sujin Oh, Uijin Ju, Ho Eun Chang, Jin-Sil Hong, Hyeong-Jin Baek, Keun-Suh Kim, Hyo-Jung Lee, Kyoung Un Park
Summary: The exploration of oral microbiome has increased due to its association with systemic diseases, but there is a lack of standardization in saliva sampling for microbiome analysis, leading to incomparable data. This study evaluated factors influencing microbiome data by comparing saliva samples collected through two methods (passive drooling and mouthwash) and preserved using three methods (OMNIgene, DNA/RNA shield, and simple collection). The alpha diversity of the mouthwash samples was significantly higher than the drooling group, while there were no significant differences between the saliva-preservation methods. The study suggests that mouthwash and simple collection are comparable to other sample collection and preservation methods, offering convenience and cost-effectiveness for saliva sample preparation.
SCIENTIFIC REPORTS
(2023)
Article
Engineering, Civil
Merkouris Karaliopoulos, Orestis Mastakas, Wei Koong Chai
Summary: Our work focuses on online parking reservation platforms that have been proposed in the past decade to address the parking challenges in cities worldwide. These platforms aim to facilitate transactions between parking space providers and drivers by enlisting parking resources from commercial operators and individuals, allowing drivers to make online reservations through mobile apps. We formulate optimization problems for maximizing the platform's revenue by differentiating between fixed per transaction and proportional commissions. We design a novel algorithm that combines greedy and dynamic programming principles to solve these NP-hard problems efficiently. Through experiments and analysis of real parking data, we demonstrate the algorithm's effectiveness in optimizing parking resource reservation, achieving gains of up to 35% compared to existing policies.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Psychiatry
Timothy I. Michaels, Elsa Thomas, Joseph M. Flaxer, Sonali Singal, Lauren Hanna, Anna Van Meter, Sunny X. Tang, John M. Kane, Ema Saito
Summary: This study found racial inequities in the assignment of psychiatric inpatients of color to different buildings and units in a hospital system in the tristate area of the United States. Black, Hispanic/Latinx, and Asian patients were less likely to be assigned to better resourced units in the new building, indicating the presence of racial disparities. The findings emphasize the need for hospital systems to address the impact of structural racism on clinical care.
PSYCHIATRY RESEARCH
(2023)
Article
Business
Xin Hu, Liuyi He, Junjun Liu
Summary: This study investigates the impact of customer status in hierarchical loyalty programs on the valence of online reviews. The results show that a customer's need for status leads to a negative rating bias, while the need for social conformity can alleviate such bias.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2022)
Article
Surgery
Thuy B. Tran, Mustafa Raoof, Laleh Melstrom, Namgyal Kyulo, Zameer Shaikh, Veronica C. Jones, Loretta Erhunmwunsee, Yuman Fong, Susanne G. Warner
Summary: The study found that patient and surgeon race and sex affect patient satisfaction with physician communication and care. Minority and Spanish-speaking patients were more likely to report negative experiences. Female surgeons received higher ratings for overall communication, while Asian surgeons received lower scores.
Article
Neurosciences
Ruth Mueller, Anja Kathrin Ruess, Franziska Britta Schoeweitz, Alena Buyx, Cristina Gil Avila, Markus Ploner
Summary: Neuroscience research is influenced by significant racial bias and addressing this bias presents major challenges. The authors propose a global discussion involving researchers from various disciplines and individuals with lived experience to develop solutions and best practices for promoting racial and ethnic equity in neuroscience research and beyond.
NATURE NEUROSCIENCE
(2023)
Article
Medicine, General & Internal
Dowin Boatright, Nientara Anderson, Jung G. Kim, Eric S. Holmboe, William A. McDade, Tonya Fancher, Cary P. Gross, Sarwat Chaudhry, Mytien Nguyen, Max Jordan Nguemeni Tiako, Eve Colson, Yunshan Xu, Fangyong Li, James D. Dziura, Somnath Saha
Summary: This study examines the association between race and ethnicity and performance assessments among internal medicine residents. The results show that underrepresented in medicine and Asian residents received lower ratings on performance assessments compared to White residents during the first and second years of training, indicating the presence of racial bias in assessment.
Article
Management
Musa Eren Celdir, Soo-Haeng Cho, Elina H. Hwang
Summary: This paper examines the popularity bias in online dating platform recommendations and its impact on users' likelihood of finding dating partners. The study finds that while there may be bias against unpopular users, recommendations that maximize platform revenue and successful matches are not necessarily contradictory. Popular users can help the platform generate more revenue and successful matches as long as they do not become inaccessible.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2023)
Article
Mathematics
Juan M. Cebrian, Baldomero Imbernon, Jesus Soto, Jose M. Cecilia
Summary: Clustering algorithms are widely used kernels for generating knowledge from large datasets by grouping data elements into clusters to identify patterns or common features. Fuzzy clustering algorithms, while computationally expensive, show different performance depending on platforms due to the high computational cost and the variation in algorithmic patterns.
Article
Management
Ali Aouad, Daniela Saban
Summary: Motivated by online labor markets, this paper focuses on the online assortment optimization problem faced by a two-sided matching platform. The study investigates how platforms should design online assortment algorithms to maximize the expected number of matches in such settings. The results show that a simple greedy algorithm is 1/2-competitive against an optimal clairvoyant algorithm. However, no randomized algorithm can achieve a better competitive ratio, even in asymptotic regimes. The study further explores structured settings and develops new preference-aware balancing algorithms to improve the competitive ratios. The findings highlight the importance of suppliers' choices in designing online assortment algorithms for two-sided matching platforms.
MANAGEMENT SCIENCE
(2023)
Article
Political Science
Olga A. Avdeyeva, Richard E. Matland
Summary: The study found that the structure of the regional economy and labor market integration play different roles in reducing gender-trait stereotypes and ethnic biases, which is important for policy makers. It also highlights that social biases stem from complex structural phenomena and require transformative political and economic changes.
