Our personal identity is composed of many dimensions, such as age, gender, ethnic background, or socioeconomic status. A research team led by Fariba Karimi from the Institute of Human-Centred Computing at Graz University of Technology (TU Graz) and Samuel Martin-Gutierrez from the Complexity Science Hub developed the statistical computational model “MAPS” to calculate the influence of these factors on our social relationships. The researchers have recently published a MAPS-based analysis of high school friendships and marriages in the US in the journal Communications Physics. The study shows that humans are extremely selective.

SUTD researchers used mobile phone GPS traces, street view imagery, and open-source spatial data to show that pedestrian route choices in a rapidly developing city are shaped far more by street conditions and context than by distance alone.

Large language models may be able to make moderation of social media and online communities more effective, but they are expensive to run at scale, especially when asked to provide explanations for each piece of content they flag. Yuan Zhao will present research on creating an interpretable and low-cost method for evaluating LLMs’ hate speech classification as part of 190th ASA Meeting. His framework relies on the Rational Inattention model, an economic idea developed to explain human behavior.

A study led by Qiujie “Angie” Zheng from the University of Maine found that consumers are willing to pay an average of $3.42 more for a lobster roll made with lobster harvested using ropeless fishing technology designed to reduce whale entanglement risks when presented with information on animal welfare. Researchers tested how information about whale conservation, animal welfare and Maine’s lobster industry shaped consumer willingness to pay more for lobster harvested using ropeless technology. Messaging focused on whale welfare and entanglement impacts proved most effective at increasing support for ropeless technology, with consumers willing to pay more.