Neighbourhood Dis-amenities in Singapore Public Housing: Data Mining and Culture Probe Study of Inconsiderate Social Behaviour

Abstract

Almost 80% of Singaporeans live in high-density, high-rise public housing neighbourhoods. They provide convenient access to recreational, commercial, and other facilities, but also challenges with inconsiderate social behaviour (e.g., littering, smoking, noisemaking), which may result in neighbourhood dis-amenities and decline in liveability, neighbourhood satisfaction and social well-being. In this study, we investigated types and locations of dis-amenities residents feedbacked about the most, reasons behind feedback behaviour, tolerance towards dis-amenities, and potential solutions. We first conducted data-mining analysis of feedback residents made through government apps, and views expressed through social media, employing machine learning techniques and spatial mapping for the entire city and in Toa Payoh neighbourhood. Then we employed culture probe method with seven residents to gain deeper understanding of their encounters with inconsiderate practices, and measures to solve or prevent them. Data-mining reveals that residents are concerned the most about littering, noise, smoking and pigeon-feeding, with more complaints occurring during the lockdown period due to COVID-19 pandemic. Concerns with health, hygiene, and disturbance, and their reoccurrence are cited as the key motivators for feedback, whereby social media posts show greater intolerance. Culture probes revealed different types of dis-amenities that affected residents the most (e.g., spitting, cat feeding, dripping of laundry, incense burning). Suggested solutions often rely on governmental measures, but also highlight the importance of individual or communal initiatives, yet with little consensus on the best ways to move forward. These findings prompted a series of participatory activities and a community platform to support co-creation of ground-up solutions.

Keywords Inconsiderate social behaviour; Neighbourhood dis-amenities; Singapore public housing; Data mining; Culture probe