Towards the assessment of community response to noise through social media


Noise is an important concern in modern societies affecting the health and wellbeing of citizens. Beyond the objective physiological effects of noise, noise response has a significant subjective component, which is reflected as a community response and has been traditionally evaluated through surveys. These surveys are often costly, invasive and people do not usually take part in them, whether you use one-to-one interview, phone-based polls or web-based forms. But the big boost of online social networks has demonstrated that some people are willing to share their views and feelings about everyday problems, including noise. Policy makers should pay attention to these new channels, as they can provide insights about community response and provide new ways of measuring subjective modifying factors in a faster and less expensive way. Online Social Networks act like citizen observatories, and their data can be analyzed as a trustworthy source of information, as humans can contextualize situations and discriminate non-important data. The analysis of these human-sensor data could give us the raw material to know the community response to noise in cities, and the citizens’ views regarding different aspects of noise, or specific sound sources. It can also provide a descriptor of reactions towards the performance of actions against noise, something essential to engage stakeholders and improve the efficiency of policymaking in the future. An automatic process in which noise opinions on the Internet are gathered, clustered and analyzed, being able to provide a subjective evaluation of any noise source can be conceived. Today this is something feasible, and it would suppose a breakthrough approach to noise assessment in cities. This paper describes possible examples of the potential of this new approach in noise management and the key methodological aspects that should be considered for this aim, such as the processes to follow and the technologies to use.

Aug 27, 2017 — Aug 30, 2017
Hong Kong, China
Luis Gasco
Luis Gasco
NLP Research Engineer