Towards the assessment of community response to noise through social media


Noise is an important concern in modern societies affecting health and wellbeing of citizens. Beyond the physiological objective effects of noise, noise response has a big subjective component, which is reflected as a community response and traditionally evaluated through surveys. These surveys are often costly, invasive and people do not usually take part, 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 measure subjective modifying factors in a faster and less expensive way. Online Social Networks act like citizen observatories, whose data can be analysed as a trustworthy source of information since 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 their views regarding different aspects of noise, or specific noise sources. It can also provide a descriptor of the reactions towards the performance of actions against noise, something essential to engage stakeholders and improve the efficiency of policy making of the future. Conceive an automatically process in which noise opinions on the Internet are gathered, clustered and analysed, being able to provide a subjective evaluation of any noise source. 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 it should consider for this aim, such as the processes to follow and the technologies to use.

INTER-NOISE and NOISE-CON Congress and Conference Proceedings
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Luis Gasco
Luis Gasco
NLP Research Engineer