The World Health Organization identifies noise pollution as the second leading environmental factor affecting the health of the urban population after air pollution. Exposure to high noise levels can lead to the appearance of diseases in the circulatory and nervous system, in addition to causing annoyance to the population, which is the most immediate reaction among citizens.

Noise annoyance has a strong subjective nature since besides depending on objective features, such as sound intensity, it is also related to other non-acoustic factors that depend on the distinct perception of each person. For this reason, it is essential to consider citizen participation in noise mitigation actions, as this allows city managers to identify the most annoying noise sources for the population and prioritize actions towards them, increasing the effectiveness and the impact of the interventions.

On the other hand, the evolution of ICTs (Information and Communication Technologies) has led to a change in urban management models in which, with the rise of the Internet, the paradigm of traditional management has shifted into complex systems that consider citizen participation. This technological evolution has fostered institutional transparency, which has given citizens more information about the municipal and environmental situation in their region of residence than at any other time in history.

Furthermore, with the arrival of the Information Age and the social internet, citizens have modified their communication habits and can express their opinions on social platforms. Here, they establish links with other users and actively comment on different topics, which include environmental issues. This opinion, despite not being expressed in any official media, can provide useful information for urban managers to improve their actions.

This doctoral thesis aims to incorporate ICTs into traditional noise pollution management models in cities. Public opinion is intended to be taken into account in the management of this pollutant through the use of web technologies. Moreover, the effect that transparency and communication of noise pollution has on the annoyance of the population will be measured.

To develop inclusive management systems that consider the opinions of a high percentage of the population living in a city, artificial intelligence and natural language processing techniques will be adapted to the problem of noise pollution. This will allow for extracting, classifying, and analyzing in an automated way the opinion that citizens express on social media in relation to noisy activities in cities.

It also aims to explore the use of other types of data from social media, such as multimedia content, to estimate the presence of specific sound sources in a city. This information will be used, together with other public data, to improve knowledge of the effects of urban noise on the population of a city. Managers will be able to identify the areas of the city where noise most affects residents' health to carry out sound management actions in areas where noise pollution harms a greater percentage of the population.