Geographical distribution of the sources of IEQ complaints: an analysis through text-mining of online job reviews

Text-mining allows analyzing a large amount of non-structured data, such as online reviews, to gain insights about previously unknown information. Online job reviews contain a variety of information, ranging from salary estimations to interview experiences. Among this information, the text posted online can report an evaluation of the workplace’s indoor environmental quality (IEQ), describing both its positive and negative aspects. When referring to negative characteristics, online reviews can be considered to report IEQ complaints. Such complaints can be categorized according to the four IEQ aspects (i.e., thermal, visual, acoustic, and indoor air quality) and their combination. This paper exploits text-mining techniques to investigate the geographical distribution of the sources of IEQ complaints according to the location in which the job review is posted. The analysis is performed in terms of climate (according to the Köppen-Geiger climate classification), country, and population (to consider the distribution between high-density and low-density areas). The results show that the distribution of the source of IEQ complaints varies according to the climate and the country, even though thermal aspects are always the largest source of discomfort in all countries and climatic zones. The more significant rates of thermal complaints are observed in the U.S. and India. They could be associated with the extensive use of HVAC systems and the restrictive operating temperatures adopted in these countries. The results also show that acoustic, indoor air quality and visual complaints are more numerous in large cities than in rural areas, where thermal complaints prevail. This paper provides a picture of the current IEQ discomfort across several geographical regions and highlights the great potential of User-Generated-Content to study various aspects of the IEQ, in this case, their geographic distribution.