Review Design Professional's Guide to Zero Net Energy Buildings by Charles Eley
Year: 2020

own custom software (Urban Attitudes) their methodological framework, and their analytical strategies. Using a small sample of geocoded tweets from Bedford, Massachusetts, the authors used Urban Attitudes software to organize the data and run all tweets through the sentiment dictionary AFINN (named after developer Finn Arup Nielsen) Next, the authors undertook a cross comparison of the software's findings of positive and negative sentiments with the results using the sentiment analysis module of IBM's SPSS Modeler, which uses its own dictionary. While the SPSS Modeler uses an entire tweet as a unit of analysis, Urban Attitudes uses individual words. Nevertheless, the findings with respect to positive and negative sentiments are similar. Thus, the authors point out that Urban Attributes is a valid tool. Finally, the authors present a list of twenty four frequently occurring urban expressions (e.g. school, children, safety, vacant lot, zoning, health) assembled from meeting minutes of planning and administrative meetings that they use as the building blocks as the focus for urban social listening to study cities. Chapter 4 "A Close Look at Urban Immigrant Communities" presents a case study of the well being of Portuguese speaking communities in five selected areas in Massachusetts based on previously described sentiment analysis of microblogging data. The well being of Portuguese speaking residents is compared to that of English speaking residents by analyzing tweets written in Portuguese and in English for each of the five study areas. Using more than one study area adds validity and allows for applying a two sample T test to provide for statistical significance. The authors compare their sentiment analysis findings to demographic information by the US Bureau of the Census and conduct a Spearman's rho test. In short, the authors find significant differences between Portugueseand Englishspeaking residents for some, but not all, of the study areas at the 5 percent level of significance. In addition, the analysis further shows statistically significant correlations between the sentiment variables and some of the demographic variables. The latter finding indicates that the sentiment analysis can indeed be a valuable supplement to traditional analysis based on demographic data. However, the authors could have done more to explain how planners and policy makers can specifically utilize the presented information for planning purposes. In other words, the presented analysis is purely descriptive in nature. Indeed, some readers may wonder about the consequences and implications of local planners' knowing important patterns, trends, and relationships of these two selected linguistic communities. Chapter 5 "A National Comparison: Twitter versus the American Housing Survey" presents a second case study of applied sentiment analysis, looking at how residents perceive neighborhood quality of life with respect to population changes between 1970 and 2010 for eight selected cities. The question the authors try to answer is whether residents of cities with declining populations have a lower evaluation of life satisfaction than residents of growing cities. The authors compare results from the sentiment analysis with average neighborhood satisfaction results from AHS, where residents rate their neighborhoods on a scale from 1 to 10. The comparison suggests that there is no significant correlation between population change and residents' SWB as measured by either AHS or tweets. Furthermore, there is no statistically significant correlation when ranking the cities based on AHS and tweet results. The authors partly explain these findings with the fact that the tweets and AHS measure two different concepts of SWB, namely, affect and life satisfaction. The authors provide an interesting discussion of the strengths and weaknesses of the sentiment analysis. First, social media are used more frequently by younger people but have limits in terms of their usefulness for evaluating SWB for a broader range of urban residents. In addition, language based challenges to accurately measuring sentiment are still common as current software dictionaries usually do not cope well with slang, emotions, negations, and sarcasm. Finally, chapter 6 "Conclusions" provides a deep discussion of the limitations of sentiment analysis covered in previous chapters, with some recommendations for future research. Indeed, we wholeheartedly agree with the authors that "tweets can be considered a complement to existing, imperfect measures of attitudes and opinions, such as surveys and interviews" (p. 78) In summary, the book offers a good introductory discussion of sentiment analysis and demonstrates how to conduct a sentiment analysis. The concept of validity is explicitly addressed in the applied studies by comparing the results from the five gateway cities to the results of three specifically selected cities in chapter 4 or by cross comparison with AHS survey results in chapter 5. The authors demonstrate the potentials and pitfalls of microblogging data in studying cities as the book title promises. However, we would have appreciated a more thorough discussion of how the findings and outcomes of the case studies are of specific value to city planners and policy makers. The book is well structured, its language is easy to comprehend, and the research questions of each chapter are well presented. We recommend the book to advanced undergraduate and graduate students as well as practitioners interested in analyzing big data.