Titlebook: Urban Social Listening; Potential and Pitfal Justin B. Hollander,Erin Graves,Dibyendu Das Book 2016 The Editor(s) (if applicable) and The A

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A Close Look at Urban Immigrant Communities,ely. Here we propose and evaluate a method for sentiment analysis of microblogging data of Portuguese-speaking residents. We ask, how do Portuguese-speaking microbloggers compare to English-speaking microbloggers in terms of overall happiness and attitude? And how do the results of a sentiment analy

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Book 2016dings of several research projects that have have?experimented with using?microblogging data in conjunction with diverse quantitative and qualitative methods, including?content analysis and advanced multivariate statistics..Applied researchers, planners and policy makers have only recently begun to

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Introduction,t to analyze sentiment in microblogs to learn more about places and the people that occupy them. This book is an attempt to chronicle that work in service of demonstrating to planners and policy makers how and how not to use Big Data to understand sentiment, populations, and places.

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Conclusion,thoughts. The chapter offers hope for using microblog data to overcome perennial limitations of other urban social science methods yet invites caution about the kinds of technical and conceptual problems that arise in doing this type of research.

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Justin B. Hollander,Erin Graves,Henry Renski,Cara Foster-Karim,Andrew Wiley,Dibyendu Dasnomenon. Instead, we have demonstrated that, for humans, biology is merely a starting point. It is the extraordinary achievements that humans strive to accomplish affer their biological cards have been dealt, whether favorable or unfavorable, that offers the truest measure of excellence.

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Taking Microblogging Data for a Test Drive,Both methods showed a relatively low percentage of sentiment overall but a greater prevalence of positive tweets. Overall, we note that the magnitude of microblogging data and the ability to capture it readily and improvements in analysis techniques may allow for quantity to compensate for low percentages of sentiment.

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