Spatial-temporal characterization of an urban environment using Twitter

This paper presents a study of the usage of Twitter within the context of urban activity. We retrieved a set of tweets submitted by users located in Mexico City. Tweets were labeled as either positive or negative mood using a sentiment analyzer implementation. By calculating the average mood, we were able to run a Mann-Withney´s U test to evaluate differences in the calculated mood per day of week. We found that all days of the week had significantly different medians with Sunday being the most positive day and Thursday the most negative. Additionally, we study the location for the tweets as an indicator important events and landmarks around the city.