Título da Dissertação
Tabela 4.4: Volume of tweets for each type of geo-location
['2* [BOLD] City', '2* [BOLD] Total', '[BOLD] Bounding-boxes  [BOLD] Distinct', '[BOLD] Bounding-boxes  [BOLD] No. Tweets', '[BOLD] Bounding-boxes  [BOLD] Percentage (%)', '[BOLD] Specific Places  [BOLD] Distinct', '[BOLD] Specific Places  [BOLD] No. Tweets', '[BOLD] Specific Places  [BOLD] Percentage (%)', '[BOLD] Precisely  [BOLD] Distinct', '[BOLD] Precisely  [BOLD] No. Tweets', '[BOLD] Precisely  [BOLD] Percentage (%)']
Looking at the numbers it is possible to conclude some facts applicable to all cities. Citizens tend to geo-locate themselves with a location which has variable bounding-box size since more than 70% of the tweets are of this type. Furthermore, only a few percentage of tweets, between 0% and 1.43%, are located in specific places, although the existence of a higher number of distinct specific places comparatively to the bounding-boxes with variable size, with exception of Melbourne that has zero specific places in our dataset.