Título da Dissertação
Tabela 4.5: Percentage of Metadata composing the datasets
['2* [BOLD] City', '2* [BOLD] Total', '[BOLD] Hashtags (#)  [BOLD] Total (tweets)', '[BOLD] Hashtags (#)  [BOLD] %', '[BOLD] User Mentions (@)  [BOLD] Total (tweets)', '[BOLD] User Mentions (@)  [BOLD] %', '[BOLD] URLs  [BOLD] Total(tweets)', '[BOLD] URLs  [BOLD] %', '[BOLD] Media  [BOLD] Total (tweets)', '[BOLD] Media  [BOLD] %']
Having this considered, we counted the volume of each element constituting the previously mentioned metadata and calculate the percentage of tweets containing it. The resulting analysis and results were performed over the tweets with the city’s native language and located inside the bounding-box area used in the filtering process. The most observable evidence in the results is the greater use of this elements in the English speaking cities. User mentions, as well as URLs are the most used metadata. This elements may suggest that citizens tend to tag other people in their messages when posting and also share information about certain topic through urls. Regarding the Brazilian cities, the metadata usage is not so noticeable. This fact may me related to the number of users composing each dataset because, as it was previously mentioned, the English speaking cities possesses almost two times more users than the Brazilian cities and this characteristic contributes to the increase of this type of metadata usage since when someone tag another one in a message, usually a re-post is sent tagging the person responsible by the starting of the conversation. To prove this so, an intensive study about social media tracking and mapping of the flow of each Twitter conversation is needed.