Habidatum pilot project for the city of Barcelona explores distribution of tourists in the city by using Twitter data of March 2015.
The objective of the project is to reveal the most popular tourist destinations in Barcelona and the sentiments associated with them expressed in the tweets.
The first pilot looks at so-called “morphology of semantic space” — spatial structures and patterns formed by social media posts.
We cluster all the variety of tweets along two key dimensions reflecting: one — the origin (tourists vs. locals) of a tweet, and the other — color (positive vs. negative) of the sentiments expressed in it.
The source of the data — Twitter, once named as a “reinvention of the town square” by its executive Dick Costolo, — is a platform for people's self-expression and opinion exchange.
Tweets are connected to certain locations in the city through either the “geotags” of the users or the “toponyms” (names of locations) mentioned in the tweets.
For the purpose of the pilot we only used tweets geotag distribution; however, we look forward to comparing geotag geography with toponym-based spatial patterns.
According to the geotag-based map of tweets, locals are pretty much scattered across the whole city space. The historical center is the most crowded by locals, although several other large concentrations in the city are clearly visible.
Tourists appear much more selective: their major concentration is seen in the Gothic Quarter and around a small part of Eixample along Passeig de Gracia.
All other parts of the urban space — the “blind spots” of city tweeter space, such as parks, beaches and remote redevelopment areas — seem to be underused by tourists.
Blind spots, usually being similarly attractive but less known, could provide extra room for the existing and future volumes of tourist flows in Barcelona reducing the pressure in the central historical part of the city.
The sentiments unveiled through semantic analysis of Twitter data are predominantly positive and “tourist”. Negative tweets are not numerous and their distribution across city space is fairly even.
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