2013
DOI: 10.1016/j.knosys.2012.07.017
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A software architecture for Twitter collection, search and geolocation services

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Cited by 63 publications
(36 citation statements)
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References 12 publications
(7 reference statements)
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“…In [19], a software architecture for collecting and analyzing geospatial and semantic information from Twitter data was described. The tweets were consumed by a Twitter4j Java application and then transferred into a PostgreSQL database using the PostGIS spatial extension.…”
Section: Related Workmentioning
confidence: 99%
See 2 more Smart Citations
“…In [19], a software architecture for collecting and analyzing geospatial and semantic information from Twitter data was described. The tweets were consumed by a Twitter4j Java application and then transferred into a PostgreSQL database using the PostGIS spatial extension.…”
Section: Related Workmentioning
confidence: 99%
“…The goal of this infrastructure was to search for tweets via semantic keywords and coordinates, and export the results via a map or CSV file. The focus of [19] is on a particular domain-independent analysis technique and not with supporting the entire analysis life cycle for crisis informatics research. In contrast to their work, we store the entire JSON object of collected tweets in Cassandra in a way that allows us to answer all deep queries related to the entire tweet object.…”
Section: Related Workmentioning
confidence: 99%
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“…In particular, the access to the twitter API has some limitations such as: the maximum number of request calls in a period, the huge amount of tweets that can be produced for certain cases, the complexity of social relationships among users, the limited size of tweets (140 characters), and the fact that historical Twitter data are not accessible via the Twitter API, etc. These facts force the developers to set up specific architectures for collecting tweets, while attempting to get them with a sufficient reliability [38].…”
Section: Related Workmentioning
confidence: 99%
“…Carmel resolves locations using three primary methods i.e. looking up directly at the "Place" object, use reverse geocoding APIs to find the name of place from latitude and longitude co-ordinates and third look-up the location from user profile from the four methods described by Gonzalez and co-workers (Gonzalez et al, 2012, Oussalah et al, 2012. The locations obtained were in a tiered format starting from Earth and followed stepwise to country, then state, county and finally the city.…”
Section: Resolving Geolocationsmentioning
confidence: 99%