TY - JOUR
T1 - SensePlace3
T2 - a geovisual framework to analyze place–time–attribute information in social media
AU - Pezanowski, Scott
AU - MacEachren, Alan M.
AU - Savelyev, Alexander
AU - Robinson, Anthony C.
N1 - Publisher Copyright:
© 2017, © 2017 Cartography and Geographic Information Society.
PY - 2018/9/3
Y1 - 2018/9/3
N2 - SensePlace3 (SP3) is a geovisual analytics framework and web application that supports overview + detail analysis of social media, focusing on extracting meaningful information from the Twitterverse. SP3 leverages social media related to crisis events. It differs from most existing systems by enabling an analyst to obtain place-relevant information from tweets that have implicit as well as explicit geography. Specifically, SP3 includes not just the ability to utilize the explicit geography of geolocated tweets but also analyze implicit geography by recognizing and geolocating references in both tweet text, which indicates locations tweeted about, and in Twitter profiles, which indicates locations affiliated with users. Key features of SP3 reported here include flexible search and filtering capabilities to support information foraging; an ingest, processing, and indexing pipeline that produces near real-time access for big streaming data; and a novel strategy for implementing a web-based multi-view visual interface with dynamic linking of entities across views. The SP3 system architecture was designed to support crisis management applications, but its design flexibility makes it easily adaptable to other domains. We also report on a user study that provided input to SP3 interface design and suggests next steps for effective spatiotemporal analytics using social media sources.
AB - SensePlace3 (SP3) is a geovisual analytics framework and web application that supports overview + detail analysis of social media, focusing on extracting meaningful information from the Twitterverse. SP3 leverages social media related to crisis events. It differs from most existing systems by enabling an analyst to obtain place-relevant information from tweets that have implicit as well as explicit geography. Specifically, SP3 includes not just the ability to utilize the explicit geography of geolocated tweets but also analyze implicit geography by recognizing and geolocating references in both tweet text, which indicates locations tweeted about, and in Twitter profiles, which indicates locations affiliated with users. Key features of SP3 reported here include flexible search and filtering capabilities to support information foraging; an ingest, processing, and indexing pipeline that produces near real-time access for big streaming data; and a novel strategy for implementing a web-based multi-view visual interface with dynamic linking of entities across views. The SP3 system architecture was designed to support crisis management applications, but its design flexibility makes it easily adaptable to other domains. We also report on a user study that provided input to SP3 interface design and suggests next steps for effective spatiotemporal analytics using social media sources.
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U2 - 10.1080/15230406.2017.1370391
DO - 10.1080/15230406.2017.1370391
M3 - Article
AN - SCOPUS:85029416722
SN - 1523-0406
VL - 45
SP - 420
EP - 437
JO - Cartography and Geographic Information Science
JF - Cartography and Geographic Information Science
IS - 5
ER -