期刊
COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
卷 59, 期 -, 页码 256-268出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compenvurbsys.2015.12.001
关键词
Space-time activity; Twitter; Streaming data processing; Cloud computing
类别
资金
- SEEK (SEmantic Enrichment of Trajectory Knowledge Discovery) Project by EU FP7, PEOPLE, Marie Curie Action
The critical dimensions in describing space-time activities are what, where, when, and who, which are frequently applied to collect data about basic functions people perform in space in the course of a day. Collecting data about these dimensions using activity-based surveys has presented researchers with a number of technical and social limitations, ranging from the restricted period of time participants have to record their activities to the level of accuracy with which participants complete a survey. This paper, proposes a new streaming data processing workflow for querying space-time activities (STA) as a by-product of microblogging communication. It allows exploring a large volume of geotagged tweets to discover STA patterns of daily life in a systematic manner. A sequence of tasks have been implemented using different cloud-based computing resources for handling over one million of daily geotagged tweets from Canada for a period of six months. The STA patterns have revealed activity choices that might be attributable to personal motivations for communicating an activity in social networks. (C) 2015 Elsevier Ltd. All rights reserved.
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