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Introduction
− The most popular micro-blogging site
− Tweets with longitude and latitude
− A gold mine for scholars in linguistics, sociology, economics, health, and psychology (Ghosh & Guha, 2013)
• West Lafayette, IN
• Most densely populated city in IN
• Home of Purdue University
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Methodology
• Collect 4160 geo-tagged tweets using the Twitter Streaming API from April 11, 2013 to April 18
• Compare the spatial distribution of geo-tagged tweets on weekdays with those at the weekend
− Point Density tool in ArcGIS 10.1
− Clustering in Esri Maps for Excel
• Analyze the tweets on an hourly basis
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Results
• Geo-tagged Tweet Clusters on Weekdays
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Results
• Geo-tagged Tweet Clusters on Weekend
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Results
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Results
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Results
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COUNT OF GEO-TAGGED TWEETS BY HOUR
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Results
• Geo-tagged Tweet Clusters from 11AM to 12PM
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Results
• Geo-tagged Tweet Clusters from 20PM to 21PM
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Conclusion
• Analyze the sptio-temporal pattern of geo-tagged tweets to discover the human mobility pattern hidden behind
• Proves the feasibility of using geo-tagged tweets, in local market research, market promotions, human mobility analysis, and even education regulation in a “college town” such as West Lafayette
• Future work
− Semantic analysis, topic modeling, and content analysis, aiming to track the spread of ideas and thoughts in local area
− Framework of extracting spatio-temporal social patterns from geo-tagged tweets in a city scale to help social researchers, demographic surveyors, market researchers, advertisers, and policy makers
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References
• Ghosh, D., & Guha, R. (2013). What are we ‘tweeting’aboutobesity? Mapping tweets with topic modeling and Geographic Information System. Cartography and Geographic Information Science, 40(2), 90-102.
• Google Earth
