Difference between revisions of "ISSS608 2017-18 T1 Assign WANG YUCHEN Data Processing"
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=Geospatial and Text Data - Detecting an Epidemic Spread = | =Geospatial and Text Data - Detecting an Epidemic Spread = | ||
===Datasets=== | ===Datasets=== | ||
| − | The given datasets involved map, weather and population information of smartpolis, while the main dataset for our analysis is the microblog dataset, which contains | + | The given datasets involved map, weather and population information of smartpolis, while the main dataset for our analysis is the microblog dataset, which contains geospatial and text data gathered from tweets. |
| − | geospatial and text data gathered from tweets. | ||
| − | Through mapping the tweets information with geospatial data in the map, we | + | Through mapping the tweets information with geospatial data in the map, we try to figure out the features and trends of the epidemic. The weather information also helps us detect the transmission of the epidemic, whether it is airborne, waterborne, person-¬to¬-person, or something else? |
===Process of study=== | ===Process of study=== | ||
Revision as of 06:14, 16 October 2017
Smartpolis Epidemic Outbreak
| Visual Detective
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To be a Visual Detective
Geospatial and Text Data - Detecting an Epidemic Spread
Datasets
The given datasets involved map, weather and population information of smartpolis, while the main dataset for our analysis is the microblog dataset, which contains geospatial and text data gathered from tweets.
Through mapping the tweets information with geospatial data in the map, we try to figure out the features and trends of the epidemic. The weather information also helps us detect the transmission of the epidemic, whether it is airborne, waterborne, person-¬to¬-person, or something else?
Process of study
- Text explorer of the tweets by date to figure out symptoms and details which describe the outbreaks
Through JMP's text visualization tool, two types of illness are detected, one is breathing related illness with symptoms listed below.
The other one is stomach related diseases with symptoms listed below.
- Filter out unrelated tweets and map the informative tweets with geospatial data to trail the spread of epidemic
- Drill down the trends of the texts through visualization tools to characterize the illnesses
