Difference between revisions of "ISSS608 2017-18 T1 Assign WANG RUI Investigation step2"
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Ruiwang.2016 (talk | contribs) (Created page with " Editing ISSS608 2017-18 T1 Assign WANG RUI Investigation step1 WikitextPreviewChangesPublishCancel BoldItalicSignature and timestampLinkEmbedded fileReferenceAdvancedSpecial...") |
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− | <div><font size = 5>''''' | + | <div><font size = 5>'''''7 Steps to the Truth: '''''</font></div> |
<div><big>'''Step #2: Verify Diagnosis.'''</big></div> | <div><big>'''Step #2: Verify Diagnosis.'''</big></div> | ||
+ | Understanding the symptoms is very crucial to the following investigation works. According to the information on the letter, observed symptoms are largely flu-like. Now, I will validate this information using the microblog message collected. | ||
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+ | [[File:wrletter.png|center|1050px]] | ||
+ | On May20, large crowd of people were observed at hospitals in different zones. To investigate what these people were talking about, I selected all messages posted near hospitals and label the senders according to their IDs. These IDs are identified as potential patients. | ||
+ | [[File:wrpatient.png|center|1050px]] | ||
+ | Then the message content is studied using text explorer. | ||
+ | [[File:wrpatient2.png|center|1050px]] | ||
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<div>[[ISSS608_2017-18_T1_Assign_WANG_RUI_Investigation step3|<big>'''Next to Step #3: Perform Descriptive Epidemiology'''</big>]]</div> | <div>[[ISSS608_2017-18_T1_Assign_WANG_RUI_Investigation step3|<big>'''Next to Step #3: Perform Descriptive Epidemiology'''</big>]]</div> |
Revision as of 01:26, 16 October 2017
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7 Steps to the Truth:
Step #2: Verify Diagnosis.
Understanding the symptoms is very crucial to the following investigation works. According to the information on the letter, observed symptoms are largely flu-like. Now, I will validate this information using the microblog message collected.
On May20, large crowd of people were observed at hospitals in different zones. To investigate what these people were talking about, I selected all messages posted near hospitals and label the senders according to their IDs. These IDs are identified as potential patients.
Then the message content is studied using text explorer.