Difference between revisions of "Wyz-Visualization & Insights"
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<td><b> Number of flu-related microblog messages breakdown by symptom, May 17th-20th</b> | <td><b> Number of flu-related microblog messages breakdown by symptom, May 17th-20th</b> | ||
<br>What is also noticeable is that the areas affected spread to the downstream of Vast river on May 19th. What’s more, we discovered that the posts related to gastrointestinal problems increased gradually. The bar chart gives a breakdown of the different symptoms reported in microblog from May 17th to May 20th. It is apparently manifest from the graph that the posts related to gastrointestinal issues experienced a dramatic increase over the period from May 19th to May 20th. From the map, the reports are dense in the lower reaches of the Vast river. | <br>What is also noticeable is that the areas affected spread to the downstream of Vast river on May 19th. What’s more, we discovered that the posts related to gastrointestinal problems increased gradually. The bar chart gives a breakdown of the different symptoms reported in microblog from May 17th to May 20th. It is apparently manifest from the graph that the posts related to gastrointestinal issues experienced a dramatic increase over the period from May 19th to May 20th. From the map, the reports are dense in the lower reaches of the Vast river. | ||
+ | </td> | ||
+ | </tr> | ||
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+ | <td>[[File:Wyz-wordcloud.png|800px|center]]</td> | ||
+ | <td><b> Wordcloud by term frequency </b> | ||
+ | <br> The word cloud shows the flu-related words with high frequency in microblogs of 19th and 20th. Highlighted words "stomach" and "diarrhea" which describe abdominal problems hadn't appeared until 19th. | ||
+ | </td> | ||
+ | </tr> | ||
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+ | <td>[[File:Wyz-diarrheatext.png |800px|center]]</td> | ||
+ | <td><b> Sample messages including word "diarrhea" </b> | ||
+ | <br> To go further about this issue, the messages containing abdominal problems related words are extracted, which is shown in the screenshot to see the details. | ||
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− | <td>[[File:Wyz- | + | <td>[[File:Wyz-610road.png |800px|center]]</td> |
− | <td><b> | + | <td><b> Word Frequency table of messages containing "610" </b> |
− | <br> | + | <br> To find what happened on intersection between road 601 and Vast River, word "610" was considered as the key word to extract the most frequent words and phrases in microblogs. And unsurprisingly, a serious truck accident happened around 12 pm which was likely to even lead to fire on road 610. |
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− | <td>[[File:Wyz- | + | <td>[[File:Wyz-truck.png |800px|center]]</td> |
− | <td><b> Sample messages including word " | + | <td><b> Sample messages including word "truck accident" and "610" </b> |
− | <br> | + | <br> Then we continued to explore messages containing truck accident and inferred that pollutant carried by the truck was poured into the river where drinking water of residence nearby comes from. |
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</table> | </table> |
Revision as of 17:35, 14 October 2017
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Visualization & Insights
Contents
Origin and Epidemic Spread
Identify approximately where the outbreak started on the map (ground zero location). Outline the affected area. Explain how you arrived at your conclusion.
After a quick browse around the dataset, we can find that the content of over 1M microblog messages contains all aspects of life. So first, we start by extracting flu-related microblog messages. A list of keywords was selected to filter raw data. The list consists of keywords including flu, chill, fever, sweat, ache, pain, fatigue, cough, breath, nausea, vomit, diarrhea, and lymph, which are from observed symptoms and human judgement. After filtering, there are 71939 flu-related microblog messages left.
Visualization | Insights |
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Infer the disease outbreak date
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Map of flu-related microblog messages on May 17
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Map of flu-related microblog messages on May 18
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Map of flu-related microblog messages on May 17
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Magnification of ground zero location, May 18
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Epidemic Spread
Mode of transmission
Present a hypothesis on how the infection is being transmitted. For example, is the method of transmission person-to-person, airborne, waterborne, or something else? Identify the trends that support your hypothesis.
Person-to-person
Considering that most of the flu is spread by person-to-person, we will focus on this route of transmission first.
Visualization | Insights |
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Number of flu-related microblog messages breakdown by hour, May 18 2011
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Map of flu-related microblog messages by work status
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Airborne
Visualization | Insights |
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Changes in human traffic during the day and night
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Waterborne
Visualization | Insights |
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Number of flu-related microblog messages breakdown by symptom, May 17th-20th
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Wordcloud by term frequency
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Sample messages including word "diarrhea"
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Map of flu-related microblog messages by symptom, May 19th-20th
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Word Frequency table of messages containing "610"
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Sample messages including word "truck accident" and "610"
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