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etc [2019/04/08 02:54]
khcho 만듦
etc [2019/04/11 06:56]
jhlee
줄 143: 줄 143:
         print(noun, ":", count)         print(noun, ":", count)
 </code> </code>
 +
 +# month_avr : The average of the frequencyofthe 'patient’ morphemes per month  calculated as “ the number of 'patient’ morphemes / day *30 “ because of the data from May 20 to December 31 for 2015. \\
 +
 +# select_month : The frequency of ‘patient’ morphemes is higher than average \\
  
 {{:형태소.jpg|}} {{:형태소.jpg|}}
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 ==== Refinemnet ==== ==== Refinemnet ====
--+ 
 +get_tag() : A function that returns the frequency of the 'patient’ morpheme as a list using konlpy's Okt and extracts nouns with nouns() and figures out frequency with Counter object. \\ 
 +@param1 : Text to analyze morpheme \\ 
 +@param2 : The number of nouns to be extracted with high frequency\\ 
 + 
 +get_tags() : A function that returns a list of n morphemes with a high frequency and prints them.\\ 
 +@param1 : Text to analyze morpheme\\ 
 +@param2 : The number of nouns to be extracted with high frequency\\ 
  
 ===== Result ===== ===== Result =====
 ==== Model Evaluation and Validation ==== ==== Model Evaluation and Validation ====
 <2015> \\ <2015> \\
- 
  - The frequency of 'patient' morpheme among articles of each month \\  - The frequency of 'patient' morpheme among articles of each month \\
 {{:2015_patient.png|}} {{:2015_patient.png|}}
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 <2016> \\ <2016> \\
  - The frequency of 'patient' morpheme among articles of each month \\  - The frequency of 'patient' morpheme among articles of each month \\
 +{{:2016_patient.png|}}
 +
  - Real data on patients that actually occurred all infectious disease \\  - Real data on patients that actually occurred all infectious disease \\
 +{{:2016_epidemic.png|}}
 +
  - Correlation between 'patient' morphological frequency and all epidemic patient number \\  - Correlation between 'patient' morphological frequency and all epidemic patient number \\
 +^  ^ ** Month ** ^ ** Patient ** ^ ** Occurrences ** ^
 +^ ** Month **| 1.000000|   0.696169| 0.507285 |
 +^ ** Patient **| 0.696169 |   1.000000| ** -0.043851 ** |
 +^ ** Occurrences ** | 0.507285 |  ** -0.043851 **| 1.000000 |
 +
 <2017> \\ <2017> \\
  - The frequency of 'patient' morpheme among articles of each month \\  - The frequency of 'patient' morpheme among articles of each month \\
 +{{:2017_patient.png|}}
 +
  - Real data on patients that actually occurred all infectious disease \\  - Real data on patients that actually occurred all infectious disease \\
 +{{:2017_epidemic.png|}}
 +
  - Correlation between 'patient' morphological frequency and all epidemic patient number \\  - Correlation between 'patient' morphological frequency and all epidemic patient number \\
 +^  ^ ** Month ** ^ ** Patient ** ^ ** Occurrences ** ^
 +^ ** Month **| 1.000000|   0.490746| 0.703117|
 +^ ** Patient **| 0.490746|   1.000000| ** 0.179343** |
 +^ ** Occurrences ** | 0.703117|  ** 0.179343**| 1.000000 |
  
 ==== Justification ==== ==== Justification ====
  - 2015 year : The news article written in June showed the most abundant usage of the morpheme ‘patient’. And it was actually the same month as when there were highest number of MERS patients among the globe. \\   - 2015 year : The news article written in June showed the most abundant usage of the morpheme ‘patient’. And it was actually the same month as when there were highest number of MERS patients among the globe. \\ 
  In addition, in 2015, the usage frequency of the morpheme ‘patient’ did have a very strong positive correlation to the number of patients that actually suffered from disease, which was up to 0.985725. \\  In addition, in 2015, the usage frequency of the morpheme ‘patient’ did have a very strong positive correlation to the number of patients that actually suffered from disease, which was up to 0.985725. \\
- - 2016 year : \\ 
- - 2017 year : \\ 
  
-===== Conclustion =====+ - 2016 year : The 'patient’ morpheme did not have a high frequency as a whole, and the correlation between the frequency and the total number of infected persons was -0.043851. \\ 
 + In fact, in 2016, there was no national disaster caused by a pandemic. \\ 
 + 
 + - 2017 year : The frequencies of the "patient" morphemes were equally low evenly. The correlation between frequency and number of infections is 0.179343, which is considered to be weak. \\ 
 + In 2017, there is no national disaster caused by a contagious disease. Although the frequency of "patient" morphemes is not sufficient to identify common infectious diseases, it seems possible to understand the state of calamity caused by a pandemic. \\ 
 + 
 +===== Conclusion =====
 ==== Reflection ==== ==== Reflection ====
 In 2015 and 2017, there is a strong positive correlation between the frequency of morpheme "patient" in the article and the actual number of infectious diseases, whereas in 2016 it is seen as having a negative correlation. \\ In 2015 and 2017, there is a strong positive correlation between the frequency of morpheme "patient" in the article and the actual number of infectious diseases, whereas in 2016 it is seen as having a negative correlation. \\
etc.txt · 마지막으로 수정됨: 2021/04/13 06:54 (바깥 편집)