Color Analysis & Season Analysis
Color Analysis
To make an imaginary world seem real, an author often makes use of words and phrases that appeal to the senses: sight, sound, smell, touch, and taste. A well-written description should arouse a particular response or emotion in the reader’s imagination. One way to use imagery in poems is using figurative language. For example, colors. We choose black & white as a pair of colors.
Season Analysis
The reincarnation of the four seasons has left many exclamations to poets at all times and in all countries year after year. Poems with seasonal words as images are everywhere. Because of the consistency of the natural characteristics of the four seasons in different places, the implied meaning of the “four seasons” image in poetry has many similarities. Some poets often use “four seasons”, while others only like “spring” or “winter”. The choice preferences of different poets indirectly reflect the characteristics of poets.
Methodology
- Color Image term analysis: Invocate <matplotlib_venn> and <wordcloud> to visualize results
- Seasons Image term analysis: use <excel> to visualize results
Preliminary Results-Data Frame
Table. top 20 Authors by black_rate
|
AuthorName |
counta |
counta_black |
black_rate |
counta_white |
white_rate |
|
5 |
5 |
100.00% |
3 |
60.00% |
|
|
12 |
10 |
83.33% |
6 |
50.00% |
|
|
6 |
5 |
83.33% |
5 |
83.33% |
|
|
27 |
22 |
81.48% |
13 |
48.15% |
|
|
羅毓嘉 |
5 |
4 |
80.00% |
1 |
20.00% |
|
曾淦賢 |
5 |
4 |
80.00% |
2 |
40.00% |
|
東野 |
9 |
7 |
77.78% |
4 |
44.44% |
|
王良和 |
9 |
7 |
77.78% |
4 |
44.44% |
|
米米 |
11 |
8 |
72.73% |
2 |
18.18% |
|
葉銳霆 |
7 |
5 |
71.43% |
1 |
14.29% |
|
梁天恩 |
7 |
5 |
71.43% |
2 |
28.57% |
|
何嘉勁 |
7 |
5 |
71.43% |
2 |
28.57% |
|
黃凱怡 |
7 |
5 |
71.43% |
4 |
57.14% |
|
樓樓 |
10 |
7 |
70.00% |
4 |
40.00% |
|
胡説 |
6 |
4 |
66.67% |
2 |
33.33% |
|
沈眠 |
12 |
8 |
66.67% |
5 |
41.67% |
|
程弋洋 |
6 |
4 |
66.67% |
3 |
50.00% |
|
Bracho, Coral |
6 |
4 |
66.67% |
3 |
50.00% |
|
Ondaatje, Michael, 1943- |
11 |
7 |
63.64% |
3 |
27.27% |
|
吳耀宗 |
8 |
5 |
62.50% |
2 |
25.00% |
Visualization Results(Some Examples)
- Venn Charts(by authors)
Fig1. Venn Chart of Frequency of Using “Black” and “White” in Poems of Author Chris Song
Fig2. Venn Chart of Frequency of Using “Black” and “White” in Poems of Author Chan Wing Choi
Fig3. Venn Chart of Frequency of Using “Black” and “White” in Poems of Author Chong Yuen Sang
Fig4. Venn Chart of Frequency of Using “Black” and “White” in Poems of Author Sui Ping
2. Wordcloud Picture(by different authors)
Fig5. Wordcloud of “Black” and “White”-Related Terms in Poems of Author Chris Song
Fig6. Wordcloud of “Black” and “White”-Related Terms in Poems of Author Lee Man Kei
3. Radar Maps
Fig7. Radar Map of Frequency of Using “Four Seasons” in Poems of Different Authors
Fig8. Radar Map of Frequency of Using “Four Seasons” in Poems of Different Authors
Code
import datetime
import pandas as pd
import pyLDAvis.gensim# 一篇文章中的重復詞只保留一個
for i in range(len(df)):
df_2=pd.DataFrame(df.loc[i,'full_text'].split(',')).drop_duplicates().reset_index(drop=True)
for j in range(len(df_2)):
if j==0:
str_i=df_2.loc[j,0]
else:
str_i=str_i+','+df_2.loc[j,0]
df.loc[i, 'full_text']=str_i