Text analysis of pub rice on Yokohama City IR

0. Introduction

The August issue of "Public Relations Yokohama" was posted, so read it immediately. I always enjoyed reading it because I was always referred to by household consultations, such as "Well, the monthly food expenses for two people were too high for 50,000 yen !?" This month, there was an article about Yokohama City IR pub rice (I was doing it around April of this year), so when I looked at it, I heard that about 10,000 pub rice were received. It is unlikely that pub rice will receive such comments, so I wondered if there was any raw data, and when I looked at it it was!

The raw text data was released after processing information such as slander and slander. The city of Yokohama categorized the issues of pub rice into about five,

1. Aggregation results described in the pub rice summary report

For the time being, you can see the overall result.

1.1 Number of submitters of opinions

Submission method Number of submitters of opinions
Mail 1782
F A X 1189
e-mail 1724
Bring a window 345
total 5040

1.2 Classification of opinions

category Opinion item Number of opinions
Opinion on direction (draft)- 8621 cases
3.1 Yokohama IR Direction Basic Concept-Yokohama IR Direction Basic Concept (995 cases)
3.2 Yokohama IR Direction 1 Achieve the world's highest level of IR-Yokohama IR Direction 1 Achieve the world's highest level of IR (877 cases)
3.3 Direction of Yokohama IR 2 Fusion with the city center coastal area-Direction of Yokohama IR 2 Fusion with the city center coastal area (789 cases)
3.4 Yokohama IR Direction 3 Innovation in tourism and economy at All Yokohama-Yokohama IR Direction 3 Innovation in tourism and economy at All Yokohama (1620 cases)
3.5 Direction of Yokohama IR 4 Construction of Yokohama model for safety and security measures-Direction of Yokohama IR 4 Construction of Yokohama model for safety and security measures (1366 cases)
3.6 Background of efforts, effect of IR realization, promotion of understanding of the region, consensus building, schedule, etc.-Background of efforts, effect of IR realization, promotion of understanding of the region, consensus building, schedule, etc. (2974 cases)
4 Other opinions (opinions not related to the draft)- 888 cases
total- 9509 cases

1.3 Status of response to opinions

Classification Correspondence situation Number of opinions
Repair What will be used as a reference for changing the draft 387 cases
Consideration Items already described in the draft, items that will be used as a reference for future projects and initiatives 8234 cases
Other Other opinions (opinions not related to the draft) 888 cases
total 9509 cases

2 Take a look

df = pd.read_csv("https://docs.google.com/spreadsheets/d/e/2PACX-1vSzhD4TYx7nQ1a73zQW6ufe9w9-jEuwgYcwPLeM-ey25XbSTwYQUkw8802UM2DMLzpnS92vHn8jQdkj/pub?gid=1919825840&single=true&output=tsv",sep='\t')

無題1.png

2.1 Word aggregation

Aggregate only nouns. It seems that what you are saying is quite transmitted.

image.png

2.1.1 (Miscellaneous) Pros and cons

If the word "agree / disagree" is included, a line of pros and cons will be created because it will be for / disagree with this proposal.

df ['sanpi'] = df ['opinion']. Apply (lambda x:'agree' if'agree' in x or'agree' in x else ('opposite' if'opposite' in x or'withdraw' in x else'unprocessed'))) df['sanpi'].value_counts()

result It's quite divided. Since there is a mixture of pros and cons for unprocessed, processing is required.

position number
Untreated 6404
Opposition 2106
Agree 1002

for pos in ['Agree',' Disagree','Unprocessed']: print ("---- {} Opinion ----". format (pos)) print (df [df ['sanpi'] == pos] ['opinion']. Head (5))

---- Agree ---- 1 I agree with you. Please proceed positively. By the way, I was born and raised in Yokohama. When I was little, Yamashita Park was ... 4 I agree with IR I think Yokohama will be better. I will do my best to support you! !! 5 I agree with IR. I think Yokohama will be better. good luck! !! 6 I agree with IR. I think this is a great opportunity to utilize the potential of Yokohama. I support you! !! 8 I agree with IR. I want Yokohama to be 100 years old and say "I'm glad I lived in Yokohama all the time" ... Name: Opinion, dtype: object ----opposite opinion---- 2 Absolutely the opposite. 3 The introduction of IR attraction should be withdrawn immediately. 7 I am against attracting IRs. I don't think it is necessary in Japan, of course, in Yokohama. 11 The draft direction of Yokohama IR states that it is beautiful, but the biggest Nerai is to build a casino facility in it ... 12 Absolutely no questions asked No casino required Name: Opinion, dtype: object ---- Unprocessed Opinion ---- 0 We should proceed for the future of Yokohama. 18 With the consumption of Japan as a whole declining in Corona and the economy stagnating, the mayor is encouraged to finance from Yokohama at IR Casino ... 23 The spread of the new coronavirus is having a major impact on the world economy. Even in Japan ... 25 I AGREE TO INVITING YOKOHAMA IR!! YOKOHAMA IR ... 26 I think it's very good

2.2 Word cloud

2.2.1 Overall

image.png

2.2.2 By "correction" and "reference"

I thought the topic had changed drastically, but it didn't change much at first glance. ..

image.png

2.3 Characteristic word group for each category

2.3.1 Differentiation of "opinion" and "correction"

Calculate the importance by creating 5 models centered on the wood system, which are classified by 2 values, whether they end with "reference" or are reflected up to "correction". The closer it is to yellow, the higher the importance (words that appear biased toward either side). This one seems to better see the topics reflected in the "correction" opinion.

image.png

A confusion matrix is created and the F value is about 0.96. It seems that the fact that the number of data is unbalanced but can be divided cleanly reflects a specific opinion. This time around, the economic effect on the "shopping" district, measures against "infectious diseases", and "over tourism". Is "code" a dress code?

Let's look at some specific comments from the most important ones.

word ='shop' df [df ['opinion'] .str.contains (word)] image.png

word ='infection' df [df ['opinion'] .str.contains (word)] image.png

word ='overtourism' df [df ['opinion'] .str.contains (word)]

category No opinion Correspondence situation
1534 3.2 540.0 I want you to improve the surrounding environment at the same time so as not to become overtourism. Fix
1539 3.2 545.0 Due to the problem of coronavirus infection, it became clear that excessive human concentration should be avoided.... Fix
1542 3.2 548.0 Develop roads, pedestrian walkways, and public transportation that can accommodate large-scale customer attraction facilities, and deal with traffic congestion and overtourism... Fix
1546 3.2 552.0 It is a draft with 20 to 40 million visitors, and I do not know if I expect this, but Nishi Ward and... Fix
1547 3.2 553.0 The current city of Yokohama is already overpopulated, and if more people come, the surrounding area will become over-tourist.... Fix
1549 3.2 555.0 I would like you to take measures such as security, addiction, and overtourism to revitalize Yokohama. Fix
2605 3.3 732.0 Regarding access to the area around IR, it may be insufficient for articulated buses. Singapore... reference

2.3.2 Distinguishing between "agree" and "disagree"

features Random Forest feature importances Extra Trees feature importances AdaBoost feature importances Gradient Boost feature importances SVC featrure importances
1285 casino 0.045144 0.015389 0.013333 0.219394 0.045144
6946 IR 0.031946 0.009200 0.006667 0.050034 0.031946
5602 Absolutely 0.029189 0.014611 0.010000 0.044003 0.029189
3867 Thoughts 0.018031 0.009544 0.006667 0.028076 0.018031
944 want 0.027549 0.011890 0.003333 0.026869 0.027549
979 No 0.011003 0.003524 0.006667 0.024061 0.011003
3629 Citizen 0.003703 0.001643 0.006667 0.014392 0.003703
661 Can 0.002244 0.002126 0.013333 0.013667 0.002244
740 Absent 0.006860 0.001467 0.006667 0.013362 0.006860
70 Good 0.024577 0.013051 0.010000 0.013212 0.024577
662 it can 0.017260 0.004285 0.006667 0.012382 0.017260
325 Please give me 0.010329 0.007631 0.010000 0.011040 0.010329
3877 think 0.011447 0.007665 0.006667 0.011004 0.011447
4893 Activity 0.011980 0.033780 0.003333 0.010879 0.011980
667 is 0.007067 0.003214 0.003333 0.010223 0.007067
6064 plan 0.010016 0.002721 0.006667 0.009909 0.010016
433 Tightly 0.005392 0.016280 0.003333 0.009701 0.005392
3974 opinion 0.005566 0.001066 0.003333 0.009596 0.005566
812 about 0.007158 0.006062 0.013333 0.009207 0.007158
364 thing 0.002742 0.000340 0.003333 0.009126 0.002742
366 this 0.001693 0.000244 0.003333 0.007973 0.001693
4402 Measures 0.006044 0.010119 0.010000 0.007203 0.006044
5237 development 0.013451 0.008657 0.003333 0.006650 0.013451
5254 Blank paper 0.001903 0.002185 0.003333 0.006503 0.001903
6292 Gambling 0.013954 0.003473 0.010000 0.006346 0.013954
2306 Dependence 0.011650 0.003975 0.003333 0.006191 0.011650
134 Is 0.005019 0.001538 0.006667 0.005584 0.005019
6019 Tourism 0.006276 0.005610 0.003333 0.005410 0.006276
2214 However, 0.000887 0.000535 0.003333 0.005279 0.000887
3162 Basic 0.005198 0.003290 0.010000 0.005259 0.005198
273 Can be 0.001151 0.001321 0.003333 0.004983 0.001151
4427 quickly 0.002175 0.005300 0.003333 0.004890 0.002175
4249 Promotion 0.001771 0.000212 0.000000 0.004880 0.001771
5551 Draft 0.001307 0.002154 0.003333 0.004786 0.001307
975 Masu 0.007489 0.000759 0.000000 0.004608 0.007489
4547 Expectations 0.011055 0.012767 0.006667 0.004488 0.011055
778 If 0.001325 0.000296 0.003333 0.004451 0.001325
2137 How it works 0.007645 0.012704 0.006667 0.004389 0.007645
1324 gambling 0.009497 0.004378 0.006667 0.004227 0.009497
2119 this time 0.003435 0.002226 0.003333 0.003688 0.003435
2546 Can do 0.005972 0.006023 0.006667 0.003683 0.005972
4688 Yokohama 0.002548 0.001370 0.000000 0.003650 0.002548
480 To do 0.002029 0.001075 0.003333 0.003648 0.002029
5879 Go 0.001787 0.002110 0.003333 0.003633 0.001787
4452 I'd love to 0.002008 0.003961 0.006667 0.003410 0.002008
2980 Included 0.000075 0.000032 0.006667 0.003407 0.000075
787 Become 0.001587 0.000883 0.006667 0.003274 0.001587
2445 Admission 0.001122 0.000649 0.003333 0.003221 0.001122
1600 Pachislot 0.000000 0.000612 0.003333 0.002849 0.000000
278 From 0.001011 0.000759 0.000000 0.002804 0.001011

df ['wakati'] = df ['opinion'] .apply (wakati_mecab) df['wakati'] = df['wakati'].replace({'Agree|Agree|Opposition|Withdrawal':''},regex=True) matrix, names, y_tra = get_sparce_matrix (df [df ['sanpi']! ='Unprocessed'],'wakati','sanpi')

2.4 LDA (topic model)

Agree
====== Topic 0 ====== word prob 0 gold 0.039881 1 Agree 0.019905 2 IR 0.019235 3 years 0.012214 4 early 0.010971 5 Hope 0.010420 6 cities 0.010050 7 Yokohama 0.009538 8 Citizen 0.009480 9 Burden 0.008753 ====== Topic 1 ====== word prob 0 Agree 0.036193 1 IR 0.032817 2 people 0.026546 3 thought 0.025401 4 Yokohama 0.024380 5 target 0.021133 6 Corona 0.017271 7 Introduction 0.016123 8 Casino 0.012665 9 Specific 0.012142 ====== Topic 2 ====== word prob 0 nan 0.062391 1 year 0.038379 2 Agree 0.019877 Episode 3 0.017015 4 method 0.016732 5 Sales increase 0.016436 6 Election 0.015749 7 IR 0.015739 8 1 0.011609 9 reduction 0.011422 ====== Topic 3 ====== word prob 0 Agree 0.025471 1 IR 0.024914 2 Municipal administration 0.019222 3 Citizens 0.019068 4 selections 0.016680 5 Yokohama 0.014022 6 mayor 0.012883 7 Impact 0.011415 8 city 0.010853 9 town 0.010783 ====== Topic 4 ====== word prob 0 Yokohama 0.047014 1 IR 0.039254 2 mayor 0.024489 3 Agree 0.024379 4 ・ 0.0188898 5 Attract 0.017829 6 Promotion 0.015244 7 cities 0.014124 8 Many 0.013337 9 hearing 0.012633 ====== Topic 5 ====== word prob 0 Citizen 0.056743 1 IR 0.040896 2 Casino 0.038895 3 Yokohama 0.037232 4 Agree 0.036916 5 Opposition 0.023289 6 mayor 0.023218 7 Attract 0.018109 8 Description 0.016881 9 thought 0.016789 ====== Topic 6 ====== word prob 0 nan 0.938510 1 Reflected 0.001564 2 Positive 0.001365 3 Trust 0.001182 4 Procedure 0.001160 5 IR 0.000941 6 times 0.000897 7 thought 0.000773 8 launch 0.000688 9 Agree 0.000584 ====== Topic 7 ====== word prob 0 nan 0.082423 1 Q 0.022329 2 mayor 0.021095 3 Agree 0.020343 4 Result 0.017322 5 Yokohama 0.016735 6 factions 0.015124 7 HP 0.014980 8 IR 0.013357 9 Casino 0.012042 ====== Topic 8 ====== word prob 0 IR 0.057196 1 Yokohama 0.039346 2 Agree 0.034646 3 thought 0.034076 4 Residents 0.029105 5 votes 0.026869 6 Attract 0.023697 7 people 0.015772 8 cities 0.012917 9 Business 0.012631 ====== Topic 9 ====== word prob 0 0 0.042875 1 Casino 0.035204 2 2 0.021080 3 o'clock 0.016271 4 gambling 0.015599 5 Opposition 0.013966 6 9 0.012230 7 Plan 0.011809 8 nan 0.011778 9 ) 0.011564
Opposite
====== Topic 0 ====== word prob 0 IR 0.034444 1 Casino 0.031587 2 Yokohama 0.028335 3 Opposite 0.025735 4 cities 0.019126 5 Citizen 0.017848 6 2 0.016689 7 0 0.015812 8 sex 0.014714 9 ) 0.013129 ====== Topic 1 ====== word prob 0 Casino 0.099108 1 Opposite 0.073668 2 Yokohama 0.056968 3 IR 0.036165 4 Absolute 0.033869 5 Attract 0.031747 6 cities 0.021524 7 Finance 0.016254 8 gambling 0.012545 9 Gambling 0.011134 ====== Topic 2 ====== word prob 0 Casino 0.039083 1 Opposite 0.025963 2 illness 0.025086 3 dependence 0.022148 4 people 0.020454 5 Opinion 0.019148 6 Attract 0.019066 7 Citizens 0.018166 8 many 0.017188 9 IR 0.016424 ====== Topic 3 ====== word prob 0 Corona 0.042335 1 Casino 0.030375 2 Opposite 0.021179 3 New 0.019993 4 infection 0.018356 5 messenger 0.017009 6 Tax 0.015720 7 Yokohama 0.015411 8 Budget 0.014799 9 virus 0.012776 ====== Topic 4 ====== word prob 0 Blank paper 0.093806 1 year 0.051971 2 0 0.025658 3 Citizen 0.021323 After 4 0.020978 5 Decision 0.020293 6 ) 0.020253 7 ( 0.020068 8 election 0.019678 9 Opposition 0.018437 ====== Topic 5 ====== word prob 0 Citizen 0.028442 1 Last year 0.018782 2 Opinion 0.018358 3 Yokohama 0.015966 4 Policy 0.015784 5 Gambling 0.012446 6 ears 0.012267 7 heads 0.010973 8 words 0.010696 9 town 0.009997 ====== Topic 6 ====== word prob 0 Casino 0.040258 1 mayor 0.038348 2 Citizen 0.030434 3 IR 0.029625 4 Yokohama 0.026991 5 Opposition 0.026174 6 Attract 0.022058 7 cities 0.019688 8 ? 0.015200 9 Residents 0.014024 ====== Topic 7 ====== word prob 0 nan 0.923342 1 own 0.002323 2 young 0.001715 3 avoidance 0.001700 4 times 0.001219 5 Junior high school 0.001190 6 flow 0.001123 7 December 0.000912 8 special 0.000902 9 Parent 0.000882 ====== Topic 8 ====== word prob 0 opposite 0.062047 1 ! 0.042702 2 Citizen 0.037311 3 mayor 0.035762 4 Casino 0.032417 5 IR 0.028107 6 votes 0.019678 7 Opinion 0.018379 8 Yokohama 0.018074 9 misfortune 0.015743 ====== Topic 9 ====== word prob 0 Casino 0.052197 1 Citizen 0.036918 2 Yokohama 0.033726 3 Opposite 0.030859 4 ・ 0.020238 5 ! 0.015056 6 people 0.014770 7 IR 0.013741 8 thought 0.013240 9 Promise 0.012745
3.1 Yokohama IR Direction Basic Concept-Yokohama IR Direction Basic Concept
====== Topic 0 ====== word prob 0 Yokohama 0.046032 1 IR 0.036601 2 cities 0.017276 3 Casino 0.016841 4 Agree 0.015108 5 Thoughts 0.012211 6 Citizen 0.010738 7 Attract 0.009912 8 ! 0.009425 9 ) 0.008918 ====== Topic 1 ====== word prob 0 IR 0.051729 1 Opposite 0.034088 2 Agree 0.024974 3 Yokohama 0.020797 4 Attract 0.008087 5 Casino 0.008020 6 below 0.007332 7 comfort 0.005999 8 ( 0.005113 9 Absolute 0.004990 ====== Topic 2 ====== word prob 0 nan 0.074913 1 Casino 0.029202 2 IR 0.025825 3 Yokohama 0.021842 4 Attract 0.019968 5 Opposition 0.016199 6 Agree 0.010771 7 ・ 0.007450 8 target 0.006038 9 Consideration 0.005303 ====== Topic 3 ====== word prob 0 Yokohama 0.037075 1 IR 0.027041 2 thought 0.021906 3 Japan 0.012058 4 cities 0.009663 5 Economy 0.008272 6 Opposition 0.008173 7 Casino 0.007492 8 Agree 0.007481 9 ・ 0.006800 ====== Topic 4 ====== word prob 0 nan 0.048355 1 IR 0.044372 2 Yokohama 0.022841 3 Opposite 0.019988 4 Casino 0.016277 5 Absolute 0.009915 6 thought 0.007707 7 Attract 0.007260 8 Agree 0.007079 9 Need 0.006558 ====== Topic 5 ====== word prob 0 ! 0.007202 1 IR 0.006455 2 thought 0.003545 3 good 0.003545 4 YOKOHAMA 0.003297 5 below 0.002565 6 Realization 0.002564 7-ary 0.002564 8 lines 0.002564 9 Anxiety 0.002564 ====== Topic 6 ====== word prob 0 Yokohama 0.017978 1 Casino 0.012114 2 IR 0.011228 3 Opposite 0.009582 4 Expectation 0.006183 5 cities 0.005589 6 Thoughts 0.005371 7 nan 0.005023 8 target 0.004956 9 facilities 0.004569 ====== Topic 7 ====== word prob 0 nan 0.970669 1 Yokohama 0.000721 2 IR 0.000410 3 Attract 0.000402 4 Casino 0.000363 5 Opposite 0.000340 Senary 0.000278 7 World 0.000274 8 cities 0.000254 9 target 0.000231 ====== Topic 8 ====== word prob 0 Yokohama 0.080760 1 IR 0.055955 2 Opposite 0.054105 3 Casino 0.043317 4 ! 0.027844 5 Absolute 0.011920 6 cities 0.011358 7 Need 0.011018 8 Thoughts 0.008408 9 thought 0.008202 ====== Topic 9 ====== word prob 0 Yokohama 0.028519 1 IR 0.027840 2 nan 0.025731 3 Opposite 0.024880 4 Agree 0.022008 5 thought 0.016966
3.2 Yokohama IR Direction 1 Achieving the World's Highest Level IR-Yokohama IR Direction 1 Achieving the World's Highest Level IR
====== Topic 0 ====== word prob 0 Yokohama 0.023476 1 IR 0.023091 2 Casino 0.017672 3 thought 0.015606 4 Tourism 0.012936 5 facilities 0.011887 6 comfort 0.007733 7 Consideration 0.006482 8 Citizen 0.005922 9 Agree 0.005666 ====== Topic 1 ====== word prob 0 Casino 0.038360 1 IR 0.027691 2 Yokohama 0.020435 3 facilities 0.016945 4 target 0.006540 5 world 0.006237 6 sex 0.006221 7 Opposition 0.005993 8 without 0.005205 9 Citizen 0.005202 ====== Topic 2 ====== word prob 0 nan 0.036855 1 IR 0.010983 2 Yokohama 0.009702 3 facilities 0.008351 4 target 0.005629 5 Tourism 0.005305 6 Casino 0.005213 7 lines 0.005048 8 Japan 0.004708 9 world 0.004565 ====== Topic 3 ====== word prob 0 nan 0.944313 1 facility 0.001276 2 target 0.000418 3 works 0.000418 4 thought 0.000375 5 Yokohama 0.000365 6 Casino 0.000355 7 IR 0.000353 8 Japan 0.000341 9 people 0.000290 ====== Topic 4 ====== word prob 0 nan 0.057626 1 Casino 0.021631 2 IR 0.019492 3 Agree 0.005443 4 Yokohama 0.005235 5 Attract 0.004294 6 thought 0.004125 7 facilities 0.004100 8 ! 0.003875 9 MICE 0.003873 ====== Topic 5 ====== word prob 0 Casino 0.016577 1 IR 0.015906 2 facilities 0.011750 3 Yokohama 0.010143 4 world 0.005033 5 Japan 0.004880 6 target 0.004814 7 Citizen 0.004447 8 Need 0.004329 9 Opposition 0.003897 ====== Topic 6 ====== word prob 0 Casino 0.020266 1 Yokohama 0.017726 2 IR 0.013827 3 thought 0.011843 4 Tourism 0.009388 5 nan 0.008068 6 Japan 0.005805 7 ・ 0.005298 8 facilities 0.005093 9 target 0.005009 ====== Topic 7 ====== word prob 0 IR 0.024849 1 Casino 0.021311 2 Yokohama 0.019356 3 ( 0.015570 4 ) 0.015333 5 ・ 0.0008508 6 Japan 0.007582 7 facilities 0.006963 8 resort 0.006782 9 places 0.005804 ====== Topic 8 ====== word prob 0 IR 0.027895 1 Yokohama 0.026965 2 Casino 0.024761 3 facilities 0.012166 4 thought 0.008396 5 Citizen 0.006775 6 Need 0.006117 7 comfort 0.005871 8 Hotel 0.005715 9 target 0.005371 ====== Topic 9 ====== word prob 0 Yokohama 0.021339 1 IR 0.018183 2 thought 0.013644 3 Casino 0.009701 4 comfort 0.008678 5 ( 0.008353 6 ) 0.007714 7 Agree 0.007014 8 facilities 0.006693 9 places 0.006601
3.3 Direction of Yokohama IR 2 Fusion with the city center coastal area-Yokohama IR direction 2 Fusion with the city center coastal area
====== Topic 0 ====== word prob 0 thought 0.031435 1 ( 0.021839 2 ) 0.020260 3 IR 0.019925 4 Maintenance 0.019666 5 Yokohama 0.018728 6 1 0.016400 7 district 0.014276 8 Agree 0.011645 9 Casino 0.011184 ====== Topic 1 ====== word prob 0 nan 0.050074 1 Yokohama 0.009658 2 Who 0.009350 3 Yes 0.007193 Type 4 0.007018 5 rise 0.006115 6 modern 0.005036 7 ・ 0.004461 8 Casino 0.004421 9 down 0.003957 ====== Topic 2 ====== word prob 0 nan 0.060762 1 Casino 0.000836 2 Residence 0.000836 3 Opposite 0.000836 4 town 0.000836 5 Yokohama 0.000319 6 Ranking 0.000318 7 Ming 0.000318 8 including 0.000318 9 Iku 0.000318 ====== Topic 3 ====== word prob 0 Yokohama 0.046595 1 IR 0.027358 2 Casino 0.024009 3 cities 0.017719 4 cities 0.013127 5 Plan 0.012836 6 illness 0.012829 7 0 0.011049 8 ! 0.010750 9 image 0.010594 ====== Topic 4 ====== word prob 0 Yokohama 0.064073 1 IR 0.034073 2 facilities 0.026399 3 target 0.019416 4 thought 0.014218 5 sex 0.011987 6 disaster 0.011098 7 New 0.010925 8 Casino 0.010170 9 0.009928 ====== Topic 5 ====== word prob 0 Yokohama 0.046118 1 Casino 0.036276 2 Countermeasure 0.029657 3 Transportation 0.020583 4 town 0.020112 5 Yamashita 0.019625 6 ・ 0.0187872 7 target 0.015027 8 Park 0.013543 9 Thoughts 0.011970 ====== Topic 6 ====== word prob 0 Yokohama 0.014031 1 IR 0.011430 2 infection 0.009386 3 Landscape 0.008865 4 town 0.008599 5 2 0.007873 6 large 0.007661 7 Corona 0.007150 8 Citizen 0.007062 9 Business 0.006678 ====== Topic 7 ====== word prob 0 ・ 0.025136 1 Yokohama 0.017455 2 . 0.016707 3 nan 0.016424 4 Casino 0.013441 5 things 0.012911 6 IR 0.010202 7 Foreign 0.009894 8 0 0.009783 9 o'clock 0.008438 ====== Topic 8 ====== word prob 0 nan 0.256493 1 withdrawal 0.008938 2 0.007898 worldwide 3 Property 0.003103 4 Yokohama 0.002693 5 Casino 0.002667 6 Tourism 0.001620 7 decline 0.001521 8 Request 0.001520 9 Attract 0.001358 ====== Topic 9 ====== word prob 0 nan 0.967214 1 Casino 0.000121 2 Yokohama 0.000084 3 IR 0.000058 4 image 0.000049 5 culture 0.000048 6 Opposition 0.000038 7 Need 0.000034 8 less 0.000033 9 YOKOHAMA 0.000031
3.4 Direction of Yokohama IR 3 Innovation in tourism and economy in all Yokohama-Direction of Yokohama IR 3 Innovation in tourism and economy in all Yokohama
====== Topic 0 ====== word prob 0 estimate 0.007931 1 myself 0.004272 2 Danger 0.004165 3 Business 0.003610 4 Consideration 0.003213 5 Insurance 0.003038 6 through 0.003037 7 unpaid 0.003037 8 Focus 0.003037 9 National Health Insurance 0.003037 ====== Topic 1 ====== word prob 0 nan 0.959033 1 IR 0.000011 2 Yokohama 0.000011 3 Casino 0.000011 4 Appropriation 0.000011 5 Determination 0.000011 6 Half price 0.000011 7 cities 0.000011 8 thought 0.000011 9 Trade fair 0.000011 ====== Topic 2 ====== word prob 0 nan 0.055498 1 IR 0.000255 2 Yokohama 0.000255 3 Casino 0.000255 4 Appropriation 0.000255 5 Determination 0.000255 6 Half price 0.000255 7 Trade fair 0.000255 8 cities 0.000255 9 Kansai 0.000255 ====== Topic 3 ====== word prob 0 Yokohama 0.030913 1 IR 0.030553 2 Casino 0.024471 3 0 0.017319 4 cities 0.015287 5 thought 0.010196 6 Citizen 0.010158 7 effect 0.009052 8 people 0.008950 9 Economy 0.008827 ====== Topic 4 ====== word prob 0 Yokohama 0.031740 1 IR 0.030894 2 Casino 0.028182 3 cities 0.016468 4 0 0.013079 5 Citizens 0.010768 6 thought 0.010232 7 target 0.009626 8 Economy 0.008623 9 people 0.008119 ====== Topic 5 ====== word prob 0 Yokohama 0.029495 1 IR 0.022474 2 Agree 0.011760 3 children 0.010785 4 Expectation 0.010526 5 effect 0.010443 6 cities 0.008402 7 Economy 0.008175 8 Casino 0.007801 9 Attract 0.007528 ====== Topic 6 ====== word prob 0 nan 0.090475 1 IR 0.000245 2 Yokohama 0.000245 3 Casino 0.000245 4 Appropriation 0.000245 5 Determination 0.000245 6 Half price 0.000245 7 Trade Fair 0.000245 8 Kansai 0.000245 9 Next generation 0.000245 ====== Topic 7 ====== word prob 0 nan 0.006866 1 North 0.003863 2 Estimate 0.003765 3 souvenir 0.003765 4 method 0.002076 5 However 0.002076 6 Cooking 0.002076 7 Nationality 0.002071 8 limit 0.002071 9 grip 0.002071 ====== Topic 8 ====== word prob 0 nan 0.019196 1 half price 0.002064 2 Wiping 0.002063 3 Negative 0.002063 4 IR 0.000264 5 Yokohama 0.000264 6 Casino 0.000264 7 Appropriation 0.000263 8 Determination 0.000263 9 cities 0.000263 ====== Topic 9 ====== word prob 0 nan 0.019504 1 Auxiliary 0.002163 2 valve 0.002163 3 Waste 0.002163 4 Nursery school 0.002163 5 Tsuke 0.002111 6 IR 0.000262 7 Yokohama 0.000262 8 Junior high school 0.000262 9 School lunch 0.000262
3.5 Direction of Yokohama IR 4 Construction of Yokohama model of safety and security measures-Direction of Yokohama IR 4 Construction of Yokohama model of safety and security measures
====== Topic 0 ====== word prob 0 dependency 0.009985 1 Gambling 0.007971 2 illness 0.007080 3 Casino 0.006795 4 nan 0.004834 5th grade 0.004428 6 Countermeasure 0.004139 7 cities 0.004110 8 Yokohama 0.003993 9 increase 0.003906 ====== Topic 1 ====== word prob 0 nan 0.707560 1 Casino 0.000087 2 dependence 0.000087 3 illness 0.000087 4 Gambling 0.000087 5 Yokohama 0.000087 6 IR 0.000087 7 Countermeasure 0.000087 8 Opposition 0.000087 9 Security 0.000087 ====== Topic 2 ====== word prob 0 nan 0.132564 1 Casino 0.000259 2 dependence 0.000259 3 illness 0.000259 4 Gambling 0.000259 5 Yokohama 0.000259 6 IR 0.000258 7 Countermeasure 0.000258 8 Opposite 0.000258 9 Security 0.000258 ====== Topic 3 ====== word prob 0 Casino 0.010663 1 dependence 0.008833 2 illness 0.006815 3 nan 0.005925 4 Gambling 0.004672 5 IR 0.004373 6 Opposite 0.004345 7 Yokohama 0.004340 8 i 0.004283 9 Problem 0.002481 ====== Topic 4 ====== word prob 0 Casino 0.038447 1 dependency 0.034758 2 illness 0.030814 3 Gambling 0.022548 4 Yokohama 0.022296 5 IR 0.015999 6 Countermeasure 0.014953 7 Opposite 0.012121 8 people 0.011266 9 thought 0.009036 ====== Topic 5 ====== word prob 0 Casino 0.039466 1 dependency 0.035619 2 illness 0.032418 3 Gambling 0.022223 4 Yokohama 0.020578 5 Countermeasure 0.016523 6 IR 0.016454 7 Opposite 0.012131 8 people 0.009611 9 thought 0.009363 ====== Topic 6 ====== word prob 0 nan 0.357215 1 Casino 0.000192 2 dependence 0.000192 3 illness 0.000192 4 Gambling 0.000191 5 Yokohama 0.000191 6 IR 0.000191 7 Countermeasure 0.000191 8 Opposite 0.000191 9 Security 0.000191 ====== Topic 7 ====== word prob 0 nan 0.186162 1 Casino 0.000243 2 dependence 0.000243 3 illness 0.000243 4 Gambling 0.000243 5 Yokohama 0.000242 6 IR 0.000242 7 Countermeasure 0.000242 8 Opposite 0.000242 9 Security 0.000242 ====== Topic 8 ====== word prob 0 Casino 0.037000 1 dependency 0.032611 2 illness 0.029437 3 Gambling 0.021825 4 Yokohama 0.019739 5 Countermeasure 0.016257 6 IR 0.015574 7 Opposite 0.010480 8 people 0.009681 9 thought 0.009634 ====== Topic 9 ====== word prob 0 nan 0.956174 1 Casino 0.000013 2 dependence 0.000013 3 illness 0.000013 4 Gambling 0.000013 5 Yokohama 0.000013 6 IR 0.000013 7 Countermeasure 0.000013 8 Opposition 0.000013 9 Security 0.000013
3.6 Background of efforts, effect of IR realization, promotion of regional understanding / consensus building, schedule, etc.-Background of efforts, effect of IR realization, promotion of regional understanding / consensus building, schedule, etc.
====== Topic 0 ====== word prob 0 sandy beach 0.033390 1 ticket 0.016044 2 operator 0.013330 3 nan 0.011632 4 Return 0.010908 5 fish 0.008180 6 shells 0.008180 7 ◆ 0.006741 8 Invitation 0.006704 9 canoe 0.006653 ====== Topic 1 ====== word prob 0 Contract 0.024358 1 virus 0.017025 2 virus 0.010052 3 Act 0.007289 4 bound 0.006873 5 in 0.006862 6 event 0.006587 7 Prohibition 0.006284 8 Rejection 0.006153 9 difficulty 0.005524 ====== Topic 2 ====== word prob 0 Casino 0.030689 1 Yokohama 0.027350 2 IR 0.027209 3 Citizens 0.019461 4 cities 0.016959 5 Corona 0.014732 6 Opposite 0.010254 7 Thoughts 0.010221 8 Business 0.009930 9 0.009054 ====== Topic 3 ====== word prob 0 Casino 0.046275 1 Yokohama 0.028841 2 IR 0.028204 3 cities 0.019273 4 gambling 0.018259 5 Citizens 0.017483 6 Opposition 0.014544 7 Business 0.011322 8 ) 0.009808 9 ( 0.009805 ====== Topic 4 ====== word prob 0 nan 0.716229 1 misfortune 0.000056 2 virus 0.000056 3 sandy beach 0.000056 4 virus 0.000056 5 CSR 0.000056 6 Assumption 0.000056 7 Punishment 0.000056 8 Remains 0.000056 9 Sovereignty 0.000056 ====== Topic 5 ====== word prob 0 gold 0.030817 1 contract 0.025485 District 2 0.023621 3 virus 0.012662 4 misfortune 0.011943 5 virus 0.010278 6 IR 0.009862 7 propulsion 0.009245 8 priority 0.007648 9 Penalty 0.007552 ====== Topic 6 ====== word prob 0 virus 0.012059 1 virus 0.011974 2 misfortune 0.007783 3 Assumption 0.007014 4 First 0.006987 5 Regular 0.006879 6 in 0.006678 7 Agreement 0.006630 8 Disclosure 0.005964 9 Contract 0.005869 ====== Topic 7 ====== word prob 0 nan 0.871513 1 misfortune 0.000025 2 virus 0.000025 3 Sandy beach 0.000025 4 virus 0.000025 5 CSR 0.000025 6 Assumption 0.000025 7 Punishment 0.000025 8 Remains 0.000025 9 Sovereignty 0.000025 ====== Topic 8 ====== word prob 0 nan 0.152195 1 misfortune 0.000174 2 virus 0.000171 3 virus 0.000169 4 sandy beach 0.000168 5 CSR 0.000168 6 postponed 0.000168 7 Assumption 0.000168 8 punishment 0.000168 9 Remains 0.000168 ====== Topic 9 ====== word prob 0 Yokohama 0.036546 1 Citizen 0.029244 2 Casino 0.026907 3 IR 0.026555 4 cities 0.019777 5 ( 0.013212 6 ) 0.013041 7 Opposition 0.012819 8 Description 0.009755 9 target 0.008527
4 Other opinions (opinions not related to the draft)
====== Topic 0 ====== word prob 0 Citizen 0.034754 1 mayor 0.031555 2 Casino 0.025074 3 Yokohama 0.020426 4 IR 0.016711 5 Attract 0.015037 6 Opinion 0.012715 7 Election 0.011609 8 Blank paper 0.011597 9 votes 0.011080 ====== Topic 1 ====== word prob 0 Citizen 0.032818 1 mayor 0.031709 2 Casino 0.026090 3 Yokohama 0.021673 4 IR 0.017723 5 Attract 0.012821 6 votes 0.011204 7 Blank paper 0.011120 8 Opinion 0.011087 9 cities 0.011030 ====== Topic 2 ====== word prob 0 Mayor 0.033431 1 Citizen 0.032862 2 Casino 0.024000 3 IR 0.018101 4 Yokohama 0.017661 5 Attract 0.014563 6 Blank paper 0.012731 7 Election 0.011170 8 Opinion 0.010372 9 cities 0.009200 ====== Topic 3 ====== word prob 0 Citizen 0.036627 1 mayor 0.029157 2 Casino 0.025975 3 IR 0.019609 4 Yokohama 0.018717 5 Attract 0.015018 6 Opinion 0.012309 7 Blank paper 0.011240 8 votes 0.011196 9 Election 0.010792 ====== Topic 4 ====== word prob 0 Mayor 0.028106 1 Citizen 0.024026 2 Casino 0.020297 3 IR 0.018479 4 Yokohama 0.018317 5 Blank paper 0.017392 6 votes 0.016034 7 Residents 0.015913 8 election 0.014335 9 Opinion 0.012537 ====== Topic 5 ====== word prob 0 Mayor 0.033718 1 Casino 0.028583 2 Citizen 0.026994 3 IR 0.018146 4 Yokohama 0.017711 5 Residents 0.015480 6 Blank paper 0.014311 7 votes 0.013494 8 Opinion 0.012025 9 Attract 0.011533 ====== Topic 6 ====== word prob 0 nan 0.023749 1 mayor 0.015400 2 Yokohama 0.009116 3 Casino 0.008974 4 Attract 0.008030 5 decision 0.007883 6 lines 0.007848 7 selections 0.007811 8 destination 0.007774 9 unnecessary 0.007771 ====== Topic 7 ====== word prob 0 nan 0.958089 1 mayor 0.000014 2 Citizen 0.000014 3 Casino 0.000014 4 votes 0.000014 5 Residents 0.000014 6 Blank paper 0.000014 7 IR 0.000014 8 Yokohama 0.000014 9 Opinion 0.000014 ====== Topic 8 ====== word prob 0 nan 0.058285 1 mayor 0.000317 2 Citizen 0.000316 3 Casino 0.000314 4 votes 0.000313 5 Residents 0.000312 6 Blank paper 0.000311 7 IR 0.000311 8 Yokohama 0.000311 9 Opinion 0.000310 ====== Topic 9 ====== word prob 0 Citizen 0.031133 1 mayor 0.028824 2 Casino 0.026333 3 Yokohama 0.019486 4 Residents 0.016416 5 votes 0.016064 6 Blank paper 0.010445 7 Q 0.010179 8 words 0.009699 9 Attract 0.009617

2.5 Co-occurrence network

Under construction

2.6 Sentence vector generation with transformer

making. If you make a two-dimensional map, you can see a mass of opinions.

3. Any comment

making···

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