research question

8_ What are the recurring words used in relation to the different approaches?

All approaches

Against

Ironic

Concerned

Uncertain

Neutral

In favor

000 000 000 Twitter Text of an example Twitter post for each approach 000 000 000 Text of an example Twitter post for each approach Text of an example Weibo post for each approach Weibo 000 000 000 accordance 17 100 23 9 23 12 20 24 7 6 7 10 57 33 32 112 17 29 14 20 14 25 6 achieve behaviour big black blacklist business insider carry out china Chinese citizens city community creepy days data companies company construct country demeaning die dystopian economic digital 13 13 7 19 18 10 department 24 development embarrassing encourage environment episode establish 30 111 9 17 20 24 23 57 21 10 27 18 22 23 17 18 19 18 8 9 9 21 explained field frivolously future government held honest implementation importance important insight jeremy leader 12 look lose 13 42 management market mass mechanism meeting 19 13 7 10 19 10 23 10 17 8 18 20 10 8 9 8 8 12 22 41 7 22 6 6 mirror model new now organization orwellian participate party people perfect private problem province public 43 8 20 18 37 16 18 punish punishment push read real reform rewards rolls score sesame service 55 44 share solution spend started step surveillance trustworthy twitter under unite ways well work world year wrong 8 32 76 8 164 45 33 9 9 9 59 ranking 0 85 117 0 10 Twitter Reminiscent of the Black Mirror "Nosedive" episode, China has started ranking citizens with a creepy 'social credit' system — here's what you can do wrong (...) VIEW TWEET He Siyun, who was raped but listed as a drug addict, can’t take the railway anymore. I don’t dare to imagine how it will be when Social Credit System settles. VIEW POST Weibo 00 0 00 0 00 0 100 9 33 32 14 14 black business insider china Chinese citizens creepy 18 8 explained frivolously 13 18 10 8 mirror 20 18 punishment rewards spend under wrong 8 9 ranking 0 35 1 14 0 1 5 Twitter Just wait until President Newsom and his Silicon Valley supporters get behind instituting some American form of China's social credit system. That'll be fun. VIEW TWEET 100 33 14 black china Chinese 8 12 41 7 6 orwellian people private rolls twitter 33 105 44 0 15 Twitter China new Social Credit System not ready until 2020 already punished 7 million next @FoxBusiness. VIEW TWEET Big data and Artificial Intelligence will help to build a perfect Social Credit System. At the same time, everybody is gonna be more transparent but more and more easy to be controlled. VIEW POST Weibo 00 6 00 2 00 3 100 7 10 33 32 china Chinese citizens days companies digital 10 18 insight 7 9 8 12 7 6 model orwellian people private real twitter 33 ranking 23 29 big data perfect 105 44 0 15 Twitter Wonder how long until the social credit system as digital dang’an for every prc citizen becomes a reality. Not there yet, may take a few years, but seems pretty obvious what the vision is. VIEW TWEET I have a question to @Chen Changfeng @Tian Ning @Dian Zizheng : How do you think about Social Credit System? VIEW POST Weibo 00 4 00 0 00 0 100 china die dystopian digital 13 13 10 10 look 13 mass 10 surveillance twitter world 8 33 country 111 honest 41 people 45 1 14 4 7 01 1 Twitter Russian security state is watching closely the CCTV-cameras experiment in China, as well as the whole social credit system. For Chinese, some of Russian algorithms&companies (...) VIEW TWEET (...) In order to promote the traditional virtues of honesty and integrity, the city's recent work plan to strengthen the construction of personal credit system (...) VIEW POST Weibo 00 2 00 1 00 0 100 33 china Chinese 10 18 punishment rewards score twitter 33 112 20 blacklist city construct 24 development 24 57 21 held management 23 public 20 punishment trustworthy work year 32 76 164 18 10 1 4 1 0 1 0 Twitter '...providing the Chinese system is a success, western nations will begin their own journey towards this streamlining of government interference in day to day life' (...) VIEW TWEET Establishing Social Credit System will standardize the market economic order, improve the market credit environment, reduce transaction costs, and prevent economic risks. VIEW POST Weibo 00 0 00 1 00 0 100 33 china Chinese construct economic 19 21 17 18 importance important market 23 trustworthy 164 accordance 17 100 23 9 23 12 20 24 7 6 7 10 57 33 32 112 17 29 14 20 14 25 6 achieve behaviour big black blacklist business insider carry out china Chinese citizens city community creepy days data companies company construct country demeaning die dystopian economic digital 13 13 7 19 18 10 department 24 development embarrassing encourage environment episode establish 30 111 9 17 20 24 23 57 21 10 27 18 22 23 17 18 19 18 8 9 9 21 explained field frivolously future government held honest implementation importance important insight jeremy leader 12 look lose 13 42 management market mass mechanism meeting 19 13 7 10 19 10 23 10 17 8 18 20 10 8 9 8 8 12 22 41 7 22 6 6 mirror model new now organization orwellian participate party people perfect private problem province public 43 8 20 18 37 16 18 punish punishment push read real reform rewards rolls score sesame service 55 44 share solution spend started step surveillance trustworthy twitter under unite ways well work world year wrong 8 32 76 8 164 45 33 9 9 9 59 ranking 000 000 000 Twitter Text of an example Twitter post for each approach Text of an example Weibo post for each approachh Weibo 000 000 000
Description Protocol Data

Description

The treemap shows how recurring words in the posts analyzed in the previous protocol are used in relation to the approach of the post itself. Each rectangle is a word, blue if used on Twitter and red if used on Weibo; the ones with a marked rectangle around them are the ones in common. The size represents how many times a word was written. When each button is clicked, the main recurring related words used in the posts with that type of approach are highlighted. We matched these information to better understand the relation between specific words and the approaches to the theme. We decided to extrapolate words so that we could understand the vocabulary used within every approach and also in comparison between the two platforms, so the two cultures. It’s interesting to see how the word honest is used only by Chinese people, while words like die or orwellian are used only by the western world.

Protocol

example of protocol

From the previous protocol, we extracted the recurring words for both Weibo and Twitter, with Wordcounter, Text analyzer and Zhonghuayuwen. Then, we selected the first 10 recurring words and the most relevant posts for each kind of approach for both western and Chinese social networks. Finally we matched these two information in a treemap made with Raw Graph that we reworked with Illustrator.

Data

Data Source: Twitter, Weibo
Timestamp: 01/12/2018
View Data (500Kb)

The file focuses on how many times a word is written and the relation between these words and the approach of the posts in which they were used. For that reason, the dataset is made by two columns: keywords (filtered words) and occurrences.