research question

1_ What are the western and Chinese Wikipedia pages related to SCS?

Chinese pages English pages Company/Organization Seed Computer Technology Economics/Marketing Book/TV Series/Videogame Philosophy Politics Security Society Relevance (average of number of views in 2018, see also, references and length) Level #1 pages Most relevant pages PAGES LABELS CLUSTER Seed page POLITICS COMPUTER TECHNOLOGY COMPANY ORGANIZATION SECURITY PHILOSOPHY SOCIETY BOOK TV SERIES VIDEOGAME ECONOMICS MARKETING A Declaration of the Independence of Cyberspace 2017 Broadband Consumer Privacy Proposal repeal Public records in China Public records Archive Deliberative democracy Merit system Civil service entrance examination Oligarchy Election Equality of outcome Plutocracy Privacy concerns with social networking services Internet manipulation Virtual reality HTTP/2 Distributed computing Relational database Industrial big data MapReduce Database Supercomputer Object database DNSL Trust network Reblogging Decision support system Pasmanda Muslim Mahaz Employee monitoring Googlization Don't be evil Criticism of Google Time Well Spent NSA warrantless surveillance Edward Snowden Mass surveillance in the United States National security Golden Shield project Data breach Dataveillance Computer and network surveillance Synthetic Operation Center Distopia Brainwashing Cyber-utopianism Panopticism Egalitarianism Elitism Tecnocracy Henri de Saint-Simon Merit (Christianity) Merit (Buddihism) Information society Hawthorne effect Privacy by design Information Age Wasta Tara Hunt Brownie points Activity stream Egoboo Homo sacer Outlaw Undeclass Outcast (person) Burakumin Educational entrance examination Differential Education Achievement Social mobility Cronysm Ownership society Animal farm The Californian Ideology Daemon (novel series) Spying on Democracy The Happiness Industry Consent of the Networked The Wealth of Networks The Numerati Who Owns the Future? Orphans of the Sky App Development and Condiments Financial credit Credit risk Credit information Credit rating Digital branding 2018 China-United States trade war Business intelligence Statistics Operation Research Attention economy Commons-based peer production Shoshana Zuboff Market for zero-day exploits Information economics Targeted advertising Capital accumulation Neuromarketing Behavioral analysis of markets Post-capitalism Personalized marketing Technocapitalism Late capitalism Fourth Industrial Revolution Commercialization of the Internet Mass surveillance industry Social Credit System Confucianism Meritocracy Affirmative action Criticism of Facebook Anonymous Silicon Valley Tencent Internet of things Data mining Big data Sesame Credit Reputation system Untouchability Whitelisting Privacy Social capital Whuffie Big Brother (1984) Nosedive (Black Mirror) The Orville Syndicate PRISM Surveillance Mass surveillance in China Mass surveillance Surveillance capitalism Credit score Whisper network Web Analytics Sharing economy
Description Protocol Data


Thanks to this visualization we were able to analyze and see the macro topics involved with Social Credit System and to start looking into the debate with a clearer idea. To have a general but systematic overview of the topic, we explored Wikipedia as a first approach. We wanted to know what are the related themes involved in the discussion around the topic, how they are connected to each other and what is linked to Social Credit System. The visualization is able to show the existing network around the seed Social Credit System. As we wanted to keep the duality of the western world and the Chinese world, we also analyzed Wikipedia in Chinese. We know that it’s blocked in China, so at first we wanted to analyze, which is the Chinese pedia counterpart, but it wasn’t comparable because of some huge differences with Wikipedia, such as the non presence of the see also section, which was fundamental to us.

Each shape is a Wikipedia page, some English, some Chinese and some in common: they are linked to each other based on their see also section. Then, we clusterized all the pages into semantic categories to better understand the macro arguments around our big theme. Every color is a different cluster and the shapes’ dimension represents the average of the 2018 views, the number of see also and references and the length of the page.


example of protocol

Defined the seed Social Credit System, we used the Seealsology tool to find the correlated pages, setting the distance on 2. Since the tool didn’t work with the Chinese counterpart, we manually listed the Chinese see also pages, always at a distance 2. We read all pages and we categorized them based on what they spoke about. As we wanted to design a network visualization, we used at first the tool Gephi to better see the connections; also Raw Graph was useful to set the dimension of the shapes. Then we combined and reworked them with Illustrator.


Data Source: Wikipedia
Timestamp: 01/12/2018
View Data (500Kb)

We divided the excel file in multiple sheets to split the English and Chinese research and also the connections and the pages. In the connection sheets we have the see also pages referred to each page and in the pages sheet we have all the information regarding the pages, including the clusters that we created.