ContentQual® is Avram Turing’s Startup: a website that curates trending content found in the World Wide Web (Web), amplifying quality content and adding friction to low quality content.
Users can browse summaries of trending articles and see links to the full content on the Web. Articles are sorted based on our score (rating) or our label of the content. ContentQual analyses content using Avram Turing’s Global-OAQ® process, a hypothesis-driven online intervention.
The Global-OAQ is a system (and method) for online content analysis, a descriptive tool. Web-based information (articles, commentary etc.) is analysed then scored based on criteria designed to evaluate the quality of analytical content. Content is then categorised as ‘analytical’ /‘non-analytical’ or ‘un-analysable’. Further labelling of the intrinsic nature of the content (e.g. ‘satire’ ‘political’ ‘scientific’) and users’ (content consumers) ratings completes the process. When applied to Web browsers and online social media platforms the rating produced by the Global-OAQ can help users discern quality content and engage more analytically with other users.
At the heart of the Global-OAQ solution is the belief that analytical thinking is essential to combating information disorder and the lure of echo chambers, while upholding freedom of speech
All online content can be classified as ‘analytical’ or ‘non-analytical’ based on a list of criteria which include but are not limited to the following:
- Are any claims made in the content supported by evidence or are the claims obvious or easily verifiable?
- Does the content display logical steps in thinking and reasoning?
- Is the content free of bias and prejudice: what Dewey  describes as “prejudgements, not judgements proper that rest upon a survey of evidence”?
- Where would arguments presented in the content be placed in Graham’s disagreement hierarchy ?
- Does the content lean towards conspiratorial or conventional thinking as described by Lewandowsky and Cook ?
Monthly trending content on the web (articles, speeches, tweets etc.) are researched by Avram Turing’s analysts and posted on the Global-OAQ’s website called ContentQual. All analysed content is scored between 0.0 (not analytical) and 10.0 (highly analytical) then assigned colour-coded badges. Scores between 0.0-3.9 have dark grey badges, scores between 4.0-6.9 light grey and 7.0-10.0 scores have clear badges. All content is further categorized and labelled to describe the intrinsic nature of the content.
Figure 1: Examples of analytical score badges and category labels of online content
Consumers of content are given the opportunity to rate content already analysed on the ContentQual website. In addition to the analytical score and content categorization (labelling), users are asked the following questions concerning the content:
“Regardless of whether you agree or not with what is written here, please rate this content in terms of quality of content. Could you cite this content in any discussion? Please rate from * (poor quality) to ***** (recommended reading)”
The average users rating for each content is displayed beside the analytical score and category label. On the ContentQual website, users can browse analysed content and sort them. Content can be sorted by score (higher scoring content at the top) or by general categories (clicking on ‘political’ lists all trending political content). Users can also suggest other trending content to be analysed and included on the site.
The 50 trending content selected from the Web will be analysed monthly and posted on the ContentQual website. The website serves as the database of analysed content for licensed applications to web browsers and social media platforms. Web browser extensions offered to users will show the analytical rating of a trending article, tweet or other content once a link to the content is accessed. Search engines will display search results that include a score for any trending content found in the search results. Users of social media platforms like Facebook, Twitter etc. will see the Global-OAQ score of trending content posted on their newsfeeds.
Figure 2: Graham’s disagreement hierarchy 
Figure 3: Conventional vs conspiratorial thinking 
The Global-OAQ system is another tool to help improve the quality of content that people are exposed to online. It is a descriptive tool. It builds upon existing tools that fact-check content shared online to provide a more nuanced and in-depth examination of content. Rather than a free-for-all approach or outright censoring of content, the Global-OAQ takes a middle road that informs the user of the analytical quality of content. A user could use her own discretion and decide one day that she will only read content with a rating > 7.0 and avoid all ‘political’ content, but next day focus on ‘social commentary’ with ratings >3.0. The likelihood of being misinformed, disinformed or malinformed is greatly reduced due the scoring and labelling system of the Global-OAQ.
The Global-OAQ can improve the quality of discourse and interaction between consumers of online content. Regular use of the Global-OAQ tool will empower users to scrutinize the level of analytical quality of content they read, watch, and listen to (online or through other media like radio and television). Person-to-person discussions would also be greatly improved too. Our hope is that this will help enable people to keep talking and (politely!) arguing with one another, allowing them to better find areas of common ground on which to begin building relationships and ways of working together.
 Dewey, J. 1910. How We Think. D.C. Heath & Co., Boston. https://www.gutenberg.org/files/37423/37423-h/37423-h.htm#Page_40. Cited in Popova, M. 2014. “How We Think: John Dewey on the Art of Reflection and Fruitful Curiosity in an Age of Instant Opinions and Information Overload.” https://www.brainpickings.org/2014/08/18/how-we-think-john-dewey/  Graham, P. 2008. “How to Disagree.” http://www.paulgraham.com/disagree.html  Lewandowsky, S and Cook, J. 2020. “The Conspiracy Theory Handbook.” http://sks.to/conspiracy