Online content and information quality analysts

Avram Turing  is a non-partisan research-driven organization of analysts

We rate, label and summarize the information quality of trending/viral online content.

Through our research, in 2021, we coined two new concepts

“non-information” and “off-information”

and introduced them to the international research community and the information quality analysis body of knowledge and elaborated in our book Misinformation Matters: Online Content and Quality Analysis (Taylor & Francis)

Book Description:

What is ‘misinformation’? Why does it matter? How does it spread on the internet, especially on social media platforms? What can we do to counteract the worst of its effects? Can we counteract its effects now that it is ubiquitous? These are the questions we answer in this book. We are living in an information age (specifically an ‘algorithmic age’) which prioritises information quantity over quality. Social media has brought together online billions of people from across the world and the impact of diverse platforms, such as Facebook, WeChat, Reddit, LinkedIn, Signal, WhatsApp, Gab, Instagram, Telegram, Snapchat, has been transformational.

The internet was created, with the best of intentions, as an online space where written content could be created, consumed and diffused without any real intermediary. This empowering aspect of the web is still, mostly, a force for good. People, on the whole, are better informed and online discussion is more inclusive because barriers to participation are reduced. As activity online has grown, however, an expanding catalogue of research reveals a darker side to social media, and the internet generally. Namely, misinformation’s ability to negatively influence our behaviour both online and offline.

The solution we provide to this growing dilemma is informed by Ludwig Wittgenstein’s Tractatus Logico-Philosophicus, which examines the relationship between language and reality from a philosophical perspective, and complements Claude Shannon’s Information Quantity Theory, which addresses the quantification, storage, and communication of digital information from a mathematical perspective. The book ends by setting out a model designed by us: a ‘Wittgensteinian’ approach to information quality. It defines content published online by clarifying the propositions and claims made within it. Our model’s online information quality checklist allows users to effectively analyse the quality of trending online content. This approach to misinformation analysis and prevention has been designed to be both easy to use and pragmatic. It upholds freedom of speech online while using the ‘harm principle’ to categorise problematic content.

Our book can be purchased with a discount at our publisher's website, click here: Routledge

We were pleasantly surprised to find that our approach to online content rating and ranking is in line with the solution proposed in 2019 by Dr Stephen Wolfram to the U.S. Senate Subcommittee Hearing on Communication, Technology, Innovation and the Internet.

This expert testimony validates our approach to online content ranking

The above video is a compilation of some of Dr Stephen Wolfram's responses in the U.S. Senate Hearing "Optimizing for Engagement: Understanding the Use of Persuasive Technology on Internet Platforms." The Hearing examined how algorithmic decision-making and machine learning on internet platforms might be influencing the public.

partner with us / collaborate with us / contact us: click here

ContentQual® our startup will deploy digital technology for online misinformation prevention

a consumer-facing/content-focused online platform/app/Web browser extension,

helps to amplify high quality content circulating online

and add friction to low quality/misinformation (slow down/reduce the sharing)

which helps to strengthen the credibility of authentic online content producers and online news media by this signal of trustworthiness

We also produce research reports, academic papers, opinion articles

and we conduct online misinformation prevention training