Where Web Content Meets True Network Intelligence

An essay on the future of information networks and ‘socialized’ media…

Introduction

It might seem a bit odd for a two-and-a-half year old startup to be talking about its next generation platform like a web mythology, but that’s more or less what we’ve experienced at Faveeo. If you’re paying even casual attention to economic and geopolitical events as of late, a lot is going on in the world at the moment, and big shifts are happening that are already affecting how we live and work. This also impacts how we relate to, and interact with, online information.

That said, this is not an attempt to glorify our product suite per se, nor an effort to tell you how great our platform is. Virtually all startups make big bets based on their powers to disrupt, or their ability to scale, and/or how they navigate through their valuation strategies.

We’re in a pretty crowded space with plenty of competition, so instead of highlighting an array of features and functions, we’re here to articulate our vision.

It’s a big one. And it needs to be.

But don’t take this as hubris — you’re a big part of it. In fact, you’re driving it, whether you’re fully aware of it or not. We sincerely hope you seize the big shifts that we see.

For those of you who are unfamiliar with Faveeo as a platform, we provide three main things for global businesses and large non-profit organizations:

  • Search & content discovery capability for any type of information indexed on the web (think if Google or Yahoo! had search free of ads and editorial biases)
  • Community curation for influencers across any topic of interest domain, to include advanced search as well as intricate feedback loops (think of this as ‘bottom up’ or ‘emergent’ artificial intelligence matched with collective or group intelligence)
  • Publishing & distribution capability in the form of well-designed and branded digital magazines (think of Paper.li or ScoopIt for enterprises and with built-in advanced search & curatorial functions)

Behind this are also some unique data and content analytics capabilities; we are one of ten global partners in DataSift’s Facebook audience segmentation program, and we also have unique relationships with Twitter and LexusNexus. As well, we have been actively developing our NLP (natural language processing) capabilities with a world-class team out of EPFL (École polytechnique fédérale de Lausanne) near our headquarters in Lausanne, Switzerland.

Towards a More Open Network Stack

The enterprise software space — SaaS in particular — is an interesting one because it’s crowded, yet there are massive gaps in terms of what companies and industries need. While most software providers (our competitors) focus on features and functions, we’re honing in on brand and industrial processes with our customers and partners, whereby our platform is a true extension arm of these businesses. The reality of SaaS technologies right now is that no one platform fits all, nor do customers tend to lean on a single platform to address a particular need, or set of needs.

In technical terms, developers like to think of these capabilities in stacks. So think of what we do as a ‘network stack’ with really effective business and organizational applications.

Here’s exactly what we mean by this.

Global NGOs are redefining what philanthropy and the nature of donations mean, and therefore we are tasked with helping them discover how research changes the fund-raising process.

Global brands are hiring less and less agencies to do their marketing, advertising and outreach for them, and are instead exploring the intersections of journalism and community-building. We’re helping them get there, not only by curating and automating some of these processes, but also by showing them how to operationalize these efforts as new revenue centers.

eCommerce is even more interesting: Another powerhouse that spends roughly a billion dollars a year on digital marketing (yes, with a “B”) has said that it wants to streamline spending and turn buying into the ultimate information utility. It’s not interested in ‘content marketing’ or ‘social outreach’ so much as it is in actually investing in networks of people that can bundle its products with the power of highly resonant, opt-in customer information, be it through blogs, editorials, or comment threads.

Other industries such as banking have found that online discovery is enabling them to not only redefine their customer relationships, but on the institutional side, it is illuminating new opportunities to look at markets differently, hence affecting the ways they invest in and develop financial products.

The elements driving these discoveries aren’t anything new, of course. Innovations in social technology, digital content and analytics abound. However, what’s changed are the behaviors and interests of people (customers and value chain partners) such that the composition of online networks and the intelligence we can gain from them is literally transforming business… And we don’t mean this in the context of buzz terms like ‘social business’ or ‘social selling’ or ‘omnichannel marketing’.

Also note a fundamental operator in all of this: participation.

While automated functions have all but become choix du jour for companies and organizations in their quests to streamline normative operations, these same operators have also recognized that the way to create new, sustainable revenue models is by collaborating with a diverse array of domain experts and customers. Not only that, if you look at company or organizational operations themselves, you will also notice how hybridized and interconnected they are becoming, despite all of the preexisting silos.

Yes, ‘social business’ pundits have sung the praises of online and interdepartmental communications, but this is much bigger than that — this is about stakeholder participation that transcends industry silos to actually prototype solutions, conduct product or market experiments and design openly.

Hence the notion of networked intelligence.

Truth is, when businesses and industries are networked, and the intelligence they offer can be clearly curated, amplified and rebundled, content becomes the ultimate information utility. This level of utility also serves as an adaptive point of distribution and purchasing. As far as intelligence itself goes, this changes how we curate, how we tell stories authentically, and how data become more dimensionalized or layered. It also shows the multi-way connections people forge through content as they literally become the media we tap into while information moves across networks.

The idea that ‘people are media’ is more resonant than ever before, as evidenced by the increasing power of online communities, as well as a slew of new niche social networks.

Does this mean that social networking platforms like Facebook are being replaced? Not necessarily. It does mean, however, that instead of being platform-centric in our business and communications strategies, we need to be more and more agnostic and behavior-centric in how we observe people interacting with media across networks. The value of mobile adoption, for example, isn’t just the fact that you can consume and share content more easily, it’s the fact that your behaviors enable you to more intimately participate with that information. We’ve certainly seen elements of this with apps, but now the shift is pointing towards a whole new kind of networked intelligence, which in turn is creating more regenerative and combinatorial forms of media… what we like to call socialized media.

The (re)Birth of Truly Socialized & Democratized Media

Let’s explore this (r)evolution of socialized media, starting with the data pieces.

First, it is important to recognize that data constructs are getting smarter, between what we consider to be ‘big’ (more automated and quantitative) and what we consider to be ‘small’ (more curated and qualitative).

As we’ve encountered in our own client and partner work, we are now striking a nice balance between ‘big’ and ‘small’ such that what we see in our data gathering and what we can match up is getting more elegant, more streamlined. In this way, we can more effectively help analysts and analytical teams get to richer insight(s), knowing that the proxies, metrics and benchmarks vary and constantly change per the media, business or market environment.

From these profound shifts in data, we can now look at the ‘smart content opportunity’. Here, we can observe how ‘small’ constructs aligning content, communities and co-curation bring networks together more seamlessly. In the process of ‘making and matching’ up these smaller, niche groups, new measurement constructs emerge that result in meta dynamics (the ways in which information flows between content and communities), micro dynamics (the ways in which information flows between communities and specific curators), and mesa dynamics (the ways in which information flows between curators and how context emerges).

What’s especially important to note here is the inclusion of multiple network profiles, along with an array of data approaches. There has been a tendency in social technology and big data circles to promote ‘one size fits all’ approaches, or to advocate for one approach versus another (reductionism versus emergence), or to rely heavily on one form of intelligence (‘artificial’ versus ‘collective’). As we transition from an Internet of objects, to a web of entities and more open and adaptive protocols, the composition of networks changes, which means that all approaches must be considered as we decide what might be appropriate for a particular media ecosystem, or information ecology (‘infocology’).

Which leads us now to the composition of networks themselves, and what we believe constitutes the development of a real network graph — the measuring stick for productive and prosperous info-futures.

Currently, the Internet and the social web is primarily composed of what our colleague Simon Robinson has coined as ‘knotworks’, which are top-down, pyramidal, more command-and-control networks predicated on the more traditional concepts around ownership, as well as funneling people and information into specific domains. Knotworks reflect the inadequacies of our current economic system, which is also why so many media, journalism and advertising models struggle to provide value to customers and end users.

Google is a prime example of a knotwork: Its core search engine has significant editorial and advertising biases, and its new page ranking algorithm preselects what content it deems to be ‘relevant’ or ‘appropriate’. While we have tremendous respect for Google, we feel that a truly democratized web must move well past this, and offer significant alternatives as to how information is gathered, sorted and shared.

Here’s the good news: As more and more ‘microplayers’ enter the mix (content platforms, apps and niche social networks), web protocols are being rewritten. Further, as more and more vertical businesses ‘horizontalize’, the more software development takes on versions of the network stack. GE’s recent position as a tried-and-true software company is just one glaring example of this shift. More importantly, this challenges the traditional notions of ownership, rights management, licensing and verticality with respect to business and operational functions.

So, as networks become more co-ownership led, and content/data is rebundled, both programming and business protocols change. Big players like Cisco, IBM and SAP have already made significant investments in this emerging idea of networks, affecting everything from their IoT platforms, to telepresence, to mesh networking and quantum computing. Other players like Expedia and Yahoo! are completely revisiting their publisher network models, realizing that they can at once offset infrastructural costs, mitigate risk, and create new revenue centers that don’t have to include elements like advertising.

As these networks continue to evolve, information systems will enter what we call ‘knitworks’. These are more ecologically- or infocologically-minded networks that can wholly integrate with other systems through select APIs and network stacks, and which navigate through different network archetypes.

This essentially means that what we write, what we program and what we (re)distribute will encounter unprecedented alignments, which will in turn enable new information models. Knitworking itself will take on new behaviors between platforms, people and places, and will reveal to us the behavioral attributes of new markets as they emerge or evolve… Very different from what we’ve experienced to date.

Whereas previously the x/y axes of space and time were confounding to grasp in terms of how to scale, manage and/or control information systems, we can now look at how knitworks produce the kind of data + content constructs that measure how we move between nodes (people), across networks and within nodes and networks. We believe that mesadata will create a whole new breed of curator, one who can better self-manage, self-distribute and redistribute information.

Most importantly, it will align the attributes of time and trust by transcending the online and physical spaces in which people interact.

The Shift from Content Search to Context Serendipity

Now that we can envision an incredibly bright info-future, it is equally important to observe what it will take at a macro level to transform our information systems.

To reiterate, the knotworking of the ‘Web 2.0’ era dealt with a widening of various data/content graphs, such that signal noise became almost unbearable. The response by platforms such as Facebook and Twitter has been to ‘mute’ the noise through filtering. Countering this has been the uptick in curation, but unfortunately, AI technologies have largely superseded human input, thus affecting quality and relevancy.

As curation grows, the ‘Web 3.0’ era is showing us that niche communities, en masse, have a definitive as well as sustainable place at the content table. This of course challenges more mainstream methods of producing content and measuring its value, but has also significantly called into question the ways we manage data, how we look at privacy, and how we can manage our information streams more distributively. As writers and readers are pitted against one another through largely ineffective impressions-based models, we are also seeing a shift in how we can monetize and distribute information more equitably.

Rebundling (a Marc Andreessen term) is facilitating the shift into knitworks. This is monumental because it is inviting a return to ‘niche’ perspectives, and is giving the ‘unheard voices’ a chance to mold and balance out public opinion in fantastic ways. As many of the top publications like the New York Times run pieces that read like fairly lopsided op-eds rather than the more contextually balanced perspectives you might find in The New York Review of Books, commenters will have more and more power over the flow of information, even if they face more and more censorship challenges. This is because of rebundles and the stacks they represent — niche will ultimately overpower mass.

Monetizing & Balancing Out the Intersections Between Domains & Disciplines

Coming full circle, let’s look at how and where the rubber meets the road with respect to our info-futures.

As we touched upon earlier, companies and organizations are now completely changing their business models as they interact with the supply chain and manufacturing ecosystems in which they play. This of course, changes their information systems, aligning with the disciplines and functions of how they operate.

The operation of participating literally creates new operational functions. We can ascribe different terminology to these functions, but at the end of the day, the companies that ‘win’ will be those that can identify the relationships between these functions, take into consideration their interdependencies, and then collaborate as value chain stakeholders to develop emergent models. Emergent models — not static, fixed or non-adapative ones — are what differentiate leading businesses and organizations by enabling them to blaze their own media and informational trails.

A more obvious intersection is the one between journalism and advertising; as brands, for example, build in-house ‘content engines’, the real struggle is to get information, and specifically information about products, in the hands and hearts of customers independently of onslaughts of messaging. Concurrently, it is now the responsibility of brands — if they wish to build their own media ecosystems at network scale — to disrupt outdated compensation models so that journalists and other storytellers can continue to deliver high-quality, highly resonant content to the right audiences at the right times, in the right places. As evidenced by the shifts in mobility, we are no longer reaching audiences in a single location or point of entry, but rather in the places and spaces of their choosing, on their terms.

As digital marketing, search and publishing disciplines evolve and ‘horizontalize’, we can see other fascinating, participatory intersections. What happens next moves us well beyond the territory of buzzwords, and into realms where we can literally discover, target, rebundle and redistribute with incredible accuracy, authenticity and intentionality.

Putting Advanced Theory into Real-Time Practice

Now would be a good time to introduce Faveeo’s latest product, called Horizons. Horizons is a great example of a network-centric tool that streamlines the time and effort it normally takes to understand, contextually, what trends, memes and/or other cultural phenomenon actually mean to businesses and organizations.

At the macro level, we see Horizons as a gateway to building renewed trust within online information networks, as well as an opportunity to literally rewrite the web, free of advertising and media biases. To amplify some of the points mentioned earlier, our own clients and partners — among the biggest in the world, with very formidable information and media footprints — are all seeking alternative models in order to better connect with their customers and to build products and services that meet acute needs in the marketplace.

Ongoing, Open Questions

The network graph is not just a measurement construct, a programming protocol or an analytics model, it is a way of seeing the world of online information with open eyes.

As the trifecta of social publishing, networked intelligence and contextual insight brings organizations of all types into new revenue and civic realities, as well as the individuals and groups playing roles within them, we are tasked with developing a very different kind of awareness around what’s possible with our media ecosystems.

As Plato once said: “Good actions give strength to ourselves and inspire good actions in others.”

Alas, this can be applied to our uses of media, in liberating our information systems, and in treating our online (and offline) interactions as the ultimate forms of social currency.

Here’s to our info-futures.

As always, thanks for reading.

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Author’s note: I am the lead technology advisor to Faveeo, and spent the last two years as its acting CIO. I am now a partner at Exile and Exile Holdings, which is developing people + platforms to create widespread social and ecological change.