We’ve all heard the term Knowledge Graph. Now, a new study has been released from faberNovel that puts the spotlight on LinkedIn and how it is “silently drawing what might be the first global economic graph.”
faberNovel’s LinkedIn, The Serious Network (June 2013) features the quote by LinkedIn CEO Jeff Weiner of the platform’s ambitions to develop the world’s first economic graph: “We want to digitally map the global economy, identifying the connections between people, jobs, skills, companies and professional knowledge – and spot in real time the trends pointing to economic opportunities.”
It’s already gone far in this direction. How? As Daniel Tunkelang, who now leads LinkedIn’s efforts around query understanding, last year explained at SemTechBiz West, “the sweet spot is in the semi-structured [data] space.”
And if there’s one thing that LinkedIn has a lot of, it is semi-structured data: free-text descriptive profile text; marked-up (but typically incomplete and ambiguous) statements of employment, education, promotion etc; and (also typically incomplete) graph data representing the relationships between people and roles.
“More data beats clever algorithms, but better data beats more data,” said Tunkelang, whose role at LinkedIn at the time was as principal data scientist.
That better data informing LinkedIn’s Professional Graph, along with clever algorithms, is doing its part to turn LinkedIn into the best-valued social network. The faberNovel report says LinkedIn boasts two new members every second; as of May, that totaled 225 million people globally. Some 75,000 developers use its APIs, and the network’s involvement in B2B interactions thanks to those APIs, faberNovel writes, means that LinkedIn continually learns more about its members. At ten years old, the company is worth $20 billion, at a valuation of $81 per member; its closest networking rival, Facebook, has a $52 value per member, the report says.
Users – members, marketers, recruiters and business partners – reap value through fast and mastered product development, it says, citing as examples services like talent pipeline management for recruiters, which relies on matching algorithms and graph validation of referrals and skills for the candidate management process. Other new services its graph data is driving, faberNovel notes, include giving sales reps the ability to search it for qualified leads, and a mini-CRM and API for them to integrate the graph into their CRM clients. That’s good for the reps, but also good for LinkedIn. A corporate sales solution, the report says, will get LinkedIn into the $25 billion CRM (customer relationship management) market.
The report surveys LinkedIn’s current ambitions in becoming the first social platform for professional publishing and content promotion. But, it expects, that’s just the start, with its future ambitions around mapping the new economy revolving around allowing transactional interactions to create and augment the Business Graph. It could be the marketplace for business or the founding pillar of the graph-based app market, faberNovel speculates.
As its data expands to encompass more and more of the 3.3 billion strong global workforce, more companies and more transactions, its data and algorithms, faberNovel says, could enable LinkedIn to:
Says faberNovel, we’re looking at “the key, sprawling business tool for the New Economy.”