I don’t put much stock in lists and ‘best of …’ rankings as they rarely tell you the methodology behind the system. When Antonio Santo (@akwyz) shared a list of the top 50 influencers on ‘the future of work’, I asked about the methodology. Vishal Mishra, CEO of Right Relevance, kindly obliged.
“The Right Relevance score of an influencer for a TOPIC represents the authority within the social community for that topic, say for e.g. ‘machine learning’, of that influencer. It is a normalized score ranging from 10 to 100. This numeric influence is then inductively applied to the topical content curated by that individual for measuring relevance.
The process is fully algorithmic and leverages ML, semantic analysis and NLP on unstructured data at scale. It is primarily graph based and involves performing a 2-level proprietary people rank”
—Influencers Topic Scores & Rankings
I use Twitter as a medium to teach people how to find experts and how to build a knowledge network. This is a core part of my PKM Workshop. Understanding the algorithms behind search results and rankings is an important network era literacy, and I am glad that Right Relevance (RR) shares some of this.
“Measuring influence is not deterministic. It’s a fairly subjective task with numerous different methodologies and is generally ephemeral in nature. Using graph theory, machine learning and natural language processing, RR discovers how people congregate to form communities that share common interests, within the context of an event (or topic or trend). We also determine influence within those communities, along longer and shorter timelines. At Right Relevance, we measure influence in 2 distinct ways:
‘topical influence’ or Tribes by measuring the quality of network connections within the context of a ‘topic’ and,
‘engagement influence’ or Flocks by measuring quality and quantity of engagements (RTs, mentions, replies), reach of tweets, connections etc. within the context of an event or trend.”
—Relevance as a Service
The RR service also includes visualization of various networks, and I believe this is extremely valuable, as I have noted before. Visualization, and new metaphors, are essential for systemic change to happen. They give us new ways to describe and discuss phenomena. In business, visualizing network relationships can give the initial leverage of getting complex new ideas accepted into general management thinking.
Here is the what the Right Relevance algorithm produced on who has influence, on Twitter, on the topic of ‘the future of work’.