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RightRelevance, founded by  Vishal Mishra and Sumit Taank in 2013, is a company which leverages the social web and Big Data graph analytics to find key topics and influencers. It offers an effective way to search and discover relevant content for thousands of topics, from Big Data to cough medicine.

I recently got a nice demo from Vishal who explained how it works.

Their vision is to create a new category - Relevance As A Service.

RightRelevance mines the social web to identify and rank topical influencers. They looked at multiple sources but currently are primarily using Twitter and Wikipedia because both are public. The inherent trust of the influencers communities is then applied to finding the most relevant articles and conversations.  The global list of topic and global influencer graph are tagged and then partitioned according to topics into communities.  Then influence is recomputed within each topic.

Fig. 1: Right Relevance Information search via trusted influencer communities

This approach is much more useful than Klout which gives a single number regardless of the topic.  For example Justin Bieber has Klout of 92 and KDnuggets has Klout of 69 but you would not rely on Justin Bieber for Data Science advice or on my advice in popular music.

You can search RightRelevance (abbreviated as RR below) for topics - it has many thousands covered - and it gives you a list top articles, influencers, and conversations.

For example, for Big Data RR finds 2885 influencers (note: the RR, twitter, and influence numbers below are given as of end of July 2015)

RR also automatically finds a very good collection of topics related to Big Data:

Data Science, Data Analysis, Data Visualization, Business Intelligence, Data Mining, Cloud Computing, Apache Hadoop, Open Data, Machine Learning.

RR also gives a geographic map of influencers - Fig 2. is a snapshot of US Map.

Fig. 2: Right Relevance Map of US Big Data Influencers

and below are top 10 cities for Big Data influencers.  Not surprisingly, San Francisco leads, but note the 2nd place of New York City and 3rd place of Washington, DC.  However, RR seems to lack coverage in Asia - we don't see any influencers on its map in India , China, or Australia.

Table 1. Top Cities for Big Data Influencers

For each influencer, RR also gives their twitter bio and 5 other topics where that person is most influential, for example here is my page

Next, we look at the top 20 influencers for Big Data