Most Influential Brands in Industrial Internet of Things and Smart Cities by Right Relevance

Right Relevance (RR) provides curated information and intelligence on ~50 thousand topics.

This includes:
Topic relationships including related topics & semantic information like synonyms.
Topical influencers (~2.5M) with score and rank.
Topical content and information in the form of articles, videos and conversations.

Additionally, Right Relevance provides an Insights offering that combines the above Topics and Influencers information with real time conversations to provide actionable intelligence with visualizations to enable decision making. The Insights service is applicable to events like elections, emerging technologies, issues/activism, conferences, product launches etc.

This report is a summary of graph analysis of engagements and conversations including retweets, mentions and replies of tweets related to the subject of ‘Industrial IoT’.

Data & Duration
The report leverages tweets sampled from March 1st to March 31st 2017 and along with Right Relevance topics, topical communities’ and articles data form the basis for the analysis.
The phrase used for gathering tweets is “iiot”.
Most of the summary report is extracted from the analysis collateral in the form of:

Tableau Online Dashboard : Visualizes graph analysis results via charts and tables. Insights include flocks, top trending terms, top hashtags, top Users/accounts, RR topics, top tweets and several other measures. Faceting is supported per flock, RR topic and Twitter/RR account.
Gephi Communities Graph Visual: Extracts are shown below.

IIoT Communities Graph
Community detection graph algorithms like Walktrap and InfoMap are used to identify communities (as sub-graphs) in our engagements graph built using Neo4j & R. Graph visualizations are done via Gephi.
The all engagements graph (Fig 1), which includes mentions, is fairly dispersed with several small communities around large industry players like GE, IBM, Cisco, Intel, Bosch, Schneider Electric etc. along with a couple of dense engagement areas invoving analysts, thought leaders, IoT/IIoT publishers, news curators etc.

Graphs shows:
One high engagements area (in Purple) leading to a community around accounts that are mostly industry analysts, thought leaders (organic or via personal branding), publishers, news curators etc. Bill McCabe ( @IoTRecruiting ), IoT ONE ( @IotoneHQ ), ipfconline ( @ipfconline1 ), CB Insights ( @CBinsights ), Evan Kirstel ( @evankirstel ), Mike Quindazzi ( @MikeQuindazzi ) form part of that community.
Reasonably well engaged community (in Blue) centred around @ThingsEXPO ( @ThingsExpo ) and CloudEXPO ( @CloudExpo ) conferences.

Several smaller communities around large industry players in IoT & IIoT like GE, IBM etc.

Two of the most engaged and interesting accounts are Bill McCabe ( @IoTRecruiting ) and Marc R Gagne MAPP ( @OttLegalRebels ).
@IoTRecruiting looks like a successful personal branding effort in the IoT/IIoT space specifically applied to recruiting. This account forms the heart of the most engaged community in the graph and has the highest influence score by several measures including PageRank.
The account posts/shares/RTs some of the most relevant content with high engagements and has built real influence with high Right Relevance influence scores.

On the other hand, @OttLegalRebels , shows high engagements too but with bot-like characteristics and has been self organized to the outside of the graph. Almost all 1st degree engagements are due to a single tweet below (Fig 4) focused on privacy considerations in smart cities. Large number of posts are RTs at a high scale with little real influence value. Bot-like scale behavior mixed with some valuable content has helped the account build reasonable mindshare in IIoT.

Top Themes
Latent Dirichlet allocation (LDA) based text analysis of the tweets is used for identifying high value trending terms.