This report is an example of the deep insight reports that Right Relevance builds with graph analysis of social engagements and social conversations including retweets, mentions and replies of tweets related to the subject of ‘Industrial IoT’.
Right Relevance (RR) provides curated information and intelligence on ~50 thousand topics.
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.
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:
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.
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.
Latent Dirichlet allocation (LDA) based text analysis of the tweets is used for identifying high value trending terms. These along with hashtags and Right Relevance topics form the basis for identifying top conversation themes during the analysis timeframe.
The top trending terms, hashtags and RR topics list brings out the following as top themes around IIoT (and broader IoT space).
Using RR topics facet in Tableau is a great way to pinpoint the top accounts connected to a given conversation theme linked with IIoT. The top accounts for ‘artificial intelligence’, ‘manufacturing industry’ and ‘smart cities’ related to IIoT are outlined below.
The top ‘AI — IIoT’ conversation related accounts are Bill McCabe (@IoTRecruiting), IIConsortium (@IIConsortium), TechNative (@TechNative), Kirk Borne (@KirkDBorne) and Prashant | AI (@Prashant_1722) among others.
The top ‘Manufacturing Industry — IIoT‘ conversation related accounts are IIConsortium (@IIConsortium), GE Digital (@GE_Digital), Wind River (@WindRiver), PTC (@PTC), Ford Motor Company (@Ford), Siemens Industry (@siemensindustry), KUKA Robotics (@KUKA_RoboticsEN), Honeywell Process (@HWusers) among others.
The top ‘Smart Cities — IIoT‘ conversation related accounts are ThingsExpo (@ThingsExpo), IIConsortium (@IIConsortium), Scott Amyx (@AmyxIoT), Duane Baker (@DBaker007) and IBM Watson IoT (@IBMIoT).
More themes will be explored as part of the flock analysis later in the report.
