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Top LinkedIn Groups for Analytics, Big Data, Data Mining, and Data Science – Discussions up, Engagement down


While discussions are growing, the comments and engagements are falling, especially since 2012. We cluster groups into 4 quadrants by activity level and identify most active and engaged groups. Open groups are twice as active as closed.



We continue our analysis of Top LinkedIn Groups for Analytics, Big Data, Data Mining, and Data Science. Last month we examined growth from groups "Big Bang" in 2008 to present and in this part we look at activity - comments, discussions, and engagement.

4 quadrants of linkedin groups Our key findings
  • as groups grow, discussions increase, comments decline - surprisingly even in absolute numbers (!)
  • engagement (comments/discussions) slows down
  • Open groups are twice as active, in both comments and discussions
  • We identify 4 group quadrants (see below): Active, Commenting, Posting, Passive
  • Most active groups: KDnuggets,
    Data Scientists,
    Data Science & Machine Learning,
    Big Data and Analytics,
    RDataMining

 
Next chart shows comments and discussions per group, for each 12 months period, from Q2 2009 to Q1 2015.

Top Linkedin Analytics, Big Data Groups 2009-2015 Comments and Discussions
Fig. 1: Top LinkedIn Analytics, Big Data, Data Mining, Data Science Groups,
Comments & Discussions per year, 2009 to 2015


We note that while the total number of discussions is growing, the total number of comments actually started to decline in 2013, despite the growth in membership. The big gap between the average and the median values shows the wide range in activity levels between the groups.

We can see the trends more clearly if we measure the comments and discussions per week and per 1000 members.

Top Linkedin Analytics, Big Data Groups 2009-2015 Activity Per 1000 Members
Fig. 2: Top LinkedIn Analytics, Big Data, Data Mining, Data Science Groups,
Comments & Discussions per week per 1000 members


Note that LinkedIn group statistics only give discussion counts starting around June 2010, while comment counts are available starting from Sep 2008.

The discussion numbers per member were growing and peaked in 2012, with the launch of 2nd cluster of Big Data groups in 2012 (some of them were very active), but both discussions and activity levels are declining after 2012.

An important factor is group openness. 20 of the top 35 groups are open, and open groups have over twice as many comments (median 0.59) and discussions (median 1.61) as closed groups.

Top Linkedin Groups 2015 Open Closed
Fig. 3: Top LinkedIn Analytics, Big Data, Data Mining, Data Science Groups,
Open vs Closed groups Comments, Discussions/week per 1000 members, 14Q2 to 15Q1


Here are the 10 groups with the most comments per 1000 members per week in 12 months from 2014 Q2 to 2015 Q1.

Groups with most comments/week per 1000 members
  • RDataMining: R and Data Mining, open, 2.31
  • Data Scientists, open, 1.38
  • KDnuggets Analytics, Data Mining, and Data Science, open, 1.34
  • Big Data, Analytics, Hadoop, NoSQL & Cloud Computing, open, 1.24
  • Statistics & Analytics Consultants Group, (closed), 1.02
  • Advanced Business Analytics, Data Mining and Predictive Mode, open, 0.83
  • Big Data and Analytics, closed, 0.80
  • Next Gen Market Research (NGMR), open, 0.80
  • Text Analytics, open, 0.76
  • Data Science & Machine Learning, open, 0.74

 
Graphing comments levels for all groups shows an overall decline in levels of comments.

And here are the 10 groups with the highest discussions levels per 1000 members per week in 12 months from 2014 Q2 to 2015 Q1.

Groups with most discussions/week per 1000 members
  • KDnuggets Analytics, Data Mining, and Data Science, open, 8.86
  • Data Scientists, open, 6.66
  • IBM Big Data and Analytics, open, 4.54
  • Data Science & Machine Learning, open, 4.39
  • Predictive Analytics Network , open, 3.61
  • BIG DATA Professionals - Architects Scientists IOT Analytics, open, 3.41
  • Data & Text Analytics Professionals , open, 3.21
  • Big Data and Analytics, closed, 2.86
  • Data Mining, Statistics, Big Data, and Data Visualization, open, 2.74
  • Business Analytics, open, 2.48

 
Next graph shows the wild nature of discussions for different groups, going as high as 20/week per 1k members in 2012 for BDAHN (Big Data, Analytics, Hadoop, NoSQL & Cloud Computing) group, but declining for most groups. See all group abbreviations in the table at the end of this post.

Top LinkedIn Groups, 2009-2015, Discussions/week, per 1000 Members
Fig. 4: Top LinkedIn Analytics, Big Data, Data Mining, Data Science Groups,
Discussions per week per 1000 members, 2009 to 2015


We can measure group member engagement as the number of comments per week divided by the number of discussions per week (note that per 1000 member factor cancels out).

Top Linkedin Analytics, Big Data Groups, 2009-2015, Engagement per week
Fig. 5: Top LinkedIn Analytics, Big Data, Data Mining, Data Science Groups,
Average Engagement per week


Overall, the average engagement across all groups has declined two-fold from 2.16 in Q2 2010 to 1.03 in Q1 2015, and median engagement declined six-fold from 1.33 to 0.21. This suggest a number of very active groups which stand out.

Here are the 10 groups with the highest engagement levels in in 12 months from 2014 Q2 to 2015 Q1. We note however that groups with high engagement levels mostly have low discussion levels

Groups with highest engagement (cmts/wk per 1k mbr / disc/wk per 1k mbr)
  • Business Intelligence Professionals , 11.03 (0.23 / 0.02)
  • Pattern Recognition, Data Mining, Machine Intelligence, 6.93 (0.67 / 0.10)
  • Statistics & Analytics Consultants Group, 3.04 (1.02 / 0.34)
  • Actuary / Actuarial, Predictive Modeling, Data Mining, 2.04 (0.14 / 0.07)
  • Advanced Analytics, Predictive Modeling & Statistical, 1.96 (0.48 / 0.25)
  • Big Data, Analytics, Hadoop, NoSQL & Cloud Computing, 1.72 (1.24 / 0.72)
  • RDataMining: R and Data Mining, 1.26 (2.31 / 1.84)
  • Text Analytics, 1.02 (0.76 / 0.75)
  • Machine Learning Connection, 0.93 (0.58 / 0.63)
  • Advanced Business Analytics, Data Mining and Predictive Mode, 0.84 (0.83 / 0.99)

 
Next chart shows shows group comments/week per 1,000 members vs group discussions/week per 1,000 members. Group name abbreviations are in the table below. Since the distributions of comments and discussions are very asymmetrical, we use log scale axes.

The median along each axis create 4 quadrants: Active, Commenting, Posting, and Passive.

Top Linked Analytics, Big Data groups, 14 Q2 to 15 Q1, comments vs discussions, 4 quadrants
Fig. 6: Top LinkedIn Analytics, Big Data, Data Mining, Data Science Groups,
Activity, 14Q2 to 15Q1, Comments/week vs discussions/week per 1000 members
Closed groups are squares while open groups are circles.
4 Quadrants: Active, Commenting, Posting, and Passive

For better separation of groups, both axes are on logarithmic scale

The median lines on each dimension create 4 quadrants:
  • Active, top right - both discussions and comments above median
  • Commenting, bottom right - discussions below but comments above median
  • Posting: top left, discussions above, but comments below median
  • Passive: bottom left, both discussions and comments below median.

 
Here are the groups in each quadrant, in order of activity = comments/wk per 1k members + discussions/wk per 1k members

Active: both discussions and comments above median:
  • KDnuggets (KDnuggets), Activity=10.20
  • Data Scientists ((DScient)) , 8.04
  • Data Science & Machine Lea (ning (DS) & ML), 5.13
  • Predictive Analytics Network (PAN) , 4.24
  • RDataMining: R and Data Mining (RDM), 4.15
  • BIG DATA Professionals - Architects Scientists IOT Analytics (BD pros), 4.07
  • Big Data and Analytics (BD & A), 3.66
  • Data Mining, Statistics, Big Data, and Data Visualization (DMSBD), 3.28
  • Machine Learning and Data Science (ML/DSC), 2.66

 
Commenting, bottom right - discussions below median but comments above median
  • Next Gen Market Research (NGMR), 1.96
  • Big Data, Analytics, Hadoop, NoSQL & Cloud Computing (BDAHN), 1.96
  • Advanced Business Analytics, Data Mining and Predictive Mode (Adv BADM), 1.81
  • Text Analytics, 1.52
  • Statistics & Analytics Consultants Group, 1.36
  • Machine Learning Connection, 1.21
  • Pattern Recognition, Data Mining, Machine Intelligence ..., 0.77
  • Advanced Analytics, Predictive Modeling & Statistical ..., 0.73

 
Posting: comments below median, discussions/posts above median:
  • IBM Big Data and Analytics, 4.92
  • Data & Text Analytics Professionals , 3.37
  • Advanced Analytics, 2.91
  • Business Analytics, 2.89
  • Global Analytics Network , 2.25
  • Research Methods and Data Science, 1.77
  • Predictive Analytics, 1.62
  • Business Intelligence & Analytics Group, 1.50

 
Passive (both comments and posts below median):
  • Visual Analytics, 1.43
  • Healthcare Data Mining and Modeling, 1.41
  • Big Data | Analytics | Strategy | Finance | Innovation, 1.39
  • Data Mining Technology, 1.35
  • SAS & Analytics Users, 1.28
  • Data Warehouse / Big Data / Hadoop / Predictive Analytics, 0.88
  • SAS Analytics & BI, 0.54
  • Business Intelligence Professionals , 0.25
  • Actuary / Actuarial, Predictive Modeling, Data Mining ..., 0.20
  • Lavastorm Analytics Community Group, 0.20

 
The details are in the table with below. This table orders the groups by activity. Since the distribution of comments and discussions is very uneven, we computed separate "comment" rank and "discussion" rank for each group, and order groups by Avg Rank - their average rank. Eg KDnuggets is n. 1 in discussions/1k members and n. 3 in comments/1k members so its average rank is 2. In case of ties, we choose the group with highest sum of comments and discussions.
A group is open, unless it has a lock icon c next to its name.

Table 1: Top LinkedIn Analytics, Big Data, Data Mining, and Data Science groups,
Comments and Discussions, 2014 Q2 - 2015 Q1
.
Values 25% or more higher than median are in green,
25% or more lower than median are in red, and the rest are in black.
LinkedIn Group Avg Rank
/ 1k mbr
Cmts/wk
/ 1k mbr
Disc/wk
/ 1k mbr
Members
(Mar 30, 2015)
Median na 0.451 1.286 18377
KDnuggets KDnuggets Analytics, Data Mining, and Data Science (KDnuggets)
owner: Gregory Piatetsky-Shapiro
2 1.34 8.86 8560
DScient Data Scientists (DScient)
owner: Troy Sadkowsky
2 1.38 6.66 14063
DS & ML Data Science & Machine Learning (DS & ML)
owner: Pavandeep Kalra
7 0.74 4.39 8895
RDM RDataMining: R and Data Mining (RDM)
owner: Yanchang Zhao
7.5 2.31 1.84 11677
BD & A Big Data and Analytics (BD & A)c
owner: Sarah Howes
7.5 0.8 2.86 120776
PAN Predictive Analytics Network (PAN)
owner: Srikanth Velamakanni
9 0.63 3.61 12604
BD pros BIG DATA Professionals - Architects Scientists IOT Analytics (BD pros)
owner: Qamar Zia
9 0.66 3.41 45443
IBM BDA IBM Big Data and Analytics (IBM BDA)
owner: Bruce Weed
12 0.38 4.54 14277
DMSBD Data Mining, Statistics, Big Data, and Data Visualization (DMSBD)
owner: Jon Francis
12 0.54 2.74 68539
NGMR Next Gen Market Research (NGMR) (NGMR)
owner: Tom HC Anderson
14 0.8 1.17 24049
ML/DSC Machine Learning and Data Science (former DSC) (ML/DSC)c
owner: Richard Snee
14.5 0.46 2.2 20876
Adv An Advanced Analytics (Adv An)c
owner: Osris Arya
15 0.43 2.48 16453
Biz An Business Analytics (Biz An)
owner: Alberto Roldan
15 0.41 2.48 70326
Adv BADM Advanced Business Analytics, Data Mining and Predictive Mode (Adv BADM)
owner: Vincent Granville
15 0.83 0.99 174362
BDAHN Big Data, Analytics, Hadoop, NoSQL & Cloud Computing (BDAHN)
owner: VenkataHari Shankar
15.5 1.24 0.72 33139
RMDS Research Methods and Data Science (RMDS)
owner: Alex Liu
17 0.45 1.32 18377
Text A Text Analytics (Text A)
owner: Maria Milosavljevic
17.5 0.76 0.75 16404
SAC Statistics & Analytics Consultants Group (SAC)c
owner: Burke Powers
17.5 1.02 0.34 46481
D&TA Prof Data & Text Analytics Professionals (D&TA Prof)
owner: Tom HC Anderson
18 0.16 3.21 9086
Pred An Predictive Analytics (Pred An)
owner: William Erwin
19.5 0.24 1.38 6945
ML Conn Machine Learning Connection (ML Conn)c
owner: Shane Threatt
21 0.58 0.63 24712
BI&A Business Intelligence & Analytics Group (BI&A)
owner: Rakesh Rajora
22 0.21 1.29 20000
Visual Visual Analytics (Visual)
owner: Christian Posse
22 0.24 1.18 10762
PRDM Pattern Recognition, Data Mining, Machine Intelligence ... (PRDM)c
owner: Belur V. Dasarathy
22 0.67 0.1 21813
Healthcar Healthcare Data Mining and Modeling (Healthcar)
owner: Raghu Santhanam
22.5 0.35 1.06 4684
BDASFI Big Data | Analytics | Strategy | Finance | Innovation (BDASFI)c
owner: Josie King
22.5 0.25 1.13 128805
Global A Global Analytics Network (Global A)c
owner: Roni Lynn Zapin
23 0.08 2.16 20432
Adv AP Advanced Analytics, Predictive Modeling & Statistical ... (Adv AP)c
owner: John Frischenmeyer
23.5 0.48 0.25 9185
DMT Data Mining Technology (DMT)c
owner: Stan Byrne
26 0.07 1.29 4854
SAS Users SAS & Analytics Users (SAS Users)c
owner: Michael Kaushansky
26 0.14 1.15 18283
DW/BD/H Data Warehouse / Big Data / Hadoop / Predictive Analytics (DW/BD/H)c
owner: Chris Rosser
28.5 0.12 0.75 32994
SAS A&BI SAS Analytics & BI (SAS A&BI)c
owner: Stan Byrne
28.5 0.18 0.36 24575
BI Pros Business Intelligence Professionals (BI Pros)c
owner: Rajasekar Nonburaj
30.5 0.23 0.02 150147
Actuary Actuary / Actuarial, Predictive Modeling, Data Mining ... (Actuary)c
owner: Tom Troceen
32 0.14 0.07 17616
Lavastorm Lavastorm Analytics Community Group (Lavastorm)
owner: William Thomas
33.5 0.03 0.17 7126


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