KDnuggets Home » News :: 2013 :: Apr :: Top 30 LinkedIn Groups for Analytics, Big Data, Data Mining, and Data Science ( 13:n11 )

Top 30 LinkedIn Groups for Analytics, Big Data,
Data Mining, and Data Science


We investigate the largest LinkedIn groups for Analytics, Big Data, Data Mining, and Data Science and look at their size, growth and activity levels. We find there are 50% more discussions/week than comments, and Big Data groups are the fastest growing.



We extended our previous analysis and collected data on LinkedIn groups related to Analytics, Big Data, Data Mining, and Data Science with at least 2,000 members.

The groups with the largest number of members (as of April 20, 2013) are:

  • Advanced Business Analytics, Data Mining and Predictive Modeling, 76,150
  • Big Data / Analytics / Strategy / FP&A / S&OP ..., 60,474
  • Business Analytics, 39,851
  • Big Data and Analytics, 39,560
  • Data Mining, Statistics, Big Data, and Data Visualization, 21,705

We also measured each group growth from it founding to April 20, and the 5 groups with the fastest growth are below. Note that the two fastest growing groups start with "Big Data", another evidence of the "Big Data" buzz.

LinkedIn Group Founded Members
/Month
Big Data and Analytics 1-Mar-12 2860
Big Data / Analytics / Strategy / FP&A / S&OP ... 20-Feb-09 1194
Advanced Business Analytics, Data Mining and Predictive Modeling 28-Sep-07 1125
Data Science Central 10-Feb-12 660
Business Analytics 3-Mar-08 638

We also looked at how active is each group, as measured in the number of comments and discussions per week. We measured these over 4 weeks, from Mar 11 to Apr 7, 2013. Thanks to KDnuggets intern Anmol Rajpurohit for manually collecting the comments and discussions numbers from the activity graphs.

Interestingly, posting discussions is 50% more common than commenting - we found that over all groups, the average number of discussions was 2.4/week per 1000 members, while average number of comments was 1.6/week per 1000 members.

The chart below shows average comments/week vs average discussions/week for all 30 groups, with a circle size proportional to group size and darker color corresponding to faster growth. Group name abbreviations and full stats in the table below.

Top 30 LinkedIn Analytics/Big Data/Data Mining Groups

We note that a large cluster of groups has about 1 comment/week per 1000 members. A second cluster includes two biggest groups and has about 2 comments/1000 members. A third cluster has 5 groups which are very active relative to their size. Two more groups stand out - NGMR has the highest rate of comments, and PAN has the highest rate of discussions.

Below are the 5 most active groups, with Activity = Comments + Discussions. The numbers are counts per week, averaged over 4 weeks, from Mar 11 to Apr 7, 2013.

LinkedIn Group Activity
/1K members
Comments
/1K members
Discussions
/1K members
Data Scientists 9.64 3.48 6.16
KDnuggets Analytics and Data Mining 8.97 3.45 5.52
BIG DATA Professionals 7.8 2.92 4.88
Predictive Analytics Network (PAN) 7.68 0.97 6.71
Next Gen Market Research (NGMR) 7.03 4.69 2.34

Here is the detailed data on all 30 LinkedIn groups, with group abbreviation following the group name. Closed groups denoted by (cl). Something strange is going on with Business Intelligence & Analytics Group (BI&A) where the number of members stayed at exactly 20,000 for the past month.

LinkedIn Group Members (Apr 20) Founded Members
/Month
Comments
/1k memb
Discussions
/1k memb
Adv BADMAdvanced Business Analytics, Data Mining and Predictive Modeling (Adv BA) 76,150 28-Sep-07 1,125 2.18 1.82
Big Data ASFSSPBig Data / Analytics / Strategy / FP&A / S&OP ... (Big Data ASFSSP) 60,474 20-Feb-09 1,194 2.11 1.88
Biz AnalyticsBusiness Analytics (Biz A) 39,851 3-Mar-08 638 1.19 1.12
Big Data & ABig Data and Analytics (Big Data & A) 39,560 1-Mar-12 2,860 3.64 1.82
DM StatData Mining, Statistics, Big Data, and Data Vis (DM Stat) 21,705 25-Jul-08 376 2.63 3.87
NGMRNext Gen Market Research (NGMR) 21,277 26-Sep-07 314 4.69 2.34
BI&ABusiness Intelligence & Analytics Group (BI&A) 20,000 6-Jan-08 311 1.25 1.73
Global AGlobal Analytics Network (Global A) 18,130 23-May-08 303 0.43 2.89
BD ProfBIG DATA Professionals - Architects Scientists Analytics Experts (BD Prof) 17,808 1-Sep-08 316 2.92 4.88
SAS A&BISAS Analytics & BI (cl) (SAS A&BI) 16,858 25-Jun-08 287 0.96 1.52
ML ConnMachine Learning Connection (cl) (ML Conn) 12,780 12-Mar-08 206 0.78 0.7
ActuaryActuary / Actuarial, Predictive Modeling, Data Mining, and Statistics (Actuary) 12,374 24-Sep-08 222 0.12 1.93
RMAResearch Methods and Analytics (RMA) 11,569 10-Apr-09 236 2.13 1.11
SAS UsersSAS & Analytics Users (SAS Users) 11,567 13-Apr-08 189 0.65 1.21
Text AText Analytics (Text A) 11,447 2-Jun-08 193 0.99 1.37
Pattern Recognition, Data Data Mining, Machine Intelligence (cl) (PR) 10,846 2-Oct-08 196 2.26 0.49
DSCData Science Central (DSC) 9,568 10-Feb-12 660 0.56 3.74
Adv AAdvanced Analytics (cl) (Adv A) 7,809 11-Jan-09 150 0.75 3.4
D&TA ProfData & Text Analytics Professionals (D&TA Prof) 6,926 24-Sep-07 102 1.02 2.22
VisualVisual Analytics (Visual) 6,094 31-Mar-08 99 1.19 2.42
LavastormLavastorm Analytics Community Group (Lavastorm) 5,658 17-Apr-11 231 0.36 2.69
Adv APAdvanced Analytics, Predictive Modeling & Statistical Analyses (cl) (Adv AP) 5,464 10-Jul-08 94 2.47 0.28
PANPredictive Analytics Network (PAN) (PAN) 4,692 16-Mar-09 94 0.97 6.71
DscientistsData Scientists (Dscientists) 3,621 8-Jun-09 77 3.48 6.16
PMMLPredictive Model Markup Language (PMML) (PMML) 3,236 24-Sep-09 74 0.23 0.16
DMTData Mining Technology (cl) (DMT) 3,213 20-Jun-08 55 0.63 1.19
KDnuggetsKDnuggets Analytics and Data Mining (KDnuggets) 2,939 4-Feb-08 46 3.45 5.52
HealthcareHealthcare Data Mining and Modeling (Healthcare) 2,463 11-Jul-08 42 0.21 0
RDMRDataMining (RDM) 2,366 30-Aug-11 118 3.47 3.25
BI ToolsBusiness Intelligence Tools (BI Tools) 2,289 2-Jul-08 39 0 3.97
Average 15624 22-Dec-08 362 1.6 2.4

Comments from the Web

In Data Science Central:

Eli Y. Kling

An excellent bit of insightful analysis. Good on you. My first reaction was to join all the groups listed. But that is missing the very good bit of insight presented here. Personally I do not care how many posts appear as there is a great deal of waffle and overlap. I will go for the one that generate conversations. Perhaps the next step is to look at the length of the threads.