Workshop on Big Social Data Analytics


 
Torsdag, 8 oktober, 2015 - 09:00 to Fredag, 9 oktober, 2015 - 16:30

The workshop on Big Social Data Analytics is organized by the Computational Social Science Laboratory (cssl.cbs.dk) directed by Prof. Ravi Vatrapu in collaboration with Prof. Hannu Kärkkäinen’s research group from the Department of Information Management and Logistics at Tampere University of Technology (TUT), Finland. The workshop is hosted at the Department of IT Management from 08-09 October, 2015. The workshop is about comparing and contrasting the traditional method of Social Network Analysis (SNA) based on relational sociology and graph theory with CSSL’s new approach of Social Set Analysis (SSA) based on phenomenolgical sociology, ecological psychology and set theory for a class of problems in social media campaigns in crowdfunding platforms and knowledge ecosystems.
 
The workshop will involve hands-on demos and tutorials with data as well as discussion of conceptual problems and methodological aspects. You are welcome to participate in the  2-day workshop if you are interested. Please send an email to lal.itm@cbs.dk to register for the workshop by the 7th of October 2015. The preliminary workshop program is below:
 
Big Social Data Analytics of Crowdfunding Platforms and Knowledge Ecosystems

DAY #1: 09:00-16:30 on Thursday, 08-Oct-2015

  • Data Crawling and Scraping Exercises
  • Social Network Analysis Exercises (1/2)
  • Social Set Analysis Exercises: Interactions (1/2)

Data Crawling and Scraping Exercises

  1. Exercise1: Crawling and scraping of Authors Data from Academic Articles Database (ex. Scopus, Web of Science, CRIS)
  2. Exercise2: Crawling and scraping from Crowdfunding Platform (Indiegogo: using MindTrek Script). We can go a bit further than funders data by including the Comments data as well.

What is needed for the above exercises?

  1. MacBook (For Crowdfunding data, limitation because of Indiegogo)
  2. Tools – Python, CasperJS

 Social Network Analysis (SNA): 1/2

  1. Introduction to Network Analysis
  2. Creating networks with NetworkX library
  3. Network analysis of Exercise 1 (Authors Data) from data crawling and scraping session

What is needed for the above exercises?
Tools : Gephi, NodeXL, Python, Pandas library, NetworkX library

Social Set Analysis Exercises (SSA): Interactions 1/2

  • Social Set Analysis (SSA)
  • Introduction to Set Theory and Set Theoretical Computational Social Science
  • Introduction to Event Study Methodology and Text Analytics
  • SSA across Time
  • SSA across Space

What is needed for the above exercises?

Tools: SODATO, R, R-Studio
 
DAY #2: 09:00-16:30 on Friday, 09-Oct-2015

  • Social Network Analysis (2/2)
  • Social Set Analysis Exercises: Conversations (2/2)
  • Publication planning based on the results from the exercises during the 2 days

Social Network Analysis (SNA): 2/2

  1. Network analysis of Exercise 2 (Crowdfunding Data) from data crawling and scraping session

What is needed for the above exercises?
Tools : Gephi, NodeXL, Python, Pandas library, NetworkX library

Social Set Analysis Exercises (SSA): Conversations: 2/2

Tools: SODATO, R, NLTK

 What is needed for the above exercises?
Tools : From CSSL: Social Data Analytics Tool, Social Set Visualizer, R-scripts, NLTK

Publication planning

Publication on comparison of methods (SSA/SNA)

  • Based on the workshop it has to be agreed upon if these methods can be compared or they are used to complement each other.
  • Next publication on the crowdfunding case using data from the workshop
  • Based on the workshop the data has to be preliminarily analyzed and Research objectives (questions) to be made for the publication.
  • If there is some specific Data related requirement from Jolla then that has to be identified. This will enable TUT researchers to get in touch with Jolla and get that data.

SNA v. SSA
·       Conceptual Problems
·       Methodological Issues
·       Class of Problems: Suitability & Applicability
 
Next Steps & Conclusion
* A detailed program will be sent to all the participants.
 
Find more about Computational Social Science Laboratory (CSSL) here -> http://cssl.cbs.dk
Find more about Prof. Hannu  Kärkkäinen’s research group here -> (https://www.tut.fi/novi/?page_id=1973)

Organisers:

Raghava Rao Mukkamala
Assistant Professor of Computational Social Science
Computational Social Science Laboratory (cssl.cbs.dk)
Dept. of IT ManagementCopenhagen Business School
+45 41 85 22 99
rrm.itm@cbs.dk
http://www.itu.dk/people/rao/

Lester Allan Lasrado
PhD Fellow in Networked Business Maturity
Computational Social Science Laboratory (cssl.cbs.dk)
Dept. of IT ManagementCopenhagen Business School
+45 41 85 22 64
lal.itm@cbs.dk
www.cbs.dk/en/staff/lalitm

Sted 
Howitzvej 60, 2000 Frederiksberg

Room: 5.23

Sidst opdateret: Department of Digitalization // 08/10/2015