This document discusses computational methods for intelligent matchmaking using social media data. It summarizes a case study called CMAD that aimed to identify weak ties from publicly available social media data related to a conference event. The study found it was possible to identify potential weak ties using Twitter data but Facebook data was not useful. Limitations included a small number of survey respondents. Future research opportunities include combining additional data sources and analytics methods like social network analysis to better identify tie strengths and validate results.

1. COMPUTATIONAL METHODS FOR INTELLIGENT MATCHMAKING FOR
KNOWLEDGE WORK – CASE CMAD
Jayesh Prakash Gupta, Tampere University of Technology, Finland
Jari Jussila, Tampere University of Technology, Finland
Ekaterina Olshannikova, Tampere University of Technology, Finland
Karan Menon, Tampere University of Technology, Finland
Jukka Huhtamäki, Tampere University of Technology, Finland
Thomas Olsson, Tampere University of Technology, Finland
Prof. Ravi Vatrapu, Copenhagen Business School, Denmark
Prof. Hannu Kärkkäinen, Tampere University of Technology, Finland
References
Granovetter, Mark S. "The strength of weak ties." American journal of sociology 78.6 (1973): 1360-1380.
Marsden, Peter V., and Karen E. Campbell. "Measuring tie strength." Soc. F. 63 (1984): 482.
Gilbert, Eric, and Karrie Karahalios. "Predicting tie strength with social media." Proceedings of the SIGCHI conference on human factors in computing systems. ACM, 2009.
Gupta, Jayesh Prakash, et al. "Identifying weak ties from publicly available social media data in an event." Proceedings of the 20th International Academic Mindtrek Conference. ACM, 2016.
Availability of Big Social DATA
Results
• It is possible to identify potential weak ties from using the publically available social
media data
• Facebook data was not useful in identifying weak ties
• Twitter was helpful in identifying the potential weak ties.
• Temporal pattern of different social media channels use was different for Twitter
and Facebook
Limitations:
• Insufficient number of survey respondents to draw any statistically significant result
• Only some of the possible methods for weak tie identification were used
Future Research
• Combined other kind of data sources and methods for weak tie identification
• Move towards utilizing Big Social Data
• Utilize new analytics methods like Social Set Analysis
• Validate the results using large number of survey respondents
• The next steps:
 Please signup to be part of the future studies by providing your details on the
following link or by scanning the QR code
http://bit.ly/2jGOw64
Part of the COBWEB research project
Funded by Academy of Finland (http://www.aka.fi).
Presented Jan 23, 2017 at CMAD2017, University of Tampere, Tampere.
Match Making in Professional Life Some Current Match Making Apps
grip.events shapr.net
Case CMAD 2016 Results
Interaction networks
Twitter
Facebook
Possible clusters based on Twitter Data
Modularity class Cluster name
1 Personal branding
2 Employee advocacy
3 Drawings and infographics
5 **Broadly about cmadfi event
6 Community manager
7 Communications
10 *Reporting on CMADFI event
15 Customer service
16 Project
17 *Outsider greetings
18 Tekes
20 Knowledge management
21 Jyväskylän energia
Why is tie strength (weak and strong ties)
important? Why social media / BSD
analytics?
Examples of matchmaking- related needs (which are rarely made use of e.g.
in current matchmaking tools):
Efficient spreading of information/research results/etc. to as large group of
relevant people as possible (strong ties, authoritative/influencing persons)
Identify new viewpoints and knowledge to problems or for new innovations /
new interdisciplinary research (weak ties; both similar and new knowledge)
Find relevant persons in professional events and conferences (find persons
with novel / complementary expertise / persons with influence)
Find interesting collaborators to a research project
Different Kind of Ties
• Strong ties: Strong ties
are the ones that a
person really trust. For
eg. family
• Weak ties: Refers to
weak links which may be
known.Eg.
acquaintances, friend of
friend
• Weak ties are very
useful in spreading novel
information.
New Possibilities with Big Social DATASocial Media Data , BSD and SNA (Social
Network Analysis) in tie strength
evaluation and matchmaking?
Social Media data for example Facebook
Friends, Twitter Follower/ Followee, have
been used to identify the actual social
network and tie strength of a person.
Additionally, it is possible to use
conversation data on social media to
evaluate tie strength and help in
identifying different kind of ties. SNA is
one possible way to do this.
SNA enables in easier identification of
different influential people and the
potential sub- communities in a network.
BSD can e.g. enable using the historical
conversation / other social data about
conference/s to provide preliminary
deductions about participants tie strength
and the possible useful ties, their common
or complimentary interests. For example
co-occurrence of conference participants.