The presentation given at the 33rd Sunbelt Social Networks Conference of the International Network for Social Network Analysis, May 21-26 2013, University of Hamburg

1. The Impact of Time Zone Difference on Social
Networks of Entrepreneurs
Dr Linas Eriksonas
International Business School at Vilnius University
Linas.Eriksonas@tvm.vu.lt
Sunbelt 2013 Conference, UniversityofHamburg

2. Introduction
• Interpersonal relationships, as a cornerstone of social capital, influence
one’s ability to access information that facilitates discovery of
entrepreneurial opportunities (Aldrich and Zimmer, 1986;Baron and
Markman, 2000)
• Capital seekers and providers often find each other via social networks
• A U.S. Small Business Administration survey found that 75% of new
businesses find and secure financing through their social capital

3. Time dimension in venture growth
Adopted from EntrepreneurialFinance,
Leach & Melicher (2011), 3rd ed

4. Time difference: initial assumption
Distance(timediff)
Social networks
Seed
stage:
Family,
pre-seed
Growth
stage:
Seed,VC
rounds
Exit stage:
Exitsvia
IPOs,M&As
Capital networks
1 hr
2-3 hrs
>3 hrs

5. Experimental model for analysis
Distance(timediff)
Social networks
Seed
stage:
Family,
pre-seed
Early
stage:
Seed, VC
rounds
Growth
stage:
Exitsvia
IPOs,M&As
Capital networks
1 hr
2-3 hrs
>3 hrs
Gap?
Gap?

6. Research questions
• Is there a gap between social networks and venture capital
networks in terms of time difference between its members?
– In other words, is venture capital rooted in social
networks? (P.Bourdieu)
– If so, can social/capital networks be time-zone dependent
when using social media (Twitter)?
– If so, how can we get around it?

7. Previous work on geo distances
• Liben and Nowell (Liben-Nowell et al. 2005) constructeda
model for predicting friendship link formation based on the
observation that the probability of forming friendship links is
inversely proportional to the geographic proximity and to the
number of people who are geographically close
• Geographic distance has a pronounced effect on the number
of reciprocal relationships created between users, but little
effect on the likelihood of users following back each other
(Tiancheng et al, 2010).

8. Previous work on Twitter
• (Java et al. 2007) and (Krishnamurthy, Gill, and Arlitt 2008)
examined and discovered differences between the properties
and growth of the networks of Twitter users in different
geographic regions
• (Takhteyev,Gruzd, and Wellman 2011) found that geographic
distances, national boundaries, and languages hold
considerable influence on the formation of social ties on
Twitter
• (Kulshrestha,Kooti, Nikravesh and Gummadi, 2012): even
though users preferentially connect and exchange information
with other users from their own country, more than a third of
all links and tweets are exchanged across national
boundaries

9. Research design
Top VCs online
(rankings*)
Research
questions
Seed->Early stage actors
Top success. 20
VCs (rankings#)
Early stage->Growth stage actors
* - Top 10 influential VC firms and venture capitalists on the web (openview, 2011/2012)
# - The Top 20 Most Successful Tech VC Firms (PrivCo, 2012, based on number of exits)
Twitter
via API
scripts
Analysis
Model
check

10. Seed lists for data collection
1. Intel Capital, Santa Clara, CA
2. Felicis Ventures, Palo Alto, CA
3. SV Angel, San Francisco, CA
4. Sequoia Capital, Menlo Park, CA
5. First Round Capital, San Francisco, NYC,
Philadelphia
6. Battery Ventures, Menlo Park, Waltham,
MA, Israel
7. Draper Fisher Jurvetson, Menlo Park
8. Greylock Partners, NYC
9. Ignition Partners, Palo Alto, Bellevue, WA
10. Google Ventures, Mountain View
11. True Ventures, Palo Alto, CA
12. Benchmark Capital, Menlo Park, San
Francisco, CA
13. Lerer Ventures, NYC
14. Menlo Ventures, Menlo Park, CA
15. Polaris Venture Partners, Boston, MA, San
Francisco CA, Dublin
16. Accel Partners, Palo Alto, CA, London, India
17. Bain Capital Ventures, Boston, MA, NYC,
Palo Alto, CA
18. Redpoint Ventures, Menlo Park, Los
Angeles, CA, Shanghai, China
19. RRE Ventures, NYC
20. Focus Ventures, Palo Alto, CA
Top 20 VC (2012, openview)Top influential10 VC firms
(2011/2012, PrivCo) Online:
• Accel Partners
• First Round Capital
• Greylock Partners
• Sequoia Capital
• Union Square Ventures
Top influential10 VC capitalists
(2011/2012, Privco) online:
• Brad Feld, Foundry
• Bill Gurley, Benchmark Capital
• Chris Dixon, Founder Collective
• Charlie O’Donnell, Brooklyn Bridge Ventures
• Charlie McClure, 500 startups
• David Hornik, August Capital
• Fred Wilson, Union Square Ventures
• Josh Kopelman, First Round Capital
• Mark Suster, GRP Partners
• Paul Graham, Y Combinator
• Paul Kedrosky, Kedrosky Capital
Consolidated35 unique Twitter handles

11. Friends
(25942
counts)
Followers
(1770908
counts)
Confirmededges
(6687 counts)
Shared 20% of
confirmed edges
<10 (21 counts)
Analysed data

12. Friends/confirmed edges share, corr.

13. Number of shared edges, time zones

14. Network of top venture capital firms and
venture capitalists, entrepreneurs
The density of the network was such that it was impossible to make much sense;
Visualisationdone with R thanks by Thomas Metz, Freiburg uni., Sunbelt 2013 conf.

15. Graph Distance:
•Diameter: 5
•Average Path length: 2.77
• Number of shortest
paths: 166817
Modularity:
•Modularity:0,61
•Average Degree: 1,28
• Number of
Communities:18
•Weakly Connected
components: 2
•Strongly Connected
Components:1294
•Average Clustering
Coefficient:0,083

16. Core of the network, time zones
Density of CORE NETWORK is: 0.1239

17. Density of CORE NETWORK ALL but
PST: 0.0588
Density of CORE NETWORK in PST:
0.2329
Density of CORE NETWORK
in EST: 0.0627
Density of CORE NETWORK ALL BUT PST & EST: 0.0719

18. Twitter limitations
• half life of a link on twitter was 2.8 hours
Bitly.com

19. GMT Pacific Mountain Central Eastern Santiago Brasil GMT Europe Eastern EurGulf Moscow Central Asia
8:00 AM 0 3600 7200 10800 14400 18000 21600 25200 28800 36000 39600 43200 46800 50400
9:00 AM 3600 7200 10800 14400 18000 21600 25200 28800 32400 39600 43200 46800 50400 54000
10:00 AM 7200 10800 14400 18000 21600 25200 28800 32400 36000 43200 46800 50400 54000 57600
11:00 AM 10800 14400 18000 21600 25200 28800 32400 36000 39600 46800 50400 54000 57600 61200
12:00 AM 14400 18000 21600 25200 28800 32400 36000 39600 43200 50400 54000 57600 61200 64800
1:00 PM 18000 21600 25200 28800 32400 36000 39600 43200 46800 54000 57600 61200 64800 68400
2:00 PM 21600 25200 28800 32400 36000 39600 43200 46800 50400 57600 61200 64800 68400 72000
3:00 PM 25200 28800 32400 36000 39600 43200 46800 50400 54000 61200 64800 68400 72000 75600
4:00 PM 28800 32400 36000 39600 43200 46800 50400 54000 57600 64800 68400 72000 75600 79200
5:00 PM 32400 36000 39600 43200 46800 50400 54000 57600 61200 68400 72000 75600 79200 82800
PST Pacific Mountain Central Eastern Santiago Brasil GMT
8:00 AM 28800 32400 36000 39600 43200 46800 50400 54000 57600
9:00 AM 32400 36000 39600 43200 46800 50400 54000 57600 61200
10:00 AM 36000 39600 43200 46800 50400 54000 57600 61200 64800
11:00 AM 39600 43200 46800 50400 54000 57600 61200 64800 68400
12:00 AM 43200 46800 50400 54000 57600 61200 64800 68400 72000
1:00 PM 46800 50400 54000 57600 61200 64800 68400 72000 75600
2:00 PM 50400 54000 57600 61200 64800 68400 72000 75600 79200
3:00 PM 54000 57600 61200 64800 68400 72000 75600 79200 82800
4:00 PM 57600 61200 64800 68400 72000 75600 79200 82800 86400
5:00 PM 61200 64800 68400 72000 75600 79200 82800 86400 3600
Twitter time zone limitations

20. Time zone coverage during best “tweeting”
hours in PST and EST

21. Time zone coverage during best “tweeting”
hours in PST, EST & GMT
Totalnumber of reachabletime zones at best twitting hours:
- PCT (65), EST (GMT), EST (39)

22. Preliminary conclusions
• Is there a gap between social networks and venture capital
networks in terms of time difference between its members? –
The hypothesis has not been confirmed
• Is venture capital rooted in social networks?(P.Bourdieu) –
Confirmed
• Can social/capital networksbe time-zone dependent when
using social media (Twitter)?Confirmed
• Time zone difference can help to understand the constrains
on social network growth and the impact it can have on the
growth social/capital networks

23. Afterthought: How can we get around it?
• Answer suggested by Masaki Shimada, Tokyo, during a Sunbelt 2013 conf.
participant: Yes, we can by having physical presence across the time zones
spread out in an optimal way* (a similar approach being used by the
syndicated VCs such as Canaan Partners, see chart below)
Twitter friends and followers of Canaan Partners, top 5 socially connected VC firms
(Activate Networks 2012) with offices in Menlo Park, CA, NYC, London, Tel Aviv, India.
* - the functionalityof rescheduled tweets was implementedby Hootsuite and Bufferapp
as of 2012; they do not ensure the full real-time experience of tweeting aroundthe globe

24. References
• Javaet al., Why We Twitter: UnderstandingMicroblogging Usage and
Communities, Joint 9th WEBKDD and 1st SNA-KDD Workshop ’07 , August 12,
2007, San Jose, California
• Krishnamurthy B., Gill P., and Arlitt M., A Few Chirps about Twitter, Proc. of ACM
SIGCOMM Workshop on Online Social Networks. Seattle, USA. Aug. 2008
• Kulshrestha, Kooti, Nikraveshand Gummadi, Geographic Dissection of the Twitter
Network, Proceedings of the Sixth International AAAI Conference on Weblogs and
Social Media, 2012
• Liben-Nowellet al., Geographic routing in social networks,
www.pnas.org/cgi/doi/10.1073/pnas.0503018102
• Hopcroft, J., Tiancheng L., Tang J., Who Will Follow You Back? Reciprocal
Relationship Prediction,CIKM '11 Proceedings of the 20th ACM international
conference on Information and knowledge management, p. 1137-1146 (2011),
http://dx.doi.org/10.1145/2063576.2063740
• Takhteyev,Y., Gruzd, A., and Wellman, B. (2012). Geography of Twitter Networks.
Social Networks, Special issue on Space and Networks, 34(1): 73-81.
DOI:10.1016/j.socnet.2011.05.006.