Presentation at the 13th Annual Conference of the APET in Taiwan, 2012

The role of reciprocation in the formation of socialnetworks

With an application to blogging

Alexia Gaudeul and Caterina Giannetti

Max Planck Institute of Economics, JenaRoyal Holloway, University of London

13th Annual Conference of the APETJune 12-14, 2012

Academia Sinica, Taipei, Taiwan

Overview Blogging Empirical Analysis Conclusions References

Overview

1 Analysis of the dynamics of network formation among bloggers

2 Panel of 1000+ bloggers, followed over more than a year3 Two main factors in audience growth:

Attractive content, i.e. writing entries others will want to readReciprocation, i.e. paying attention to others so they will payattention to you

4 Which is more important reveals the nature of the activity being ledwithin blogging network

Part of the Mass Media orA tool for social networking

The role of reciprocation in the formation of social networks 2 / 24 Alexia Gaudeul and Caterina Giannetti


Research themes

Research themes

Online social networking: unprecedented, non-intrusive, and cheapaccess to micro data about “winning friends and influencing people”[Carnegie, 1936].

Three main themes:1 Friendship [Aristotle, ca. 350 B.C.E., De Montaigne, 1588]2 Competition for attention [Simon, 1971, Falkinger, 2007]3 Norm of reciprocity [Gouldner, 1960]

Insight

The norm of reciprocity leads to requests for friendship being usuallyreciprocated, so that paying attention to and initiating friendship withothers helps gain attention for oneself



Different strands in research

Blogging - Different strands in research

1 Sociology [Technorati, 2009, Lenhart and Fox, 2006]

2 Typology [Wei, 2009]

3 Motivation [Huang et al., 2007]

4 Structure [Shirky, 2003, Kumar et al., 2010]

Contribution

We contribute to the literature by considering the development ofbloggers’ audiences over time along with their activity, including theactivity of adding people to one’s network.



Modelling the activity of bloggers

Blogging - Modelling the activity of bloggers

1 Information gathering and transmission [Galeotti and Goyal, 2010]

2 Content production in exchange for attention [Gaudeul and Peroni,2010, Rui and Whinston, 2010]

3 Building social capital [Glaeser et al., 2002]

Our approach

We adapt Glaeser et al. to take account of the role of reciprocation in theprocess of building an audience within blogging networks.



Activity, Readership and Reciprocation

Blogging - Activity, Readership and Reciprocation

Gain readersPost contentX ΔR(X)





New FriendsGain readersPost contentX ΔR(X) θΔR(X)

Reciprocation by oneself





Activity

Look for friends New Readers

New FriendsGain readersPost content

Add friends

X

ΔF(Y)

ΔR(X)

ρΔF(Y)

θΔR(X)

Reciprocation by others


Y





∆Readers = ρ Friends Added (Y ) + Readers Gained (X )

∆Friends = Friends Added (Y ) + θ Readers Gained (X )

So

∆Readers = ρ ∆Friends + (1 − ρθ) Readers Gained (X )

∆Friends = θ ∆Readers + (1 − ρθ) Friends Added (Y )

Estimation

We monitor readership over time, along with activity w.r.t. adding friendsand contributing content, with data collected from LiveJournal, a majorblog hosting site [Raynes-Goldie, 2004, Raynes-Goldie and Fono, 2006,Marwick, 2008].



The sample

Empirical Analysis - The sample

NATIONALITYBLOG AGE Russian English Total

Young Readers 152 46Friends 154 59

N (43) (24) (137)

Mature Readers 373 92Friends 265 84

N (382) (352) (1067)

Old Readers 1741 175Friends 383 111

N (9) (97) (143)

Total N (434) (473) (1347)



The sample

Empirical Analysis - The sample

1 Blogs accumulate readers and friends over time

2 Blogs reciprocate less in the aggregate over time

3 The sample is balanced in terms of languages

4 Russian blogs are younger and bigger.

5 English blogs have more balanced readers/friends lists



The estimation model

Empirical Analysis - The estimation model

We estimate the following equation:

Readerst = ρ ∆Friendst︸︷︷︸Reciprocation

+ (1 − ρθ)βAt︸︷︷︸Attract Readers

+ (1 − (1 − ρθ)δ)Readerst−1︸︷︷︸Depreciation

1 At is activity other than seeking out and adding friends

2 Readerst−1 is one’s stock of Readers, which depreciates over time(boredom, disagreements, etc. . . )

Similarly:

Friendst = θ ∆Readerst︸︷︷︸Reciprocation

+ (1 − ρθ)γBt︸︷︷︸Add Friends

+ (1 − (1 − ρθ)λ)Friendst−1︸︷︷︸Depreciation



The variables

Empirical Analysis - The variables

Stock variables are:

Readers (Blogs reading the user)

Friends (Blogs read by the user)

Activity variables are:

1 Communities joined and left

2 Entries written by the user

3 Comments posted by the user

4 Extroversion: Comments posted by the user / Comments received

5 Readers’ Engagement: Comments received / Entries

6 Inactivity: Number of weeks since last entry was made

We also include blog characteristics: Age, Language, Functionalities.The role of reciprocation in the formation of social networks 13 / 24 Alexia Gaudeul and Caterina Giannetti


Reciprocation by others

Empirical Analysis - Reciprocation by others

VARIABLES Pooled OLS FE SYS GMML.Readers 1.004*** 0.986*** 0.985***∆log(Friends) 17.783** 16.001** 25.786***Functionality 0.026 0.469*** 0.776Age blog -0.003*** 0.020*** 0.237*Community joined 0.238** 0.207* 0.567Community left 0.033 0.039 0.497**Entries 0.009** 0.010* -0.080Posted 0.011*** 0.022*** 0.148***Extroversion -0.014*** -0.015*** -0.136***Engagement 0.011 0.012 0.071**Inactive 0.004 -0.018*** -0.016Constant -0.046 -3.038** -22.337Observations 75,432 75,432 75,432Number of user 1,347 1,347 1,347




Empirical Analysis - Reciprocation by oneself

VARIABLES Pooled OLS FE SYS GMML.Friends 1.000*** 0.932*** 0.959***∆log(Readers) 54.736*** 48.869*** 43.031*Functionality 0.063** 0.756*** 0.285Age blog -0.000 0.028** 0.106Community joined 0.595* 0.469* 4.261***Community left 0.058 0.067 1.097***Entries 0.005 0.005 0.035Posted 0.003 0.008** 0.050***Extroversion -0.011* -0.013* 0.003Engagement 0.005 0.006 -0.035Inactive -0.005 -0.028*** -0.963**Constant -0.100 1.307 1.104Observations 75,432 75,432 75,432Number of user 1,347 1,347 1,347



Robustness

Empirical Analysis - Robustness

We check the robustness of our results

1 To weak identification (i.e. system-GMM, Bobba and Coviello, 2007)and instruments proliferation (i.e. Hansen J-statistics, Roodman,2009)

2 To structural specification (i.e. test the validity of subset ofinstruments, using difference in Hansen J-statistics)

3 By considering different sub-groups of blogs (i.e. small vs. large blogsand English vs. Russian-speaking)



Interpretation

Empirical Analysis - Interpretation

1 Reciprocation is a significant factor, but is quite low (25% to 50% vs.87% in Gaudeul and Peroni, 2010)

2 Depreciation in readership is limited, even if cease writing entries for awhile.

3 Making more entries does not increase readership, making them moreengaging does.

4 Posting comments increases readership, but only if compensated byreceiving more comments as well.

5 Joining communities indicate willingness to add friends (leaving themtoo...)

6 There are little differences between Russian and English blogs, eventhough both uses and users differ.

7 Bigger blogs reciprocate readership more willingly.



Social Multipliers and Reflection Effects

Empirical Analysis - Social Multipliers and ReflectionEffects

1 Simultaneity problem (Manski, 1993) as individuals affected bypeer-group activity. However:

1 We control for at least one way in which others’ actions affect mine,and vice versa (reciprocation)

2 We also are able to control for how bloggers interactions with others(comments) are determined by comments they receive.

3 We also control for different peer-groups (Russian vs. English speakingblogs).



Social Multipliers and Reflection Effects

Empirical Analysis - Social Multipliers and ReflectionEffects

We compute total effect of a unit increase in activity on number ofreaders/friends (interim and long term multipliers).

Functionality Posted InactiveTIME Readers Friends Readers Friends Readers Friends

0 0.956 0.696 0.181 0.128 -0.297 -1.091

1 1.887 1.353 0.357 0.248 -0.577 -2.129

2 2.794 1.972 0.529 0.362 -0.839 -3.118

. . .

10 9.302 5.805 1.764 1.064 -2.421 -9.497

. . .

Long-run 51.733 6.951 9.867 1.220 -1.067 -23.488



Conclusions

1 Empirics: Bloggers’ activity on LiveJournal follow consistentpatterns. Experience, audience size or location have little effect.

2 Methodology: Data on activity in social networks should includedata on effort in searching for partners.

3 Contribution: Better understanding of the process of social networkformation + A framework for a general understanding of social mediaand online social networking.

Questions? Comments? Mail usat [email protected]

[email protected]



References I

Aristotle. The Nicomachean Ethics. Oxford University Press, ca. 350 B.C.E. (1908translation by W. D. Ross).

Matteo Bobba and Decio Coviello. Weak instruments and weak identification, inestimating the effects of education, on democracy. Economics Letters, 96(3):301–306, 2007.

Dale Carnegie. How To Win Friends And Influence People. Simon & Schuster, 1936.

Michel E. de Montaigne. Essays, chapter XXVII - Of Friendship. Project Gutenberg,1588. URL http://www.gutenberg.org/ebooks/3600. (1877 translation by C.Cotton).

Josef Falkinger. Attention economies. Journal of Economic Theory, 133(1):266–294,2007.

Andrea Galeotti and Sanjeev Goyal. The law of the few. American Economic Review,100(4):1468–1492, 2010.

Alexia Gaudeul and Chiara Peroni. Reciprocal attention and norm of reciprocity inblogging networks. Economics Bulletin, 30(3):2230–2248, 2010.


http://www.gutenberg.org/ebooks/3600


References II

Edward L. Glaeser, David Laibson, and Bruce Sacerdote. An economic approach tosocial capital. The Economic Journal, 112(483):437–458, 2002.

Alvin W. Gouldner. The norm of reciprocity: A preliminary statement. AmericanSociological Review, 25(2):161–178, 1960.

Chun-Yao Huang, Yong-Zheng Shen, Hong-Xiang Lin, and Shin-Shin Chang. Bloggers’motivations and behaviors: A model. Journal of Advertising Research, 47(4):472–484, 2007.

Ravi Kumar, Jasmine Novak, and Andrew Tomkins. Structure and evolution of onlinesocial networks. In Philip S. S. Yu, Jiawei Han, and Christos Faloutsos, editors, LinkMining: Models, Algorithms, and Applications, pages 337–357. Springer: New York,2010. ISBN 978-1-4419-6515-8.

Amanda Lenhart and Susannah Fox. Bloggers: A portrait of the Internet’s newstorytellers, 2006. URLhttp://www.pewinternet.org/Reports/2006/Bloggers.aspx. accessed October18, 2010.


http://www.pewinternet.org/Reports/2006/Bloggers.aspx


References III

Charles F Manski. Identification of endogenous social effects: The reflection problem.Review of Economic Studies, 60(3):531–42, July 1993.

Alice Marwick. LiveJournal users: Passionate, prolific and private, 2008. URLhttp://www.livejournalinc.com/LJ_Research_Report.pdf. accessed January18, 2010.

Kate Raynes-Goldie. Pulling sense out of today’s informational chaos: LiveJournal as asite of knowledge creation and sharing. First Monday, 9(12), 2004. URLhttp://firstmonday.org/issues/issue9_12/raynes/index.html.

Kate Raynes-Goldie and David Fono. Hyperfriends and beyond: Friendship and socialnorms on LiveJournal. In M. Consalvo and C. Haythornthwaite, editors, InternetResearch Annual Volume 4: Selected Papers from the Association of InternetResearchers Conference. Peter Lang: New York, USA, 2006.

David Roodman. A note on the theme of too many instruments. Oxford Bulletin ofEconomics and Statistics, 71(1):135–158, 2009.


http://www.livejournalinc.com/LJ_Research_Report.pdf

http://firstmonday.org/issues/issue9_12/raynes/index.html


References IV

Huaxia Rui and Andrew Whinston. Social media as an innovation - the case of Twitter.University of Texas at Austin, 2010.

Clay Shirky. Power laws, weblogs, and inequality, 2003. URLhttp://shirky.com/writings/powerlaw_weblog.html. accessed January 18,2010.

Herbert A. Simon. Designing organizations for an information-rich world. In MartinGreenberger, editor, Computers, Communication, and the Public Interest. The JohnsHopkins Press: Baltimore, MD, 1971.

Technorati. State of the blogosphere 2009, 2009. URLhttp://technorati.com/blogging/feature/state-of-the-blogosphere-2009.accessed October 18, 2010.

Lu Wei. Filter blogs vs. personal journals: Understanding the knowledge production gapon the Internet. Journal of Computer-Mediated Communication, 14(3):532–558,2009.


http://shirky.com/writings/powerlaw_weblog.html

http://technorati.com/blogging/feature/state-of-the-blogosphere-2009

Presentation at the 13th Annual Conference of the APET in Taiwan, 2012

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