Online vs. Offline Social Networks. Valerio Arnaboldi

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1 Online vs. Offline Social Networks Valerio Arnaboldi

2 Cyber-Physical World Convergence The virtual world depends upon actions in the physical world and vice-versa Information follows social relationships New requirements for communication systems Communication systems could benefit from the analysis of social networks 2/24/2015 2

Aim of the work Better understand the process behind the CPW convergence Understand how the use of social media is changing our social behavior and

3 Aim of the work Better understand the process behind the CPW convergence Understand how the use of social media is changing our social behavior and capacity Comparison between the structure of Online and Offline Social Networks Micro-level approach point of view of single individuals 2/23/2015 3

Ego Networks (offline) Cognitive and time constraints shape human ego networks Ego networks properties are unknown in OSNs Comparison between offline and online ego networks

1, pp. 53 72, Mar. 2003. W.-X. Zhou, D. Sornette, R. A. Hill, and R. I. M. Dunbar, Discrete hierarchical organization of social group sizes. in Biological sciences, vol. 272, no.

4 Ego Networks (offline) Cognitive and time constraints shape human ego networks Ego networks properties are unknown in OSNs Comparison between offline and online ego networks essential to understand how human social behavior is influenced by the use of OSNs R. A. Hill and R. I. M. Dunbar, Social network size in humans, Human Nature, vol. 14, no. 1, pp , Mar W.-X. Zhou, D. Sornette, R. A. Hill, and R. I. M. Dunbar, Discrete hierarchical organization of social group sizes. in Biological sciences, vol. 272, no. 1561, 2005, pp S. Roberts and R. Dunbar. Communication in social networks: Effects of kinship, network size, and emotional closeness. Personal Relationships, /23/2015 4

5 Experimental Data Facebook Publicly available data set containing more than 3 million users and 23 million social links between them Subsample of a Facebook regional network ego networks are incomplete Number of direct posts or photo comment between users Twitter Roughly 2.5 million user profiles crawled Profile data and tweets (up to 3,200 per user) Direct interactions through mentions and reply tags Complete ego networks 2/23/2015 6

Socially Relevant Users in Twitter Twitter users are less homogeneous than Facebook users Twitter is more used for public communication Only some accounts are used by people for maintaining social

6 Socially Relevant Users in Twitter Twitter users are less homogeneous than Facebook users Twitter is more used for public communication Only some accounts are used by people for maintaining social relationships with others We classified users in two classes using a manually trained SVM B. Goncalves, N. Perral, and A. Vespignani, Modeling Users Activity on Twitter Networks: Validation of Dunbar s Number, PLoS ONE, vol. 6, no. 8, Aug V. Arnaboldi, M. Conti, A. Passarella, F. Pezzoni, Ego Networks in Twitter: an Experimental Analysis, NetSciCom, /23/2015 8

7 Finding the Optimal Number of Circles in OSN Ego Networks K-means and DBSCAN on the contact frequencies between egos and their alters Best configuration (k) selected using Akaike Information Criterion (AIC) V. Arnaboldi, M. Conti, A. Passarella, F. Pezzoni, Analysis of Ego Networks in online Social Networks, Socialcom, /23/2015 9

8 The Structure of Ego Networks in Facebook and Twitter Ego Network Circle C1 C2 C3 C4 C5 Facebook Size - (4.70) (15.31) (44.77) (132.5) Sc. factor Cont. freq Twitter Size Sc. factor Cont. freq Offline Size Sc. factor Cont. freq /24/

9 Ego Networks Evolution Over Time Ego networks are not static! From previous analyses on phone call networks we already know that there is a turnover among alters: Some friends are abandoned to make room for new ones The number of alters actively maintained over time is limited to the Dunbar's number Also inner circles (close friends) are affected by turnover 2/23/

10 Number of New Contacts over Time The communication history of each user is shifted to start from the same point in time (origin) People add new contacts in their social networks at a nearly constant rate 2/23/

11 Ego Network Circles Evolution The number of contacts actively maintained is limited by cognitive constraints Different behavior: Initial boost followed by decay or slow start followed by more stable activity 2/23/

12 Turnover in Ego Networks Jaccard coefficient over consecutive (but not overlapped) 1-year windows Ego networks with at least 2 years of communications Very high turnover (low Jaccard) Structured networks show turnover similar to face-to-face networks Turnover also affects support cliques Circle Occasional users Regular users All ego networks Aficionados Active network Sympathy group Support clique Structured ego networks Active network Sympathy group Support clique /23/

13 Conclusion Ego network structure in OSN is similar to the one observed in offline environments OSN are not changing the fundamental properties of our personal social networks, that are instead controlled by the constrained nature of our brain OSN could change our social behavior, but not our social capacity New inner circle found thanks to the accuracy of OSN data Ego networks in OSN are more dynamic than in offline environments (mediated by more traditional communication means) Easier to make new friends and to abandon old ones OSN seem perfect tools for a highly dynamic society 2/23/

14 Thank you!

Dynamics of personal social relationships in Online Social Networks: a study on Twitter

Dynamics of personal social relationships in Online Social Networks: a study on Twitter Valerio Arnaboldi, Marco Conti, Andrea Passarella, Robin Dunbar valerio.arnaboldi@iit.cnr.it Social Lives vs. Social