Geographic aspects of tie strength and value of information in social networking

Relations between the dimension of social tie strength and the dimension of value of communicated information have been investigated in the past by researchers such as Mark Granovetter. Also the connection between spatial distance and the existence of ties in social networks with small world characteristics has been discussed by Liben-Nowell and others. In this contribution we aim at investigating the relation between the dimensions spatial distance and non-binary, continuous value of information. Furthermore, we discuss the connection between non-binary, continuous measures for value of information and the dimension of non-binary social, continuous measures of tie strength. We also especially investigate the interrelation between all three dimensions in Social Networking and especially the research question of whether a spatial dependency of the inverse relation between social tie strength and value of information exists which may be named 'Geo-Granovetter effect'. As a basis for our empirical investigations we used a large Twitter dataset, because this Social Medium allows us to simultaneously access spatial, social and informational dimensions of interaction and thus to simultaneously model these three dimensions for Social Networking. We found that the social tie strength decreases as expected with increasing spatial distance among participants in our data-set. We also observed that in general the information value decreases when the tie strength increases and that the value of information is independent from the distance. According to our findings, Social Media such as Twitter don't exhibit a Geo-Granovetter effect.

[1]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[2]  Cecilia Mascolo,et al.  Far from the eyes, close on the web: impact of geographic distance on online social interactions , 2012, WOSN '12.

[3]  Yehuda Koren,et al.  Advances in Collaborative Filtering , 2011, Recommender Systems Handbook.

[4]  Georg Groh,et al.  Spatio-temporal small worlds for decentralized information retrieval in social networking , 2012, SIGSPATIAL/GIS.

[5]  Jafar Adibi,et al.  The Enron Email Dataset Database Schema and Brief Statistical Report , 2004 .

[6]  Andrew McCallum,et al.  Topic and Role Discovery in Social Networks with Experiments on Enron and Academic Email , 2007, J. Artif. Intell. Res..

[7]  David Barber,et al.  Bayesian reasoning and machine learning , 2012 .

[8]  Tefko Saracevic.  Relevance: A review of the literature and a framework for thinking on the notion in information science. Part III: Behavior and effects of relevance , 2007 .

[9]  Mark S. Granovetter.  Getting a Job: A Study of Contacts and Careers , 1974 .

[10]  Brendan T. O'Connor,et al.  TweetMotif: Exploratory Search and Topic Summarization for Twitter , 2010, ICWSM.

[11]  Christopher D. Manning,et al.  Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..

[12]  Thomas L. Griffiths,et al.  Learning author-topic models from text corpora , 2010, TOIS.

[13]  K. Axhausen,et al.  Size and structure of social network geographies , 2007 .

[14]  Peter Harremoës,et al.  Properties of Classical and Quantum Jensen-Shannon Divergence , 2009 .

[15]  P. Harremoes,et al.  Properties of Classical and Quantum Jensen-Shannon Divergence , 2008, 0806.4472.

[16]  Mark S. Granovetter.  The Strength of Weak Ties , 1973, American Journal of Sociology.

[17]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[18]  Jaime Teevan,et al.  Implicit feedback for inferring user preference: a bibliography , 2003, SIGF.

[19]  Alessandro Micarelli,et al.  User Profiles for Personalized Information Access , 2007, The Adaptive Web.

[20]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[21]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[22]  Stefano Mizzaro,et al.  Relevance: The Whole History , 1997, J. Am. Soc. Inf. Sci..

[23]  Seungyeop Han,et al.  Analysis of topological characteristics of huge online social networking services , 2007, WWW '07.

[24]  Barry Wellman,et al.  Did distance matter before the Internet?: Interpersonal contact and support in the 1970s , 2007, Soc. Networks.

[25]  Andrew McCallum,et al.  Topic and Role Discovery in Social Networks , 2005, IJCAI.

[26]  Yunjie Calvin Xu,et al.  Relevance judgment: What do information users consider beyond topicality? , 2006, J. Assoc. Inf. Sci. Technol..

[27]  Cecilia Mascolo,et al.  Socio-Spatial Properties of Online Location-Based Social Networks , 2011, ICWSM.

[28]  Alfred Kobsa,et al.  Generic User Modeling Systems , 2001, User Modeling and User-Adapted Interaction.

[29]  N. Milburn.  To Dwell Among Friends: Personal Networks in Town and City. , 1983 .

[30]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[31]  Eric Gilbert,et al.  Predicting tie strength with social media , 2009, CHI.

[32]  Yunjie Xu,et al.  Relevance judgment: What do information users consider beyond topicality? , 2006 .

[33]  Jasmine Novak,et al.  Geographic routing in social networks , 2005, Proc. Natl. Acad. Sci. USA.

[34]  Pasquale Lops,et al.  Content-based Recommender Systems: State of the Art and Trends , 2011, Recommender Systems Handbook.

[35]  Eric Gilbert,et al.  Predicting tie strength in a new medium , 2012, CSCW.

[36]  Lars Backstrom,et al.  Find me if you can: improving geographical prediction with social and spatial proximity , 2010, WWW '10.

[37]  George Karypis,et al.  A Comprehensive Survey of Neighborhood-based Recommendation Methods , 2011, Recommender Systems Handbook.

[38]  David Liben-Nowell,et al.  Wayfinding in Social Networks , 2010, Algorithms for Next Generation Networks.

[39]  Charles L. A. Clarke,et al.  Novelty and diversity in information retrieval evaluation , 2008, SIGIR '08.

[40]  Michel Grossetti,et al.  Are French networks different? , 2007, Soc. Networks.

[41]  Georg Groh.  Contextual Social Networking , 2011 .

[42]  C. Domeniconi,et al.  The Role of Semantic History on Online Generative Topic Modeling , 2009 .

[43]  Nan Lin,et al.  Analyzing the Instrumental Use of Relations in the Context of Social Structure , 1978 .

[44]  P. V. Marsden,et al.  Measuring Tie Strength , 1984 .

[45]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[46]  Cecilia Mascolo,et al.  Distance Matters: Geo-social Metrics for Online Social Networks , 2010, WOSN.