Predicting social networks and psychological outcomes through mobile phone sensing

Proliferation of mobile phones over the last decade has led to innovative methods for studying social behavior and friendship patterns. Our present study combined advanced mobile phone technologies, such as Bluetooth scanning and automated pushing surveys, with self-reported questionnaires to examine the social structure and psychological well-being of college students. We distributed smartphones to 35 first-year undergraduate students to use everyday over one academic term (three months) and asked them to complete questionnaires on language background, loneliness, adaptation to college life, feelings of community cohesion, and friendship ties. Results suggested that behavioral networks in physical co-location, obtained using our mobile phone sensing techniques, reliably inferred real reported friendships. In addition, mobile phone usage, such as calling and SMS, were significantly correlated with psychological well-being in terms of feelings of loneliness, sense of community cohesion and adaptation to college life. Finally, results revealed that activities in the mobile phone social network, in particular SMS, may influence students' language use, such that students tended to adapt their language behavior to match that of their SMS partners.

[1]  Mathieu Bastian,et al.  Gephi: An Open Source Software for Exploring and Manipulating Networks , 2009, ICWSM.

[2]  A. P. Rovai.  Development of an instrument to measure classroom community , 2002, Internet High. Educ..

[3]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[4]  R. Merton.  The Matthew Effect in Science , 1968, Science.

[5]  Yu Gu,et al.  WiFi Fingerprint Localization in Open Space , 2013, LCN 2013.

[6]  Mika Raento,et al.  Smartphones , 2009 .

[7]  A-L Barabási,et al.  Structure and tie strengths in mobile communication networks , 2006, Proceedings of the National Academy of Sciences.

[8]  C. Steglich,et al.  Applying SIENA: An illustrative analysis of the co-evolution of adolescents’ friendship networks, taste in music, and alcohol consumption , 2006 .

[9]  D. Russell.  UCLA Loneliness Scale (Version 3): reliability, validity, and factor structure. , 1996, Journal of personality assessment.

[10]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[11]  Noah E. Friedkin.  A Structural Theory of Social Influence: Measures of the Theoretical Constructs , 1998 .

[12]  David Lazer,et al.  Inferring friendship network structure by using mobile phone data , 2009, Proceedings of the National Academy of Sciences.

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

[14]  Alex Pentland,et al.  Reality mining: sensing complex social systems , 2006, Personal and Ubiquitous Computing.

[15]  Andrew T. Campbell,et al.  From Smart to Cognitive Phones , 2012, IEEE Pervasive Computing.

[16]  Ruth M. Ripley,et al.  Manual for RSiena , 2011 .

[17]  A. Barabasi,et al.  Network effects in service usage , 2006, physics/0611177.

[18]  N. Christakis,et al.  Alone in the Crowd: The Structure and Spread of Loneliness in a Large Social Network , 2009 .

[19]  PATRICK DOREIAN,et al.  Network Autocorrelation Models , 1984 .

[20]  Tom A. B. Snijders,et al.  Introduction to stochastic actor-based models for network dynamics , 2010, Soc. Networks.

[21]  Stephanie M. Reich,et al.  Online and Offline Social Networks: Use of Social Networking Sites by Emerging Adults , 2008 .

[22]  Noah E. Friedkin,et al.  A Structural Theory of Social Influence: List of Tables and Figures , 1998 .

[23]  N. Christakis,et al.  Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study , 2008, BMJ : British Medical Journal.

[24]  Martin G. Everett,et al.  Analyzing social networks , 2013 .

[25]  Noah E. Friedkin,et al.  A Structural Theory of Social Influence: List of Tables and Figures , 1998 .