The SocioMetric Badges Corpus: A Multilevel Behavioral Dataset for Social Behavior in Complex Organizations

This paper presents the SocioMetric Badges Corpus, a new corpus for social interaction studies collected during a 6 weeks contiguous period in a research institution, monitoring the activity of 53 people. The design of the corpus was inspired by the need to provide researchers and practitioners with: a) raw digital trace data that could be used to directly address the task of investigating, reconstructing and predicting people's actual social behavior in complex organizations, b) information about participants' individual characteristics (e.g., personality traits), along with c) data concerning the general social context (e.g., participants' social networks) and the specific situations they find themselves in.

[1]  K. Heil.  Please! , 1924, The Hospital and Health Review.

[2]  Miss A.O. Penney.  (b) , 1974, The New Yale Book of Quotations.

[3]  P. Killworth,et al.  Informant accuracy in social network data III: A comparison of triadic structure in behavioral and cognitive data , 1979 .

[4]  A. Tellegen.  Brief manual for the Differential Personality Questionnaire , 1982 .

[5]  D. Watson,et al.  Development and validation of brief measures of positive and negative affect: the PANAS scales. , 1988, Journal of personality and social psychology.

[6]  J. R. Larson,et al.  Research strategies and tactics in industrial and organizational psychology. , 1990 .

[7]  Owen Daly-Jones,et al.  Informal workplace communication: what is it like and how might we support it? , 1994, CHI '94.

[8]  W. Fleeson.  Toward a structure- and process-integrated view of personality: traits as density distribution of states. , 2001, Journal of personality and social psychology.

[9]  V. Akila,et al.  Information , 2001, The Lancet.

[10]  S. Donaldson,et al.  Understanding Self-Report Bias in Organizational Behavior Research , 2002 .

[11]  L. D. Blas,et al.  L’approccio psicolessicale nella lingua italiana: Due studi tassonomici a confronto , 2002 .

[12]  M. Perugini,et al.  The Big Five Marker Scales (BFMS) and the Italian AB5C taxonomy: Analyses from an emic-etic perspective , 2002 .

[13]  P. Costa,et al.  Factorial and construct validity of the Italian Positive and Negative Affect Schedule (PANAS). , 2003, European journal of psychological assessment : official organ of the European Association of Psychological Assessment.

[14]  S. Gosling,et al.  A very brief measure of the Big-Five personality domains , 2003 .

[15]  J. Henry,et al.  The positive and negative affect schedule (PANAS): construct validity, measurement properties and normative data in a large non-clinical sample. , 2004, The British journal of clinical psychology.

[16]  T. Judge,et al.  Affect and job satisfaction: a study of their relationship at work and at home. , 2004, The Journal of applied psychology.

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

[18]  W. Fleeson.  Situation-based contingencies underlying trait-content manifestation in behavior. , 2007, Journal of personality.

[19]  Benjamin N. Waber,et al.  Mining Face-to-Face Interaction Networks Using Sociometric Badges: Evidence Predicting Productivity in IT Configuration , 2008 .

[20]  Alex Pentland,et al.  Mining Face-to-Face Interaction Networks using Sociometric Badges: Predicting Productivity in an IT Configuration Task , 2008, ICIS.

[21]  Albert-László Barabási,et al.  Understanding individual human mobility patterns , 2008, Nature.

[22]  Alex Pentland,et al.  Wearable sensors for pervasive healthcare management , 2009, 2009 3rd International Conference on Pervasive Computing Technologies for Healthcare.

[23]  Alex Pentland,et al.  Sensible Organizations: Technology and Methodology for Automatically Measuring Organizational Behavior , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[24]  A. Pentland,et al.  Computational Social Science , 2009, Science.

[25]  Subramanian Ramanathan,et al.  Employing social gaze and speaking activity for automatic determination of the Extraversion trait , 2010, ICMI-MLMI '10.

[26]  Alex Pentland,et al.  Social sensing for epidemiological behavior change , 2010, UbiComp.

[27]  D. Gática-Pérez,et al.  Towards rich mobile phone datasets: Lausanne data collection campaign , 2010 .

[28]  Ciro Cattuto,et al.  Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks , 2010, PloS one.

[29]  Nicu Sebe,et al.  Please, tell me about yourself: automatic personality assessment using short self-presentations , 2011, ICMI '11.

[30]  Alex Pentland,et al.  Modeling the co-evolution of behaviors and social relationships using mobile phone data , 2011, MUM.

[31]  T. Judge,et al.  A within‐individual study of interpersonal conflict as a work stressor: Dispositional and situational moderators , 2011 .

[32]  Subramanian Ramanathan,et al.  Automatic modeling of personality states in small group interactions , 2011, MM '11.

[33]  Nicu Sebe,et al.  Friends don't lie: inferring personality traits from social network structure , 2012, UbiComp.