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GroupUs: Smartphone Proximity Data and Human Interaction Type Mining
6 references·8 citing·39 second hop
GroupUs: Smartphone Proximity Data and Human Interaction Type Mining (2011)GroupUs: Smartphone Proximity Data and Hu…Towards rich mobile phone datasets: Lausanne data collection campaign (2010)Towards rich mobile phone dat…Inferring friendship network structure by using mobile phone data (2009)Inferring friendship network …What did you do today? (2008)What did you do today?Reality mining: sensing complex social systems (2005)Reality mining: sensing compl…Using GPS to learn significant locations and predict movement across multiple users (2003)Using GPS to learn significan…Social net (2002)Social netPassive social sensing with smartphones: a systematic review (2022)Passive social sensing with s…TeamSense (2018)TeamSenseJoint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning (2018)Joint Modeling of Heterogeneo…Validation of a smartphone app to map social networks of proximity (2017)Validation of a smartphone ap…CommSense: Identify Social Relationship with Phone Contacts via Mining Communications (2015)CommSense: Identify Social Re…Smartphone bluetooth based social sensing (2013)Smartphone bluetooth based so…A probabilistic approach to mining mobile phone data sequences (2013)A probabilistic approach to m…Extracting Mobile Behavioral Patterns with the Distant N-Gram Topic Model (2012)Extracting Mobile Behavioral …The Museum Wearable: real-time sensor-driven understanding of visitors' interests for personalized visually-augmented museum experiences (2002)Understanding mobility based on GPS data (2008)Uncovering individual and collective human dynamics from mobile phone records (2008)Understanding individual human mobility patterns (2008)Empirical Big Data Research: A Systematic Literature Mapping (2015)A Probabilistic Lifestyle-Based Trajectory Model for Social Strength Inference from Human Trajectory Data (2016)Group travel behavior in metro system and its relationship with house price (2021)Learning and inferring transportation routines (2007)Social signal processing: Survey of an emerging domain (2008)Limits of Predictability in Human Mobility (2010)Psychological status of the script concept. (1981)Computational Social Science (2009)Dynamics of Dyads in Social Networks: Assortative, Relational, and Proximity Mechanisms (2010)Friendship and mobility (2011)Human mobility: Models and applications (2018)Eigenbehaviors: identifying structure in routine (2009)By their apps you shall understand them (2010)Probabilistic Mining of Socio-Geographic Routines From Mobile Phone Data (2010)Mining smartphone data for app usage prediction and recommendations: A survey (2017)The PHQ-9 (2001)The 16-Item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression (2003)StudentLife (2014)Investigating Rhythmicity in App Usage to Predict Depressive Symptoms: Protocol for Personalized Framework Development and Validation Through a Countrywide Study (2024)Using Mobile Daily Mood and Anxiety Self-ratings to Predict Depression Symptom Improvement (2024)Smartphone Data Gathered Early in Depression Treatment Predicts Treatment Outcome (2025)A Multimodal Database for Affect Recognition and Implicit Tagging (2011)DEAP: A Database for Emotion Analysis ;Using Physiological Signals (2011)A Global Measure of Perceived Stress (1983)UCLA Loneliness Scale (Version 3): Reliability, Validity, and Factor Structure (1996)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Acceptability and experience of a smartphone symptom monitoring app for people with psychosis in China (YouXin): a qualitative study (2024)Evaluating a smartphone-based symptom self-monitoring app for psychosis in China (YouXin): A non-randomised validity and feasibility study with a mixed-methods design (2024)Smartphone-Based Digital Phenotyping Across Health Conditions: Scoping Review (2026)Machine perception and learning of complex social systems (2005)Automatic mapping and modeling of human networks (2006)Learning to rank for spatiotemporal search (2013)Discovering routines from large-scale human locations using probabilistic topic models (2011)Who's Who with Big-Five: Analyzing and Classifying Personality Traits with Smartphones (2011)A survey on deep learning for human mobility (2023)
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References

  • 2005Reality mining: sensing complex social systems2,771 cited
  • 2009Inferring friendship network structure by using mobile phone data1,858 cited
  • 2003Using GPS to learn significant locations and predict movement across multiple users1,060 cited
  • 2010Towards rich mobile phone datasets: Lausanne data collection campaign278 cited
  • 2002Social net122 cited
  • 2008What did you do today?120 cited

Cited by

  • 2018Joint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning85 cited
  • 2018TeamSense52 cited
  • 2013A probabilistic approach to mining mobile phone data sequences35 cited
  • 2022Passive social sensing with smartphones: a systematic review29 cited
  • 2012Extracting Mobile Behavioral Patterns with the Distant N-Gram Topic Model25 cited
  • 2017Validation of a smartphone app to map social networks of proximity25 cited
  • 2013Smartphone bluetooth based social sensing24 cited
  • 2015CommSense: Identify Social Relationship with Phone Contacts via Mining Communications5 cited

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