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Measuring serendipity
3 references·16 citing·38 second hop
Measuring serendipity (2009)Measuring serendipityUnderstanding individual human mobility patterns (2008)Understanding individual huma…The scaling laws of human travel (2006)The scaling laws of human tra…Reality mining: sensing complex social systems (2005)Reality mining: sensing compl…Attentional Markov Model for Human Mobility Prediction (2021)Attentional Markov Model for …Human Mobility Prediction Using Sparse Trajectory Data (2020)Human Mobility Prediction Usi…Automatic depression prediction using Internet traffic characteristics on smartphones (2020)Automatic depression predicti…Modeling Spatio-Temporal App Usage for a Large User Population (2019)Modeling Spatio-Temporal App …A Survey on Machine Learning‐Based Mobile Big Data Analysis: Challenges and Applications (2018)A Survey on Machine Learning‐…Not All Apps Are Created Equal (2017)Not All Apps Are Created EqualMobile app adoption in different life stages: An empirical analysis (2017)Mobile app adoption in differ…Joint spatial and temporal classification of mobile traffic demands (2017)Joint spatial and temporal cl…Inferring social influence in transport mode choice using mobile phone data (2017)Inferring social influence in…Understanding the impact of personality traits on mobile app adoption – Insights from a large-scale field study (2016)Understanding the impact of p…Mobile big-data-driven rating framework: measuring the relationship between human mobility and app usage behavior (2016)Mobile big-data-driven rating…A Tale of Ten Cities: Characterizing Signatures of Mobile Traffic in Urban Areas (2016)A Tale of Ten Cities: Charact…User mobility from the view of cellular data networks (2014)User mobility from the view o…Steps towards the Extraction of Vehicular Mobility Patterns from 3G Signaling Data (2012)Steps towards the Extraction …Are call detail records biased for sampling human mobility? (2012)Are call detail records biase…Profiling users in a 3g network using hourglass co-clustering (2010)Profiling users in a 3g netwo…Limits of Predictability in Human Mobility (2010)Mobility Viewer: An Eulerian Approach for Studying Urban Crowd Flow (2015)Survey of wireless big data (2017)Mobile Social Data Learning for User-Centric Location Prediction With Application in Mobile Edge Service Migration (2019)Exploring Millions of Footprints in Location Sharing Services (2021)The origin of bursts and heavy tails in human dynamics (2005)Friendship and mobility (2011)A universal model for mobility and migration patterns (2012)Using GPS to learn significant locations and predict movement across multiple users (2003)Learning and inferring transportation routines (2007)Social signal processing: Survey of an emerging domain (2008)Inferring friendship network structure by using mobile phone data (2009)Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology (1989)User Acceptance of Information Technology: Toward A Unified View1 (2003)Personality Traits Predict Smartphone Usage (2017)The influence of the propensity to trust on mobile users' attitudes toward in-app advertisements: An extension of the theory of planned behavior (2017)Diffusion of Innovations 1 (2019)Exploring short-form video application addiction: Socio-technical and attachment perspectives (2019)OpenStreetMap: User-Generated Street Maps (2008)Estimating Origin-Destination Flows Using Mobile Phone Location Data (2011)Discovering regions of different functions in a city using human mobility and POIs (2012)Estimation of Static and Dynamic Urban Populations with Mobile Network Metadata (2018)TRANSIT: Fine-grained human mobility trajectory inference at scale with mobile network signaling data (2021)The Varimax Criterion for Analytic Rotation in Factor Analysis (1958)A Rationale and Test for the Number of Factors in Factor Analysis (1965)Evaluating the use of exploratory factor analysis in psychological research. (1999)Can We Map-Match Individual Cellular Network Signaling Trajectories in Urban Environments? Data-Driven Study (2019)A DBSCAN-based framework to mine travel patterns from origin-destination matrices: Proof-of-concept on proxy static OD from Brisbane (2021)A Framework for the Comparative Analysis of Multi-Modal Travel Demand: Case Study on Brisbane Network (2021)The Strength of Weak Ties (1973)Birds of a Feather: Homophily in Social Networks (2001)Understanding Human Mobility Patterns in a Developing Country Using Mobile Phone Data (2019)Exploring strengths and weaknesses of mobility inference from mobile phone data vs. travel surveys (2020)A data fusion approach with mobile phone data for updating travel survey-based mode split estimates (2023)Multi-scale spatio-temporal analysis of human mobility (2017)Reconstruction of human movement trajectories from large-scale low-frequency mobile phone data (2019)Measuring objective and subjective well-being: dimensions and data sources (2020)Assembling and Using a Cellular Dataset for Mobile Network Analysis and Planning (2017)
this work references cited by second hop

References

  • 2008Understanding individual human mobility patterns6,071 cited
  • 2005Reality mining: sensing complex social systems2,771 cited
  • 2006The scaling laws of human travel2,207 cited

Cited by

  • 2016Understanding the impact of personality traits on mobile app adoption – Insights from a large-scale field study193 cited
  • 2012Are call detail records biased for sampling human mobility?124 cited
  • 2016A Tale of Ten Cities: Characterizing Signatures of Mobile Traffic in Urban Areas100 cited
  • 2010Profiling users in a 3g network using hourglass co-clustering88 cited
  • 2017Inferring social influence in transport mode choice using mobile phone data70 cited
  • 2017Joint spatial and temporal classification of mobile traffic demands54 cited
  • 2014User mobility from the view of cellular data networks53 cited
  • 2017Not All Apps Are Created Equal52 cited
  • 2018A Survey on Machine Learning‐Based Mobile Big Data Analysis: Challenges and Applications52 cited
  • 2017Mobile app adoption in different life stages: An empirical analysis40 cited
  • 2016Mobile big-data-driven rating framework: measuring the relationship between human mobility and app usage behavior38 cited
  • 2020

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Automatic depression prediction using Internet traffic characteristics on smartphones
37 cited
  • 2012Steps towards the Extraction of Vehicular Mobility Patterns from 3G Signaling Data34 cited
  • 2019Modeling Spatio-Temporal App Usage for a Large User Population33 cited
  • 2021Attentional Markov Model for Human Mobility Prediction31 cited
  • 2020Human Mobility Prediction Using Sparse Trajectory Data25 cited