Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones

392 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Social media data for conservation science: A methodological overview (2019, methodology): “These methods include anchor point modelling (Ahas et al., 2010) to reveal origins of social media users, space-time prisms (Neutens et al.”
Urban Building Energy Modeling (UBEM) Tools: A State-of-the-Art Review of bottom-up physics-based approaches (2020, background): “Thus, due to the advancement of the Internet of things, numerous researchers begin to exploit the data from mobile phones, and Wi-Fi sensors to estimate the spatio-temporal movement patterns of occupants in the building and within the city [104–106].”
Urban Sensing Using Mobile Phone Network Data: A Survey of Research (2014, background): “Ahas et al. [2010] and Isaacman et al. [2011] introduce a model for determining the geographical location of home and workplaces, while Nurmi and Bhattacharya [2008] describe and evaluate a nonparametric Bayesian approach for identifying places from sparse GPS traces (given the generic approach of t”
Inferring Passenger Travel Demand to Improve Urban Mobility in Developing Countries Using Cell Phone Data: A Case Study of Senegal (2016, background): “Personal use is permitted, but republication/redistribution requires IEEE permission.”
Locative media and data-driven computing experiments (2016, background): “However, getting access to a snapshot of mobile phone data is difficult, expensive and time consuming (Ahas et al., 2010).”