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Application of Mobile Signaling Data in Determining the Seismic Influence Field: A Case Study of the 2017 Mw 6.5 Jiuzhaigou Earthquake, China
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Application of Mobile Signaling Data in Determining the Seismic Influence Field: A Case Study of the 2017 Mw 6.5 Jiuzhaigou Earthquake, China (2022)Application of Mobile Signaling Data in D…Social media and disaster management: Case of the north and south Kivu regions in the Democratic Republic of the Congo (2020)Social media and disaster man…Social media for intelligent public information and warning in disasters: An interdisciplinary review (2019)Social media for intelligent …Modeling real-time human mobility based on mobile phone and transportation data fusion (2018)Modeling real-time human mobi…Estimation of urban crowd flux based on mobile phone location data: A case study of Beijing, China (2018)Estimation of urban crowd flu…Emergency information diffusion on online social media during storm Cindy in U.S. (2018)Emergency information diffusi…Risk assessment of people trapped in earthquake based on km grid: a case study of the 2014 Ludian earthquake, China (2017)Risk assessment of people tra…Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns (2017)Coupling mobile phone and soc…Rapid and near Real-time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake (2016)Rapid and near Real-time Asse…Digitally enabled disaster response: the emergence of social media as boundary objects in a flooding disaster (2016)Digitally enabled disaster re…Quantifying seasonal population fluxes driving rubella transmission dynamics using mobile phone data (2015)Quantifying seasonal populati…Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan (2015)Analysis of spatio-temporal m…Social media in Saudi Arabia: Exploring its use during two natural disasters (2014)Social media in Saudi Arabia:…A new insight into land use classification based on aggregated mobile phone data (2014)A new insight into land use c…Predictability of population displacement after the 2010 Haiti earthquake (2012)Predictability of population …Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti (2011)Improved Response to Disaster…Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake (2010)Emergency knowledge managemen…Determination of most affected areas by earthquakes based on mobile signaling data: a case study of the 2022 Mw 6.6 Luding earthquake, China (2023)Determination of most affecte…Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)From mobile phone data to the spatial structure of cities (2014)Extracting urban functional regions from points of interest and human activities on location‐based social networks (2017)Power-Law Distributions in Empirical Data (2009)A survey of results on mobile phone datasets analysis (2015)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Power-law distributions in empirical data (2018)Social physics (2022)Measuring the information society (1989)Volunteered Geographic Information and Crowdsourcing Disaster Relief: A Case Study of the Haitian Earthquake (2010)Applications of artificial intelligence for disaster management (2020)Transforming Qualitative Information: Thematic Analysis and Code Development (1998)Qualitative research & evaluation methods (2002)Is There Social Capital in a Social Network Site?: Facebook Use and College Students' Life Satisfaction, Trust, and Participation (2009)Public perception and attitudes to disaster risks in a coastal metropolis of Saudi Arabia (2019)When Is It Democratic to Postpone an Election? Elections During Natural Disasters, COVID-19, and Emergency Situations (2020)Polarization and social media: A systematic review and research agenda (2022)Communities of practice learning, meaning, and identity (1999)Transferring, Translating, and Transforming: An Integrative Framework for Managing Knowledge Across Boundaries (2004)Social Media in Disaster Risk Reduction and Crisis Management (2013)Social network analysis: Characteristics of online social networks after a disaster (2017)Detection and Resolution of Rumours in Social Media (2018)Dynamic population mapping using mobile phone data (2014)Big Data in Natural Disaster Management: A Review (2018)Spatial variations in urban public ridership derived from GPS trajectories and smart card data (2018)Portraying the spatial dynamics of urban vibrancy using multisource urban big data (2019)Multiscale dynamic human mobility flow dataset in the U.S. during the COVID-19 epidemic (2020)The Geography of Transport Systems (2020)Empirical study of topic modeling in Twitter (2010)Predicting the Present with Google Trends (2012)Social Capital and Community Resilience (2014)Social media data and post-disaster recovery (2018)Impact of corporate social responsibility on reputation—Insights from tweets on sustainable development goals by CEOs (2019)Retweets of officials’ alarming vs reassuring messages during the COVID-19 pandemic: Implications for crisis management (2020)The scaling laws of human travel (2006)Extracting trips from multi-sourced data for mobility pattern analysis: An app-based data example (2019)New and emerging data forms in transportation planning and policy: Opportunities and challenges for “Track and Trace” data (2020)Interactive COVID-19 Mobility Impact and Social Distancing Analysis Platform (2021)Advances in Social Media Research: Past, Present and Future (2017)Social media in marketing: A review and analysis of the existing literature (2017)Disaster City Digital Twin: A vision for integrating artificial and human intelligence for disaster management (2019)Why do small and medium enterprises use social media marketing and what is the impact: Empirical insights from India (2020)Natural Disasters—Origins, Impacts, Management (2021)
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References

  • 2010Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake874 cited
  • 2011Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti634 cited
  • 2012Predictability of population displacement after the 2010 Haiti earthquake633 cited
  • 2014A new insight into land use classification based on aggregated mobile phone data399 cited
  • 2017Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns298 cited
  • 2019Social media for intelligent public information and warning in disasters: An interdisciplinary review293 cited
  • 2016Rapid and near Real-time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake179 cited
  • 2018Emergency information diffusion on online social media during storm Cindy in U.S.166 cited
  • 2018Modeling real-time human mobility based on mobile phone and transportation data fusion150 cited
  • 2014Social media in Saudi Arabia: Exploring its use during two natural disasters142 cited
  • 2016Digitally enabled disaster response: the emergence of social media as boundary objects in a flooding disaster141 cited
  • 2015Quantifying seasonal population fluxes driving rubella transmission dynamics using mobile phone data137 cited
  • 2020Social media and disaster management: Case of the north and south Kivu regions in the Democratic Republic of the Congo

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96 cited
  • 2018Estimation of urban crowd flux based on mobile phone location data: A case study of Beijing, China46 cited
  • 2015Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan41 cited
  • 2017Risk assessment of people trapped in earthquake based on km grid: a case study of the 2014 Ludian earthquake, China41 cited
  • Cited by

    • 2023Determination of most affected areas by earthquakes based on mobile signaling data: a case study of the 2022 Mw 6.6 Luding earthquake, China3 cited