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Complementing Travel Diary Surveys with Twitter Data: Application of Text Mining Techniques on Activity Location, Type and Time
7 references·12 citing·46 second hop
Complementing Travel Diary Surveys with Twitter Data: Application of Text Mining Techniques on Activity Location, Type and Time (2015)Complementing Travel Diary Surveys with T…Exploring Social-Historical Ties on Location-Based Social Networks (2021)Exploring Social-Historical T…Urban activity pattern classification using topic models from online geo-location data (2014)Urban activity pattern classi…Understanding urban human activity and mobility patterns using large-scale location-based data from online social media (2013)Understanding urban human act…Exploring temporal effects for location recommendation on location-based social networks (2013)Exploring temporal effects fo…Using Social Media to Enhance Emergency Situation Awareness (2012)Using Social Media to Enhance…Emergency situation awareness from twitter for crisis management (2012)Emergency situation awareness…Understanding attitudes towards public transport and private car: A qualitative study (2007)Understanding attitudes towar…A multi-modal social media data analysis framework: Exploring the complex relationships among urban environment, public activity, and public perception—A case study of Xi’an, China (2025)A multi-modal social media da…Horizon 2020 Project Analysis by Using Topic Modelling Techniques in the Field of Transport (2024)Horizon 2020 Project Analysis…Explaining and Predicting Station Demand Patterns Using Google Popular Times Data (2023)Explaining and Predicting Sta…Feasibility of estimating travel demand using geolocations of social media data (2021)Feasibility of estimating tra…Effects of the autonomous vehicle crashes on public perception of the technology (2021)Effects of the autonomous veh…Recent Progress in Activity-Based Travel Demand Modeling: Rising Data and Applicability (2020)Recent Progress in Activity-B…Investigating Dominant Trip Distance for Intercity Passenger Transport Mode Using Large-Scale Location-Based Service Data (2019)Investigating Dominant Trip D…Destination choice modeling using location-based social media data (2019)Destination choice modeling u…Can Tourist Attractions Boost Other Activities Around? A Data Analysis through Social Networks (2019)Can Tourist Attractions Boost…Utilizing Social Media in Transport Planning and Public Transit Quality: Survey of Literature (2018)Utilizing Social Media in Tra…Geolocation prediction in social media data using text analysis: A review (2018)Geolocation prediction in soc…Transportation application of social media: Travel mode extraction (2016)Transportation application of…Friendship and mobility (2011)Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges (2016)Location-based advertising on mobile devices (2016)A Neural Network Approach to Jointly Modeling Social Networks and Mobile Trajectories (2017)An Empirical Study of Geographic User Activity Patterns in Foursquare (2021)Exploring Millions of Footprints in Location Sharing Services (2021)Discovering themes and trends in transportation research using topic modeling (2017)Social-media data for urban sustainability (2018)Applications of artificial intelligence for disaster management (2020)Predicting Depression via Social Media (2021)The theory of planned behavior (1991)Basics of qualitative research : techniques and procedures for developing grounded theory (1998)A methodology for evaluating transit service quality based on subjective and objective measures from the passenger’s point of view (2010)Travel and Subjective Well-Being: A Focus on Findings, Methods and Future Research Needs (2013)The happy commuter: A comparison of commuter satisfaction across modes (2014)The Discovery of Grounded Theory (2017)The scaling laws of human travel (2006)Understanding individual human mobility patterns (2008)Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China (2018)Nonlinear and synergistic effects of TOD on urban vibrancy: Applying local explanations for gradient boosting decision tree (2021)The Death of Distance: How the Communications Revolution Will Change Our Lives (1997)Understanding mobility based on GPS data (2008)Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data (2014)A Survey of Location Prediction on Twitter (2018)Toward a Theory of Situation Awareness in Dynamic Systems (1995)Geographic Situational Awareness: Mining Tweets for Disaster Preparedness, Emergency Response, Impact, and Recovery (2015)Social media analytics for natural disaster management (2017)Social Media in Crisis Management: An Evaluation and Analysis of Crisis Informatics Research (2018)Microblogging during two natural hazards events (2010)Social network analysis: Characteristics of online social networks after a disaster (2017)Detection and Resolution of Rumours in Social Media (2018)Users of the world, unite! The challenges and opportunities of Social Media (2009)Social media? Get serious! Understanding the functional building blocks of social media (2011)Mine Your Own Business: Market-Structure Surveillance Through Text Mining (2012)Spatiotemporal Analysis to Observe Gender Based Check-In Behavior by Using Social Media Big Data: A Case Study of Guangzhou, China (2019)Fusing Mobile Phone and Travel Survey Data to Model Urban Activity Dynamics (2020)Investigating transportation research based on social media analysis: a systematic mapping review (2021)The P 1 P 2 D Hypothesis: On the Intercity Movement of Persons (1946)Limits of Predictability in Human Mobility (2010)Rapidex: A Novel Tool to Estimate Origin–Destination Trips Using Pervasive Traffic Data (2021)Airport terminal passenger forecast under the impact of COVID-19 outbreaks: A case study from China (2022)Flow count data-driven static traffic assignment models through network modularity partitioning (2023)Collecting Social Network Data to Study Social Activity-Travel Behavior: An Egocentric Approach (2007)A Survey of Public Opinion about Autonomous and Self-Driving Vehicles in the U.S., the U.K., and Australia (2014)Public Opinion on Automated Driving: Results of an International Questionnaire Among 5,000 Respondents (2014)What is the public really concerned about the AV crash? 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this work references cited by second hop

References

  • 2007Understanding attitudes towards public transport and private car: A qualitative study1,200 cited
  • 2012Using Social Media to Enhance Emergency Situation Awareness649 cited
  • 2013Exploring temporal effects for location recommendation on location-based social networks522 cited
  • 2013Understanding urban human activity and mobility patterns using large-scale location-based data from online social media315 cited
  • 2014Urban activity pattern classification using topic models from online geo-location data289 cited
  • 2012Emergency situation awareness from twitter for crisis management269 cited
  • 2021Exploring Social-Historical Ties on Location-Based Social Networks246 cited

Cited by

  • 2021Effects of the autonomous vehicle crashes on public perception of the technology82 cited
  • 2018Utilizing Social Media in Transport Planning and Public Transit Quality: Survey of Literature40 cited
  • 2021Feasibility of estimating travel demand using geolocations of social media data30 cited
  • 2018Geolocation prediction in social media data using text analysis: A review28 cited
  • 2016Transportation application of social media: Travel mode extraction23 cited
  • 2020Recent Progress in Activity-Based Travel Demand Modeling: Rising Data and Applicability22 cited
  • 2019Destination choice modeling using location-based social media data

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21 cited
  • 2019Can Tourist Attractions Boost Other Activities Around? A Data Analysis through Social Networks15 cited
  • 2025A multi-modal social media data analysis framework: Exploring the complex relationships among urban environment, public activity, and public perception—A case study of Xi’an, China14 cited
  • 2019Investigating Dominant Trip Distance for Intercity Passenger Transport Mode Using Large-Scale Location-Based Service Data14 cited
  • 2023Explaining and Predicting Station Demand Patterns Using Google Popular Times Data11 cited
  • 2024Horizon 2020 Project Analysis by Using Topic Modelling Techniques in the Field of Transport3 cited