Preliminary Program

Preliminary Program

 

July 1, 2017

13:30 – 13:40  Welcome
 

13:40 -15:20

 

 Session 1  Theories and Data Models

 Session chair:

Bin Jiang , University of Gävle, Sweden
A Topological Representation for Predicting Human Activities using Big Data

Haiyun Ye and Keith Clarke
Spatial, Temporal, and Thematic Structure of Volunteered Geographic Information in Social Media Following Different Catastrophic Events

Thomas Gründemann and Dirk Burghardt
Event-Oriented Taxonomy of Users in Location Based Social Networks

Paul Goodhue and Ioannis Delikostidis
Modelling Information Quality and Source Reliability to Improve the Trust Of Volunteered Geographic Information

15:20 – 15:50 Coffee break 
15:50 – 17:55

 

 

 

 

 

 Session 2. Participation and User Tasks

Session Chair:

MatthewTenney, G, B. Hall and Renee Sieber
Machines Learning to Engage: Citizens’ Geosocial Media to City Participation

Ayberk Kocatepe,Mehmet Baran Ulak Ulak, Javier Lores, Eren Erman Ozguven and Anil Yazici
Assessing the Factors that Affect the Public Engagement with Department of Transportation Twitter Accounts

Jayakrishnan Ajayakumar
Spatio-temporal analysis of public response through Social media during extreme events

Marcela Suarez and Keith Clarke
Leveraging Spatio-Temporal Information to Enrich Thematic Clustering of Twitter Posts

18: 30 – as your wish      Optional Group Dinner

July 2nd

8:30 – 10:10 Session 3. Traffic Modelling

Session chair:

Yi Cheng, Haosheng Huang, Oliver Burkhard and Robert Weibel
Does Considering the Underlying Geographic Context Help to Improve the Accuracy of Passenger Flow Forecasting? A Case Study with Spatially-Extended Graph Neural Network and Location-Based Passenger Counting Data

 

Hai-Ping Zhang, Guo-An Tang, Li-Yang Xiong and Xing-Xing Zhou
Big data analysis for resident mobility characteristics by using multi-source urban traffic tracking data

Andreas Keler, Jukka Krisp and Linfang Ding
Towards detecting travel-mode- and commuter-specific destination hotspots – comparing the boro taxi service with Citi Bike in NYC

Qiulei Guo and Hassan Karimi
Human Mobility Prediction Through Trajectory Distribution

10:10 – 10:40 Coffee Break
10:40 – 12:20

 

 

 

 

 

Session 4. Analyzing Human Dynamics

Session Chair:

Caglar Koylu
Integrating Topic Modeling and Network Smoothing to Uncover Space-Time Semantics of Interpersonal Communication: An Analysis Of Twitter User Mentions

Xuebin Wei and Xiaobai Yao
Analyzing Human Activities in Spatial-Social Dimensions

Robert Olszewski
Digital Agora – Using Spatial Data Mining Algorithms to Process Geographic Information and Social Media Data

Hyunwoo Hwangbo, Jonghyuk Kim and Soyean Kim
Customer Movement Pattern Analysis Using Location-based Tracking Data

12:20 – 14:00 Lunch Break
14:00 – 15:40 Session 5. Research Applications Using Location-based Big Data

Session Chair:

Huina Mao, Gautam Thakur, Kevin Sparks, Jibonananda Sanyal and Budhendra Bhaduri
Mapping Real-time Power Outage from Social Media

Jie Shen, Mi Wan, Haosheng Huang, Kaiyue Zang and Yiqiu Tan
Assessing and Mapping of Road Surface Roughness based on GPS and Accelerometer Sensors on Bicycle-Mounted Smartphone

Lei Zou, Nina Lam, Heng Cai and Yi Qiang
Visualizing and Mining Social Media Data for Improved Understanding of Disaster Resilience

Haibo Ma, Manman Wang, Zhijun Gao and Di Wang
Location Analysis of Terminal Logistics Distribution Center Based On Geographic Spatial Suitability

15:40-16:10 Coffee Break
16:10-17:50 Session 6.  Understanding Places with Location-based Big Data

Session Chair:

Rui Zhu, Krzysztof Janowicz and Song Gao
Quantifying the Attractiveness of Destinations for Modeling Travel Patterns Using Location-Based Social Media Data

Yingjie Hu, Huina Mao and Grant McKenzie
A NLP and Geospatial Workflow for Harvesting Local Place Names from Geotagged Social Web


Myeong Lee, Grant McKenzie and Rajat Aghi
Exploratory Cluster Analysis of Urban Mobility Patterns to Identify Neighborhood Boundaries

Hua Liao and Weihua Dong
Identifying User Tasks in Map-based Pedestrian Navigation from Eye Tracking Data

17:50 – 18:00         Closing

Each talk has 20 minutes for the presentation, followed by 5-minutes of Q&A time