This project consists of two research components. The objective of the first component is to develop an approach to resample social media data in order to reduce biases and errors through estimation of socio-demographics. Several machine learning models are proposed for predicting socio-demographics, including gender, age, ethnicity and education levels. Afterward, this study resamples social media data and compares the results with the 2009 California Household Travel Survey data. The resampled data shows comparable characteristics to the survey data. Moreover, since social media is a kind of long-term data, it shows several advantages in research over survey data. This research sheds light on tackling sampling bias issues when social media data is used for travel behavior analysis.
This project intends to demonstrate the possibilities for using smartphones to obtain highlyresolved behavioral information for older adults, especial...
The research team conducted a survey of travel and activity scheduling behavior to better understand seniorcitizens’ trip chaining behavior in the C...
Links with this icon indicate that you are leaving a Bureau of Transportation
Statistics (BTS)/National Transportation Library (NTL)
Web-based service.
Thank you for visiting.
You are about to access a non-government link outside of
the U.S. Department of Transportation's National
Transportation Library.
Please note: While links to Web sites outside of DOT are
offered for your convenience, when you exit DOT Web sites,
Federal privacy policy and Section 508 of the Rehabilitation
Act (accessibility requirements) no longer apply. In
addition, DOT does not attest to the accuracy, relevance,
timeliness or completeness of information provided by linked
sites. Linking to a Web site does not constitute an
endorsement by DOT of the sponsors of the site or the
products presented on the site. For more information, please
view DOT's Web site linking policy.
To get back to the page you were previously viewing, click
your Cancel button.
United States Department of Transportation
[PDF-1.97 MB]
