At the present time, social media is not only used for connecting people in a virtual environment, but is also considered as a reach source of information for organizations and public service agencies to facilitate their policy and decision making processes. As an example, such crowdsourced data can be considered as a complementary source for analyzing people choices. In this study, we attempt to show how social media data can be used (and utilized) in order to extract travel mode choice which can be used as complementary source of information to improve traditional costly methods such as House Travel Surveys (HTS). The contents of Twitter data posted in Melbourne metropolitan areas have been analyzed to determine travel mode choices information. The results show, walking and driving modes are the most frequent travel modes extracted from Twitter data while public mode of transportations such as bus and taxi are rarely detected. Future research is required to extend this approach by considering and validating sociodemographic metrics of social media users so as to utilize social media data as complementing source of information for HTS.