For practical reasons, surveys that aim for a large number of respondents tend to restrict themselves to closed-ended responses. Despite potentially bringing richer insights, the use of open-ended questions poses great challenges in terms of extracting useful information while significantly increasing the analysis time. Nevertheless, automatic text analysis techniques speed up the analysis of open-ended responses. In this research, we explore the potential to use techniques in topic modelling [Latent Dirichlet Allocation (LDA) and Supervised LDA (sLDA)] to extract information from open-ended responses. This is compared to the information obtained from closed-ended responses, accomplished using a questionnaire that measures the intention to use shared autonomous vehicles (SAVs). Two versions of the questionnaire-Ver_OE and Ver_Lk were used, with open-ended and Likert scales measuring the same attitudes in the alternative versions. Factors were extracted for closed-ended questions. For questions common to both versions of the questionnaire, respondents answering Ver_OE had a higher positive attitude towards autonomous vehicles. These attitudinal questions were placed after the open-ended questions. When evaluating the performance of the models that predict the intention to use SAVs, models estimated using Ver_OE performed better. This increased further with the inclusion of the information extracted from the open-ended responses using both, the unsupervised (LDA) and supervised (sLDA) methods. No improvement was observed in the model for Ver_Lk. These indicate the potential for the use of open-ended questions to measure attitudes and topic modelling to extract information from these responses.

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Information and Communication Technologies (ICT) enable individuals to travel more flexibly. The choice of location for social activities has become very flexible. In addition to this, land-use characteristics also play a vital role in the location of social activities. This work aims to analyse the influence of land-use characteristics, ICT use, and social networks in the destination choices for face-to-face social activities of university students during both weekdays and weekends. Students from the two different campuses of the Instituto Superior Técnico were presented with an online questionnaire, which was intended to collect information about their use of ICT and social networks, in addition to their travel characteristics and socio-demographics. Emphasis was made upon capturing the characteristics of social networks and ICT usage. Information on land-use characteristics was obtained from secondary sources. Factor analysis was initially carried out to extract factors related to the use of ICT and social networks; these were later used to model the destination choice for social activities. The alternatives considered for destination choice included: home or the vicinity thereof, university or the vicinity thereof, other locations (further away from home and university), and evenly spread locations-having no specific priority for any of the other three locations considered. The analysis was performed separately for travel during weekdays and weekends so that an understanding of the differences and similarities in behaviour during these different time periods could be garnered. A multinomial logit model was estimated to model this choice. The results point to the relevance of landuse characteristics, the location of close friends, and modes of interaction. Individuals residing in more accessible central, and denser areas, were more likely to have activities distributed evenly across the city. These results stress the relevance of accessibility in allowing larger and more diverse spaces to be used for social activities.

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