Destination choice modeling using location-based social media data

Hasnat, Mehedi; Faghih-Imani, Ahmadreza; Eluru, Naveen; Hasan, Samiul

doi:10.1016/j.jocm.2019.03.002

Cited by 10 publications

(8 citation statements)

References 46 publications

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“…This is because there are currently 1.86 billion social media users with an active Facebook account (Misirlis and Vlachopoulou, 2018). On Twitter’s social media platform, more than 300 million registered users actively release an average of 500 million UGC across the continent of the world every day (Hasnat et al , 2019). Interestingly, although there are campus sustainability indicators in the selected tools for appraising the various HEIs’ public participation and involvement of students, the utilization of various platforms of social media for advancing such endeavors was missing.…”

Section: Resultsmentioning

confidence: 99%

Exploring the usage of social media in extant campus sustainability assessment frameworks for sustainable campus development

Adenle

Abdul-Rahman

Soyinka

2021

IJSHE

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Purpose As one of the buzzwords in the present age with considerable impacts in tertiary institutions, social media use in online teaching, learning and information dissemination have been extensively discussed in extant literature. This paper aims to explore the existing campus sustainability appraisal (CSA) tools to identify the length at which social media has been used, especially in environmental sustainability indicators’ selection and empirical verification. Design/methodology/approach The methodology is mainly based on a desktop study involving comprehensive review and content analysis of existing CSA tools’ documents. Webpage content analysis of selected sustainability monitoring and tracking system in higher education institutions was also conducted. Findings The tools' content analysis reveals insufficient utilization of social media data and platforms in campus sustainability environmental-dimension indicators selection. To bridge this identified research gap, social media user-generated content for appraising the campus-wide environmental sustainability indicators preference in tertiary institutions was proposed. Practical implications The adoption and modification of this study’s proposed approach by tertiary institutions, especially in sub-Saharan African countries, could help address most campus-wide environmental challenges raised, commented on and discussed on social media. Originality/value This study contributes to knowledge gaps by revealing the extent of social media utilization in extant tools. With the expanding utilization of different social media platforms by various tertiary institutions worldwide, their administrators' responsibility is to put these social media data into fair use.

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Section: Resultsmentioning

confidence: 99%

Exploring the usage of social media in extant campus sustainability assessment frameworks for sustainable campus development

Adenle

Abdul-Rahman

Soyinka

2021

IJSHE

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“…Instead of geotagged displacements, one can model destination choices to estimate zonal attractiveness. Hasnat et al (2019) applied Twitter data together with census tract data for modelling travellers' destination choice behaviour, which suggests that Twitter data can be utilised effectively for modelling destination choices that reflect the attractions of zones. Molloy and Moeckel (2017) develop a long-distance destination choice model using Foursquare check-ins whose results suggest that check-ins from social media platforms can improve destination choice models, particularly for leisure travel.…”

Section: Trip Generationmentioning

confidence: 99%

Feasibility of estimating travel demand using geolocations of social media data

2021

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Travel demand estimation, as represented by an origin–destination (OD) matrix, is essential for urban planning and management. Compared to data typically used in travel demand estimation, the key strengths of social media data are that they are low-cost, abundant, available in real-time, and free of geographical partition. However, the data also have significant limitations: population and behavioural biases, and lack of important information such as trip purpose and social demographics. This study systematically explores the feasibility of using geolocations of Twitter data for travel demand estimation by examining the effects of data sparsity, spatial scale, sampling methods, and sample size. We show that Twitter data are suitable for modelling the overall travel demand for an average weekday but not for commuting travel demand, due to the low reliability of identifying home and workplace. Collecting more detailed, long-term individual data from user timelines for a small number of individuals produces more accurate results than short-term data for a much larger population within a region. We developed a novel approach using geotagged tweets as attraction generators as opposed to the commonly adopted trip generators. This significantly increases usable data, resulting in better representation of travel demand. This study demonstrates that Twitter can be a viable option for estimating travel demand, though careful consideration must be given to sampling method, estimation model, and sample size.

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“…The comparison between this new OD with the traditional values produced by the 4-step model proved the great potential of using social media data in modeling aggregate travel behavior. Social media data can be used in other areas such as destination choice modeling [86], recognizing activity [87], understanding the patterns of choosing activity [80,88,89], and interpreting life-style behaviors via studying activitylocation choice patterns [90].…”

Section: Social Media Datamentioning

confidence: 99%

Recent Progress in Activity-Based Travel Demand Modeling: Rising Data and Applicability

Tajaddini¹,

Rose²,

Kockelman³

et al. 2021

Models and Technologies for Smart, Sustainable and Safe Transportation Systems

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Over 30 years have passed since activity-based travel demand models (ABMs) emerged to overcome the limitations of the preceding models which have dominated the field for over 50 years. Activity-based models are valuable tools for transportation planning and analysis, detailing the tour and mode-restricted nature of the household and individual travel choices. Nevertheless, no single approach has emerged as a dominant method, and research continues to improve ABM features to make them more accurate, robust, and practical. This paper describes the state of art and practice, including the ongoing ABM research covering both demand and supply considerations. Despite the substantial developments, ABM's abilities in reflecting behavioral realism are still limited. Possible solutions to address this issue include increasing the inaccuracy of the primary data, improved integrity of ABMs across days of the week, and tackling the uncertainty via integrating demand and supply. Opportunities exist to test, the feasibility of spatial transferability of ABMs to new geographical contexts along with expanding the applicability of ABMs in transportation policy-making.

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Destination choice modeling using location-based social media data

Cited by 10 publications

References 46 publications

Exploring the usage of social media in extant campus sustainability assessment frameworks for sustainable campus development

Exploring the usage of social media in extant campus sustainability assessment frameworks for sustainable campus development

Feasibility of estimating travel demand using geolocations of social media data

Recent Progress in Activity-Based Travel Demand Modeling: Rising Data and Applicability

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