Hitchhiking Rides Dataset: Two decades of crowd-sourced records on stochastic traveling
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915361381679104 |
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| author | Wenke, Till |
| author_facet | Wenke, Till |
| contents | Hitchhiking, a spontaneous and decentralized mode of travel, has long eluded systematic study due to its informal nature. This paper presents and analyzes the largest known structured dataset of hitchhiking rides, comprising over 63,000 entries collected over nearly two decades through platforms associated with hitchwiki.org and lately on hitchmap.com. By leveraging crowd-sourced contributions, the dataset captures key spatiotemporal and strategic aspects of hitchhiking. This work documents the dataset's origins, evolution, and community-driven maintenance, highlighting its Europe-centric distribution, seasonal patterns, and reliance on a small number of highly active contributors. Through exploratory analyses, I examine waiting times, user behavior, and comment metadata, shedding light on the lived realities of hitchhikers. While the dataset has inherent biases and limitations - such as demographic skew and unverifiable entries it offers a rare and valuable window into an alternative form of mobility. I conclude by outlining future directions for enriching the dataset and advancing research on hitchhiking as both a transportation practice and cultural phenomenon. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2506_21946 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Hitchhiking Rides Dataset: Two decades of crowd-sourced records on stochastic traveling Wenke, Till Computers and Society Machine Learning Hitchhiking, a spontaneous and decentralized mode of travel, has long eluded systematic study due to its informal nature. This paper presents and analyzes the largest known structured dataset of hitchhiking rides, comprising over 63,000 entries collected over nearly two decades through platforms associated with hitchwiki.org and lately on hitchmap.com. By leveraging crowd-sourced contributions, the dataset captures key spatiotemporal and strategic aspects of hitchhiking. This work documents the dataset's origins, evolution, and community-driven maintenance, highlighting its Europe-centric distribution, seasonal patterns, and reliance on a small number of highly active contributors. Through exploratory analyses, I examine waiting times, user behavior, and comment metadata, shedding light on the lived realities of hitchhikers. While the dataset has inherent biases and limitations - such as demographic skew and unverifiable entries it offers a rare and valuable window into an alternative form of mobility. I conclude by outlining future directions for enriching the dataset and advancing research on hitchhiking as both a transportation practice and cultural phenomenon. |
| title | Hitchhiking Rides Dataset: Two decades of crowd-sourced records on stochastic traveling |
| topic | Computers and Society Machine Learning |
| url | https://arxiv.org/abs/2506.21946 |