Preserving traveller privacy in location-based social media: a local differential privacy approach

Purpose This paper aims to address the issue of privacy leakage indirectly caused by non-private data shared by travellers on location-based social media (LBSM) in data mining. Design/methodology/approach This paper proposes a privacy-preserving location data collection approach based on local differential privacy (LDP) and validates the feasibility of the approach through experiments on three real-world public check-in datasets. Findings The experimental results demonstrate the effectiveness of our proposed approach, which preserves privacy while retaining over 90% of the data utility. Practical implications This research has the potential to assist tourism practitioners in establishing improved collaborations with trusted third parties, enabling the exploration of user location data insights without undue concerns regarding indirect privacy breaches during data mining, thereby enhancing travellers’ experience and aiding businesses’ decision-making. Originality/value This paper is likely to be the first to represent a promising solution for addressing privacy leakage concerns related to non-sensitive data in data mining. It provides a location data collection technology that strikes a balance between user privacy and data utility for tourism practitioners.