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"I Prefer Regular Visitors to Answer My Questions": Users' Desired Experiential Background of Contributors for Location-based Crowdsourcing Platform

Fang-Yu Lin, Pei-Hua Tsai, Chia-Yi Lee, Yi-Ting Ho, Yao-Kuang Chen, Yu-Chun (Grace) Yen, Yung-Ju Chang

2024Year
2Citations
1Top-tier citations

Abstract

This three-phase study explores the experiential background of contributors to platforms that provide crowdsourced location-related information. Initially, we utilized interviews to understand users’ expectations for location-related information and the contributors’ experiential background they believe would enhance this information’s utility. We then deployed a survey to identify the top eight sought-after location-information types and their perceived characteristics. Then the concluding online scenario-based study provided quantitative evidence about the interrelationships of eight types of location-related information, ten crucial quality attributes, and aspects of the contributors’ experiential background believed to enhance the utility of the descriptions they provide. Notably, although certain experiential background aspects were deemed universally advantageous across all information types, unique connections were identified among specific information types and distinct experiential background aspects seen as augmenting the contributor’s descriptions’ utility. These insights underline the importance of location-based crowdsourcing platforms incorporating contributors’ experiential background when assigning tasks.

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