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Evaluating the VGI Users' Level of Expertise: An Application of Statistical and Artificial Neural Network Approaches

Evaluating the VGI Users' Level of Expertise: An Application of Statistical and Artificial Neural Network Approaches
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Author(s): Elaheh Azariasgari (Islamic Azad University, South Tehran, Iran)and Farhad Hosseinali (Shahid Rajaee Teacher Training University, Iran)
Copyright: 2023
Volume: 14
Issue: 1
Pages: 16
Source title: International Journal of Applied Geospatial Research (IJAGR)
Editor(s)-in-Chief: Donald Patrick Albert (Sam Houston State University, USA)and Samuel Adu-Prah (Sam Houston State University, USA)
DOI: 10.4018/IJAGR.316770

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Abstract

Currently, online maps are of the most innovative and significant sources of information in people's daily life. However, quality assessment of volunteered geographic information (VGI) data raises some challenges. This research aims to analyze the VGI participants' level of expertise through evaluation of their background information. Towards this goal, an android application was developed to test users' knowledge and cognition about some selected regions of city as well as their background information. In order to evaluate the quality of information expressed by participants, some changes were made in Tehran's online map, and users were asked to identify the changes and to guess the vanished attributes. Statistical and ANN approaches were applied for analysis. The results demonstrated that the ANN was able to predict the percentage of correct answers of a new volunteer with mean squared error of 0.2. This research suggests that users' age and familiarity with the specific region in the city play more significant roles in their expertise in using online maps and in probable participating in VGI.

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