Comparing Social Media Data and Survey Data in Assessing the Attractiveness of Beijing Olympic Forest Park

Zhifang Wang · Yue Jin · Yu Liu · Dong Li · Bo Zhang

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Human Mobility and Location-Based Analysis Geographic Information Systems Studies Urban Green Space and Health

Abstract

Together with the emerging popularity of big data in numerous studies, increasing theoretical discussions of the challenges and limitations of such data sources exist. However, there is a clear research gap in the empirical comparison studies on different data sources. The goal of this paper is to use “attractiveness” as a medium to examine the similarity and differences of Social media data (SMD) and survey data in academic research, based on a case study of the Beijing Olympic Forest Park, in Beijing, China. SMD was extracted from two social media platforms and two surveys were conducted to assess the attractiveness of various locations and landscape elements. Data collection, keyword extraction and keyword prioritization were used and compared in the data gathering and analysis process. The findings revealed that SMD and survey data share many similarities. Both data sources confirm that natural ambience is more appreciated than cultural elements, particularly the naturalness of the park. Spaces of practical utility are more appreciated than facilities designed to have cultural meanings and iconic significance. Despite perceived similarities, this study concludes that SMD exhibits exaggerated and aggregated bias. This resulted from the intrinsic character of SMD as volunteered and unstructured data selected through an emotional process rather than from a rational synthesis. Exciting events were reported more often than daily experiences. Reflecting upon the strength and weakness of SMD and survey data, this study would recommend a combined landscape assessment process, which first utilizes SMD to build up an assessment framework, then applies conventional surveys for supplementary and detailed information. This would ultimately result in comprehensive understanding.

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References

2012CRITICAL QUESTIONS FOR BIG DATA 2005Increasing walking 1993Measuring Destination Attractiveness: A Contextual Approach 2011Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter 2015Social Sensing: A New Approach to Understanding Our Socioeconomic Environments 2013Using social media to quantify nature-based tourism and recreation 2014Big-data applications in the government sector 2012Big Data for All: Privacy and User Control in the Age of Analytics

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