Given the importance of urban parks for recreation, it is critical to understand how they, are used and perceived. Currently, relatively few studies have examined the public’s, activities and preferences at the same time. Social media data are increasingly, recognized as a promising data source to study these two aspects. However, little is, known regarding the utility and representativeness of social media data for urban, parks. In particular, a lack of understanding exists on the comparability of research, results measured by bottom-up social media data and top-down official survey data in, urban park studies. This research used social media data from Ctrip and Dianping and, survey data from the local government agency with park visits statistics and park, satisfaction surveys to understand the public’s visitation and satisfaction of 102 urban, parks in central Shanghai. We first assessed the similarities between the social media, data and survey data by correlation analysis. We then used the negative binomial, regression model and beta regression model to examine the matches and mismatches, of the different data sources in investigating factors influencing park visitation and park, satisfaction. Our correlation results showed that the social media data significantly, correlated with the survey data and that social media data performed better in more, frequently visited parks. Our regression results showed that the water bodies, recreational facilities, and surrounding commercial facilities were the common, influencing factors of park visitation and park satisfaction for all parks. While significant, correlations were noticed between these two data sources, we found that the, surrounding population density was negatively associated with park visitation, measured by social media data but positively associated with park visitation measured, by survey data. This study provides a comparative perspective to study park visitation, and park satisfaction by combining social media data and official survey data. Clarifying the consistencies and inconsistencies between the social media data and, official survey data is important because it could help us to understand the, representativeness and potential biases of the social media data when used in, visitation monitoring and satisfaction monitoring.

鉴于城市公园对娱乐的重要性，了解它们的使用和感知方式至关重要。目前，同时考察公众、活动和偏好的研究相对较少。社交媒体数据越来越被认为是研究这两个方面的有前途的数据源。然而，关于城市、公园的社交媒体数据的效用和代表性，人们知之甚少。特别是，对于研究的可比性、城市公园研究中自下而上的社交媒体数据和自上而下的官方调查数据所衡量的结果缺乏了解。本研究使用来自携程和大众点评的社交媒体数据，以及来自当地政府机构的公园访问统计数据和公园满意度调查数据，以了解 102 个城市的公众访问和满意度，上海市中心的公园。我们首先通过相关性分析评估了社交媒体、数据和调查数据之间的相似性。然后，我们使用负二项回归模型和 beta 回归模型来检查不同数据源在调查影响公园访问和公园满意度的因素时的匹配和不匹配。我们的相关性结果表明，社交媒体数据与调查数据显着相关，并且社交媒体数据在更多、更频繁访问的公园中表现更好。我们的回归结果表明，水体、娱乐设施和周边商业设施是所有公园的公园访问量和公园满意度的共同影响因素。虽然这两个数据源之间存在显着相关性，但我们发现，周围的人口密度与公园访问量呈负相关（通过社交媒体数据衡量），但与公园访问量（通过调查数据衡量）呈正相关。本研究通过结合社交媒体数据和官方调查数据，为研究公园参观和公园满意度提供了一个比较视角。澄清社交媒体数据与官方调查数据之间的一致性和不一致性很重要，因为它可以帮助我们了解社交媒体数据在用于访问量监测和满意度监测时的代表性、代表性和潜在偏差。本研究通过结合社交媒体数据和官方调查数据，为研究公园参观和公园满意度提供了一个比较视角。澄清社交媒体数据与官方调查数据之间的一致性和不一致性很重要，因为它可以帮助我们了解社交媒体数据在用于访问量监测和满意度监测时的代表性、代表性和潜在偏差。本研究通过结合社交媒体数据和官方调查数据，为研究公园参观和公园满意度提供了一个比较视角。澄清社交媒体数据与官方调查数据之间的一致性和不一致性很重要，因为它可以帮助我们了解社交媒体数据在用于访问量监测和满意度监测时的代表性、代表性和潜在偏差。