社交媒体文本数据分析方法对比与适用性研究:以北京市城市公园感知为例

Comparison and Applicability Study of Analysis Methods for Social Media Text Data:Taking Perception of Urban Parks in Beijing as an Example

互联网科技和媒体的蓬勃发展产生了大量社交媒体数据,基于自发评论文本进行社会感知分析逐渐成为研究热点,也开始被应用于城市公园使用情况和情感认知的研究中。鉴于现有研究大都应用单一的文本分析方法,本研究尝试开展社交媒体文本数据分析方法的对比研究,并揭示其在公园感知研究中的优缺点和适用性。研究选择在相关领域广泛应用的词典模型和LDA模型,以大众点评网站上北京10座城市公园的点评文本为研究数据,分别从单个公园和公园整体使用感知两个层面进行文本分析,并对比分析感知主题的分类结果。结果表明:词典模型更有利于在公园间进行横向对比分析;LDA模型则可以直观显示公园特色和游客感知偏好;综合运用两种模型可优化公园感知评估。两种方法揭示了北京城市公园游客对公园的关注主要集中于社交活动的需求、自然景观带来的视觉审美需求,以及交通设施状况和城市公园消费情况。本研究既可为社交媒体文本分析方法的选择和使用提供优化建议,又可为公园建设与管理改进提供依据与指导。

The booming Internet technology and media have generated large sets of social media data,with which the social sensing analyses based on users’reviews have become a research hotspot and have been increasingly applied in the study of urban park usage and perception.However,most existing studies adopt a single model for text data processing.To fill this gap,this study aims to compare social media text data analysis methods and assess their advantages,disadvantages and applicability in park perception research.The Lexicon-based classification analysis model(lexicon model)and LDA(Latent Dirichlet Allocation)model widely used in relevant research were selected.Based on text data obtained from public reviews of 10 urban parks in Beijing on Dianping,this study explored the perception topic distribution of each park and all parks in general,and compared the classification results of perception topics between these two models.Results show that the lexicon model is conducive to the parallel comparison of perception frequency between parks,while the LDA model can directly reflect each park’s characteristics and visitors’perception preferences;the combined use of the two models can optimize park perception assessment.Results from the two methods reveal that visitors to urban parks in Beijing focused more on their social recreation needs and visual aesthetics brought by the natural landscape,as well as conditions of the transportation facilities and the consumption in the parks.This research can provide optimization suggestions for the selection and use of social media text analysis methods,and a basis and guidance for park construction and management improvement.