社交媒体文本与语义网络:公众认知视角下空间基因识别提取新方法——以山东省烟台市蓬莱区为例  

Social Media Texts and Semantic Networks:A New Method for Space Gene Recognition Extraction from Public Perception Perspective:Taking Penglai District of Yantai in Shandong Province as an Example

作　　者：郭楚怡 李伊格[1] GUO Chuyi;LI Yige

机构地区：[1]东南大学建筑学院

出　　处：《城乡规划》2024年第6期83-89,共7页Urban and Rural Planning

摘　　要：空间基因的识别提取是后续解析评价与传承导控的基础,目标是从复杂的城市形态中提炼出具有地方代表性的空间组织模式。针对以往数据有效样本量小、主观判断依赖性强等研究局限,本文采用社交媒体文本数据,引入语义网络分析技术,通过文本数据采集、主题模型分类、语义网络聚类、要素组合筛选,构建公众认知导向的空间基因识别提取新方法。该方法在山东省烟台市蓬莱区得到成功应用,为识别提取城市空间基因提供了一种新的技术路径。The identification and extraction of space genes is the basis of subsequent analytical evaluation and inheritance control,with a view of extracting locally representative spatial organization patterns from complex urban forms.Addressing limitations of previous studies such as small effective sample size of data and strong dependence on subjective judgement,this paper adopts social media text data and introduces semantic network analysis technology to construct a new method of identification and extraction of space genes oriented to public cognition through the collection of text data,classification of thematic model,clustering of semantic network,and screening of element combinations.The method is successfully applied in Penglai District of Yantai in Shandong,providing a new technical path for identifying and extracting urban space genes.

关 键 词：空间基因 公众认知 社交媒体文本 语义网络分析 蓬莱 

分 类 号：TU984[建筑科学—城市规划与设计]