基于社交媒体数据的北京游客情感体验及时空特征研究

A Study on the Spatial and Temporal Characteristics of Beijing Tourists'Emotional Experience Based on Social Media Data

社交媒体数据的数量和类型日渐丰富,通过机器学习等分析技术可以对人们的行为和情感特征进行挖掘和分析。以北京游客为研究对象,基于新浪微博数据,经过数据预处理,利用文本分析和空间分析方法研究了游客情感的时空变化特征。结果表明:游客在京旅游的积极情感占比高于消极情感;在空间上,情感热点主要分布在主城区,情感冷点主要分布在郊区。游客的积极情感多表现为赞美、良好体验、文化丰富等;消极情感主要与人流量大、景区服务质量欠佳、较差的天气状况等因素有关。该结果以期丰富情感地理学的内容和方法,并为提升旅游业服务质量和城市基础设施建设提供理论依据。

The amount and types of social media data are becoming more and more abundant,and people's behavior and emotional characteristics can be mined and analyzed through analysis techniques such as machine learning.This paper takes Beijing tourists as the research object,based on Sina Weibo data.After data preprocessing,text analysis and spatial analysis methods are used to study the spatial and temporal characteristics of tourists'emotions.The research results show that the proportion of tourists positive emotions in Beijing is higher than that of negative emotions;in terms of space,emotional hot spots are mainly distributed in the main urban areas,and emotional cold spots are mainly distributed in the suburbs.The positive emotions of are mostly expressed as praise,good experience,rich culture,etc.The negative emotions are mainly related to factors such as large flow of people,poor service quality of scenic spots,and poor weather conditions.This research aims to enrich the content and methods of emotional geography,which provides a theoretical basis for improving tourism service quality and urban infrastructure construction.