{"title":"City Influence Network: Mining and Analyzing the Influence of Chinese Cities Based on Social Media","authors":"Lihua Wang, Shengyi Jiang","doi":"10.1111/tgis.13249","DOIUrl":null,"url":null,"abstract":"There have been very few studies done on measuring the influence of all prefecture‐level cities on a national scale due to the limited availability of public data, challenges in data collection, and insufficient data comprehensiveness. In this paper, we aim to fill this gap by investigating this problem in China. We first collected 692,859 news articles spanning one full year from the WeChat Official Accounts of 339 cities and Taiwan Province, which served as our study area and dataset. Then, we developed a city extractor module to reduce the ambiguity of place names and constructed a city interaction network. Then, we modeled the City Influence Index (CII) and the intensity of its influence. Finally, we proposed an analytical framework that examines the relationship between CII and Gross Domestic Product (GDP), compares it with the Global Cities Index, conducts influence analysis of cities at different levels, and more. The experimental results demonstrate that our analytical framework can effectively measure the influence of cities on a national scale and uncover the implicit relationships between cities. In doing so, our study offers a new perspective for measuring city influence. Code is available at: <jats:ext-link xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"https://github.com/vczero/CII\">https://github.com/vczero/CII</jats:ext-link>.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions in GIS","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1111/tgis.13249","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 0
Abstract
There have been very few studies done on measuring the influence of all prefecture‐level cities on a national scale due to the limited availability of public data, challenges in data collection, and insufficient data comprehensiveness. In this paper, we aim to fill this gap by investigating this problem in China. We first collected 692,859 news articles spanning one full year from the WeChat Official Accounts of 339 cities and Taiwan Province, which served as our study area and dataset. Then, we developed a city extractor module to reduce the ambiguity of place names and constructed a city interaction network. Then, we modeled the City Influence Index (CII) and the intensity of its influence. Finally, we proposed an analytical framework that examines the relationship between CII and Gross Domestic Product (GDP), compares it with the Global Cities Index, conducts influence analysis of cities at different levels, and more. The experimental results demonstrate that our analytical framework can effectively measure the influence of cities on a national scale and uncover the implicit relationships between cities. In doing so, our study offers a new perspective for measuring city influence. Code is available at: https://github.com/vczero/CII.
期刊介绍:
Transactions in GIS is an international journal which provides a forum for high quality, original research articles, review articles, short notes and book reviews that focus on: - practical and theoretical issues influencing the development of GIS - the collection, analysis, modelling, interpretation and display of spatial data within GIS - the connections between GIS and related technologies - new GIS applications which help to solve problems affecting the natural or built environments, or business