Profiling the digital divide of the elderly based on Internet big data: evidence from China

Abstract

The integrated development of population aging and digital information age has brought an insurmountable “digital divide” to the elderly. We propose a method to profile the digital divide of the elderly by text mining, Baidu index and principal component analysis. The top ten scenarios related to the digital divide of the elderly are extracted, which are mobile, payment, phone, QR code, technology, WeChat, Alipay, cash, insurance and medical. The attention distribution of different scenarios in major cities in China was investigated and classified. The results suggest that the health code, social media, and online insurance need higher policy attention to promote narrow digital divide measure. And an inconsistency between netizens' attention and news reports makes Internet search behaviors have the potential to be a real-time supplement to narrow the digital divide among the elderly. The problem states of different cities reflect spatial heterogeneity and temporal asynchrony. The proposed method timely tracks the scenarios of the elderly's digital divide, providing effective insights and references to policy making and services and products improvement, and also providing suggestions for optimizing the development of “Internet +” aging.

Keywords

• Digital divide of the elderly
• Text mining
• Baidu index
• Principal component analysis