Social Media and COVID-19: Can Social Distancing be Quantified without Measuring Human Movements?

TL;DR

This paper introduces a novel, cost-effective method to quantify social distancing during COVID-19 by analyzing social media hashtags, avoiding the need for direct human movement measurement.

Contribution

It proposes using hashtag frequency analysis as an alternative to traditional movement-based social distancing metrics, validated by correlation with Google reports.

Findings

Strong correlation (P<0.05) with Google social distancing data.

Identified 18 relevant hashtags supporting social distancing.

Tracked hashtag trends from Jan to May 2020.

Abstract

The COVID-19 outbreak has posed significant threats to international health and the economy. In the absence of treatment for this virus, public health officials asked the public to practice social distancing to reduce the number of physical contacts. However, quantifying social distancing is a challenging task and current methods are based on human movements. We propose a time and cost-effective approach to measure how people practice social distancing. This study proposes a new method based on utilizing the frequency of hashtags supporting and encouraging social distancing for measuring social distancing. We have identified 18 related hashtags and tracked their trends between Jan and May 2020. Our evaluation results show that there is a strong correlation (P<0.05) between our findings and the Google social distancing report.