Social network analysis using open-source software: the most used terms in Spanish during the Covid-19 pandemic

Abstract

Introduction: communication on social media is a reflection of the behavioral patterns of a society, allowing us to understand its community structure. The objective of this research was to identify the most used terms on social media during the COVID-19 pandemic in five Spanish-speaking countries to identify their social patterns.
Method: a descriptive and quantitative approach was used, using web scraping techniques to collect 31 353 Facebook comments between July 2017 and July 2022. Through Data Wrangling and Text Mining methods, the data was processed by removing irrelevant words and applying lexical analysis using the POS Tagging technique. Five countries were selected: Spain, Colombia, Mexico, Peru, and Chile, to compare term frequencies.
Results: the results revealed that the most recurrent terms were "bono", "delivery" and "distancing" in Peru, while "cuarentena", "bono" and "teletrabajo" dominated in Chile. The term “bono” was observed to be especially relevant in Peru and Chile, while the anglicism “delivery” was concentrated in Peru. In addition, a significant variation was noted in the use of terms before and after the pandemic.
Conclusions: the analysis of terms on social media during the pandemic reveals significant patterns in social communication. Terms such as “quarantine” and “teleworking” not only emerged during confinement, but their use persisted, indicating a cultural change. This study demonstrates that social media is a valuable tool to understand community dynamics and the social impact of global events such as the pandemic.