#Cyberbullying in the Digital Age: Exploring People's Opinions with Text Mining

TL;DR

This paper employs text mining on Twitter data to explore public opinions on cyberbullying, highlighting key themes, concerns, and the emotional tone associated with the issue.

Contribution

It introduces a novel application of text mining to analyze social media opinions on cyberbullying, identifying major themes and emotional sentiments.

Findings

Three major themes identified: prevention actions, important events, and concerns.

Negative sentiments are 2.45 times more frequent than positive ones.

Parents and teachers play crucial roles in cyberbullying prevention.

Abstract

This study used text mining to investigate people's insights about cyberbullying. English-language tweets were collected and analyzed by R software. Our analysis demonstrated three major themes: (a) the major actions that needed to be taken into consideration (e.g. guiding parents and teachers to cyberbullying prevention, funding schools to fight cyberbullying), (b) certain events that were important to people (e.g. the Michigan cyberbullying law), and (c) people's major concerns in this regard (e.g. mental health issues among students). Parents and teachers have an important role in educating, informing, warning, preventing, and protecting against cyberbullying behaviors. The frequency of negative sentiments was almost 2.45 times more than positive sentiments.