Analysing Social Media Network Data with R: Semi-Automated Screening of Users, Comments and Communication Patterns

TL;DR

This paper presents a semi-automated method for analyzing social media communication patterns, aiming to identify active users and understand the spread of harmful content like hate speech and fake news.

Contribution

It introduces a novel approach to break down social media interactions, trace users, and distinguish active users with high accuracy, considering social network framing and topics.

Findings

Identifies active users with 100% accuracy when considering social context.

Highlights the need for dynamic methods to detect harmful content.

Provides a framework for qualitative inspection of social media communication.

Abstract

Communication on social media platforms is not only culturally and politically relevant, it is also increasingly widespread across societies. Users not only communicate via social media platforms, but also search specifically for information, disseminate it or post information themselves. However, fake news, hate speech and even radicalizing elements are part of this modern form of communication: Sometimes with far-reaching effects on individuals and societies. A basic understanding of these mechanisms and communication patterns could help to counteract negative forms of communication, e.g. bullying among children or extreme political points of view. To this end, a method will be presented in order to break down the underlying communication patterns, to trace individual users and to inspect their comments and range on social media platforms; Or to contrast them later on via qualitative research. This approeach can identify particularly active users with an accuracy of 100 percent, if the framing social networks as well as the topics are taken into account. However, methodological as well as counteracting approaches must be even more dynamic and flexible to ensure sensitivity and specifity regarding users who spread hate speech, fake news and radicalizing elements.