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01-12-2023 | Original Article

An analysis of the public consequences of cybersecurity incidents in Brazil

Authors: Vitória de Lemos, Luciano Ignaczak

Published in: Social Network Analysis and Mining | Issue 1/2023

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Abstract

The study focuses on the public consequences of cybersecurity incidents in Brazil, particularly data breaches and ransomware. It analyzes the impact on stock values, social media sentiment, and news coverage of incidents involving Brazilian companies. The research highlights the lack of significant stock value impact and the predominantly neutral sentiment on social media. Additionally, it proposes an anatomy for the consequences of cybersecurity incidents, identifying three phases: Information, Repercussion, and Extenuation. The study also compares the behavior of data breaches and ransomware incidents in terms of news coverage and sentiment over time. The findings suggest that ransomware incidents have a shorter reverberation period compared to data breaches.

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Footnotes
2
The following link introduces the Twitter API version 2: https://​developer.​twitter.​com/​en/​docs/​twitter-api.
 
3
We collected the stock information from B3, the Brazilian stock exchange, using Yahoo services at https://​br.​financas.​yahoo.​com.
 
4
The news analyzed in this study was collected using the platform published by Google: https://​news.​google.​com.
 
5
Tweets and news used in the analysis are available on https://​github.​com/​VitoriaLemos/​Unisinos-PFII.
 
6
The Python scripts developed by authors are available in the following GitHub repository: https://​github.​com/​VitoriaLemos/​Unisinos-PFII.
 
7
The Text Analytics features made available as part of the Cognitive Service for Language are explained at https://​azure.​microsoft.​com/​en-us/​services/​cognitive-services/​text-analytics/​.
 
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Metadata
Title
An analysis of the public consequences of cybersecurity incidents in Brazil
Authors
Vitória de Lemos
Luciano Ignaczak
Publication date
01-12-2023
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2023
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-023-01113-9

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