A Systematic Literature Review on Technological Solutions to Fight

Bullying and Cyberbullying in Academic Environments

Priscila Cedillo

, Alexandra Bermeo

, Alexa Betancourth

, Francisco Espinosa

Lourdes Illescas

and Janio Jadán

Computer Science Department, Universidad de Cuenca, Cuenca, Ecuador

Computer Science Research & Development Lab-LIDI, Universidad del Azuay, Cuenca, Ecuador

Universidad Tecnológica Indoamérica, Quito, Ecuador

alexbermeo@uazuay.edu.ec, janio.jadan@uti.edu.ec

Keywords: Bullying, Cyberbullying, Technology Tools, Education.

Abstract: Nowadays, the world is more connected than ever; the use of internet, social networks and platforms allows

for people of all ages to have constant communication. During the past year, due to the COVID-19 pandemic,

children and teenagers have had to spend most of their time using a technological device, for educational and

recreational purposes. This constant connection has carried on several issues, one of them being cyberbullied.

This is when a person intentionally and repeatedly harms another one, on a virtual environment. Even with

its downside, technology has many advantages; it has allowed for children and teenagers to engage in

educational communities and applications. Then, studies on bullying and the ways to fight it exist from many

years prior, however, there are little literature about the technological solutions to help in the fight against

cyberbullying and bullying. Therefore, the objective of this research is to perform a Systematic Literature

Review (SLR) about technological solutions for education and to fight bullying and cyberbullying in children

and teenagers. To perform a trustworthy, rigorous and repeatable SLR, the methodology proposed by

Kitchenham was used. The presented SLR, uses studies from 2009 to 2021. To start, a group of primary

studies was selected, which met the characteristics to answer the research question “What technological tools,

methods and models are used to educate about bullying and cyberbullying?” The primary studies were

obtained from the most used digital libraries, prominent journals, and most representative conferences in the

area. In conclusion, this study provides a global vision of the state of the art in this area, which represents a

helpful tool for researchers to detect weaknesses and gaps and open new horizons regarding the use and design

of technology to fight bullying and cyberbullying.

1 INTRODUCTION

The closure of schools due to the COVID-19

pandemic and the increase in using technological

tools, social networks, and digital platforms brought

along the need to adopt technologies in education. (E.

Onyema et al., 2020). Nowadays, most academic

stages have become digitized (e.g., Online courses,

MOOCs, digital learning methods) (Onyema, 2019).

https://orcid.org/0000-0002-6787-0655

https://orcid.org/0000-0002-2697-7528

https://orcid.org/0000-0002-4790-5996

https://orcid.org/0000-0003-2242-4130

https://orcid.org/0000-0002-0027-439X

https://orcid.org/0000-0002-3616-2074

This technological change has also turned bullying

behaviours that affect the welfare of children and

adolescents, into cyberbullying (e.g., attacking peers

through harmful text messages, photos, or videos)

(Pedreira et al., 2011, Washington, 2014).

Bullying and cyberbullying are quite prevalent

behaviours among children and adolescents at school

(Cedillo L, 2020). These behaviours are primarily

related to the difference in power between victims

Cedillo, P., Bermeo, A., Betancourth, A., Espinosa, F., Illescas, L. and Jadán, J.

A Systematic Literature Review on Technological Solutions to Fight Bullying and Cyberbullying in Academic Environments.

DOI: 10.5220/0011091800003182

In Proceedings of the 14th International Conference on Computer Supported Education (CSEDU 2022) - Volume 1, pages 413-420

ISBN: 978-989-758-562-3; ISSN: 2184-5026

413

and victimizers and can lead to psychological

consequences for the victims (Monks & Smith, 2006;

Foody et al., 2015).

In this sense, due to cyberbullying being caused

during the use of Information and Communication

Technologies (ICTs), technological tools are being

created to counteract this problem, such as vigilance

software, serious games, artificial intelligence within

e-learning tools, among others (Calderón & Ruiz,

2015). Besides, social networks, internet providers,

and other e-learning tools have implemented

functionalities for detecting when a person is virtually

assaulted.

Furthermore, those intervene by monitoring and

filtering parents, blocking an account, deleting

content, reporting, and redirecting to online resources

and safety centers in a preventive manner (Topcu-

Uzer & Tanrikulu, 2018). Therefore, the use of ICTs

as a strategy for intervention and prevention of

bullying and cyberbullying is an excellent benefit to

the emotional, psychological and social well-being of

children and teenagers (Nocentini et al., 2015).

In this context, due to the use increase of

prevention tools against bullying and cyberbullying,

it is necessary to know the state of the art in this

domain in order to determine the research lines and

tools implemented and detect investigation gaps.

Therefore, this research aims to conduct a

Systematic Literature Review (SLR) on technological

solutions for education and the fight against bullying

and cyberbullying in children and teenagers due to its

importance in today's society, following the guidelines

established by Barbara Kitchenham (2007). For this

reason, there is a need to know the technology tools

developed currently to prevent this problem and

intervene in the different social and educational fields.

Also, it will allow us to know which tools are the most

used and in which areas they develop. Furthermore, the

writing will serve as a basis for further research and

technological solutions to fight this problem in schools,

colleges, and universities.

Finally, this document has the following structure:

Section 2 presents the related works; it mentions

secondary studies related to technological tools to

fight against bullying and cyberbullying. Section 3

describes the core of the SLR, its protocol execution,

and results; and finally, Section 4 presents the

conclusions and future works.

2 RELATED WORK

To define the need for the performing of this SLR,

existing reviews on topics related to the use of tools

to fight against bullying and cyberbullying were

found. They are presented in the following sections.

The study conducted by Topcu-Uzer & Tanrikulu

(2018) presents the fact that technological tools are

not 100% focused on bullying and cyberbullying.

Although, there are still no scientific studies that can

prove the effectiveness of new technological

solutions against bullying and cyberbullying, with the

exception of stop systems such as text-based

detection (Dinakar et al., 2011; Soundar & Ponesakki,

2016), participant-vocabulary coherence (Raisi &

Huang, 2016) or morphosemantic patterns

(Ptaszynski et al., 2016). Moreover, there are recent

studies such as the Rethink software and an empathy-

enhancing video movie being conducted to combat

these problems. They will be a key element in the

development of new technological solutions to fight

bullying and cyberbullying and in future research to

demonstrate their effectiveness.

Calvo, A. et al., (2020) present a SLR of serious

games as technological tools of prevention and

detection to fight bullying and cyberbullying, through

the use of video games. The study had several

objectives: a) to see the benefits of using video

games, b) to determine the users on which these will

focus and, c) to assess the extent to which a given

population can benefit. At present, these games are

not yet available, but the idea is to create spaces of

awareness, empathy and teaching for students,

teachers and parents.

On the other hand, Nocentini et al., (2015) present

a SLR on ICT used to prevent and intervene bullying,

based on anti-bullying programs. Although it has

relation to the presented proposal, however, this

research will cover the solutions and technological

tools that currently exist to prevent and intervene

bullying and cyberbullying. Therefore, it will also be

an important contribution for future research on this

problem.

3 RESEARCH METHOD

In order to carry out the SLR in the framework of this

paradigm, it is necessary to follow a structured

procedure. The purpose of the SLR is to extract

previously conducted studies according to a specific

topic, to evaluate them and interpret the results

obtained in each one of them in an objective and

reliable way, so that it can be repeatable and

applicable in the future.

This study was conducted using the methodology

of Kitchenham (2007), the process has three stages.

First, the planning of the review, where the research

CSEDU 2022 - 14th International Conference on Computer Supported Education

414

questions are established and the protocol is started.

Second, conduct of the review, in this section the

primary studies are chosen, their quality is evaluated

and then the data obtained in the first stage are

extracted and traced in order to synthesize them.

Finally, the third stage refers to the review report,

which will enable the selection of the dissemination

mechanisms and thus, the presentation of the SLR.

3.1 Planning the Review

This SLR focuses on technological solutions that help

in the promotion against bullying and cyberbullying

in children and teenagers. According to UNESCO

(2019), bullying affects 1 in every 3 children, and

cyberbullying globally affects 1 in 10 children,

therefore, the main research question that has been

raised is: What technological tools, methods and

models are used to educate about bullying and

cyberbullying?

Therefore, to answer the research question, the

following research sub-questions have been proposed

a) In what population and environment will

technological tools be used to address the problem of

bullying and cyberbullying b) What are the tools,

technological methods, solutions, and deployment

platforms to fight Bullying and cyberbullying? and c)

How is the research conducted in relation to Bullying

and cyberbullying technology?

3.1.1 Identification of Data Sources and

Search Strategy

To obtain the primary studies, several digital libraries

were used, such as: Redalyc, IEEEXplore, Scielo,

ACM Digital Library, SpringerLink, Science Direct,

PUBMED.

The milestone date established for the search is

2009 (U.S. Department of Education, 2021), because

from that year, almost everyone in the United States

had access to technology and Internet. According to

Purdue University, one out of every five students had

a computer, 83% had laptops, 50% had a cell phone

and 97% of the classrooms had one or more

computers with internet (Department of Education,

2021).

For the first phase, a search string was established

to facilitate the retrieval of publications related to

technology used for bullying and cyberbullying. The

string used to obtain these publications and then

review the title and abstract was: (Bullying OR

Cyberbullying) AND (tech*) AND (tool* OR

program*), it is important to note that the syntax

varies in each digital library. In addition, for the

search to be complete, it was searched in conferences

and journals.

3.1.2 Criteria for Selecting Primary Studies

To select the primary studies, a complementary

semantic check was performed in addition to a

syntactic inquiry. The title and abstract of the

documents were analysed and, if necessary, the

complete article was read to corroborate that it was

useful for the research and that it met the extraction

and inclusion criteria.

The authors evaluated and retrieved each study

from the automated or manual search in order to

decide whether or not it should be included by

considering its title, abstract and keywords.

Discrepancies in the selection were solved by

consensus among the authors after scanning the entire

paper.

The studies that met at least one of the following

inclusion criteria were included.

a) Studies presenting tools to fight bullying and

cyberbullying

b) Studies presenting technological methodologies

to reduce bullying and cyberbullying.

c) Studies presenting effective psychological

models through technologies to fight bullying

and cyberbullying.

The studies that met at least one of the following

exclusion criteria were excluded.

a) Non-English or non-Spanish language papers.

b) Papers that do not feature technologies to fight

bullying and cyberbullying.

c) Papers that are less than five pages.

d) Documents published before the milestone date

(2009), in which the first technological tools

appeared.

e) Introductory papers, short papers, books and

workshops.

f) Duplicate reports of the same study in different

sources.

3.1.3 Data Extraction Strategy

In order to answer the sub-questions, extraction

criteria have been defined for each of them. These are

shown in Table 1.

A Systematic Literature Review on Technological Solutions to Fight Bullying and Cyberbullying in Academic Environments

415

Table 1: Criteria for extraction of research sub-questions.

RQ1: In what population and environment will

technological tools be used to address the problem of

bullying and cyberbullying?

EC1 Environment School, Home, Social

environment

EC2 Population

(Calvo-Morata et

al., 2019)

Students, Teacher,

School Authorities,

Parents, General

Population

RQ2: What are the tools, technological methods,

solutions, and deployment platforms to fight bullying and

cyberbullying?

EC3 Type of gadgets Computers, Tablets, Cell

phone, Laptops, I-pads,

Others, None

EC4 Area of study Psychology, Electronics,

Informatics, Education

EC5 Type of interaction

(Garnica Bautista &

Tepán Mita, 2019)

Visual, Touch, Auditory,

Other

EC6 Type of Application

(Sousa & Goncalves,

2021)

MOOCs, 3D virtual,

Serious Game, Apps,

Others

EC7 Artificial

Intelligence

(Fernández, n.d.)

Data mining, Machine

Learning, Automatic

speech recognition,

Natural language

processing, Text

recognition, Deep

learning, Emotion

Recognition, Motion

Recognition

EC8 Types of

harassment

(Donegan, 2012)

Bullying,

Cyberbullying, Physical

Bullying, Psychological

Bullying, Verbal

Bullying, Sexual

Bullying, Social

Bullying

EC9 Types of

development

Software, None

EC10 Usability features

(ISO 25010, n.d.)

Functional adaptation,

Performance efficiency,

Compatibility,

Usability, Reliability,

Security,

Maintainability

EC11 Technology

suppliers

(Topcu-Uzer &

Tanrikulu, 2018)

Social networking

companies, Internet

service providers, E-

mail service providers

instant, Messaging

applications,

Cyberbullying

applications, Others

EC12 Solutions for

Cyberbullying

(Topcu-Uzer &

Tanrikulu, 2018)

Parental control and

filtering, Account

locking, Content

removal, Reporting,

Redirecting to online

resources, Security

centers

EC13 Technology

solutions

(Topcu-Uzer &

Tanrikulu, 2018)

Online Cyberbullying

detection systems,

Software, Video film,

Positive messages by

technical means, Others

EC14 Software

(Educba, n.d.)

Website, Application,

Mobile Systems, Others

EC15 Forms of Bullying

(Botell, 2017)

Social blocking,

Harassment,

Manipulation, Coercion,

Social exclusion,

Intimidation,

Aggressions, Threats

RQ3: How is the research conducted in relation to

bullying and cyberbullying technology?

EC16 Phases

(Wasson, n.d.)

Analysis, Design,

Implementation, Testing

EC17 Validation Experiment, Prototype,

Proof of Concept, Others

EC18 Approach scope

(Mårtensson et al.,

2016)

Industry, Academy

EC19 Methodology New, Extension

EC20 Area of study Informatics, Medicine,

Psychology, Electronics,

Others

EC21 Country

EC22 Year

3.2 Conducting the Review

The planning, execution and identification of the

primary studies was performed on December 17,

CSEDU 2022 - 14th International Conference on Computer Supported Education

416

2021. Here, 180 research papers were identified from

the databases, based on the automatic search.

In addition, a manual search was performed, from

which 50 research papers were selected. The papers

were carefully read and inclusion and exclusion

criteria were applied. Several studies were read in

detail and, finally, 32 were selected to be part of this

secondary study, for the complete list of selected

papers, see shorturl.at/cvwRT. Figure 1 summarizes

the entire process, up to the final selection of articles.

Figure 1: Articles selection.

4 DISCUSSION

4.1 Environment and Population

Most of the studies found in the SLR were conducted

in the school setting, where there are various

technological tools to prevent and intervene in

children and teenagers. It is very important to note

that they were carried out in this population, as

presented by Cedillo, L (2020), based on a report of

the United Nations International Children's

Emergency Fund (UNICEF), it stated that between 50

and 70% of students in Latin America and the

Caribbean had been involved in some type of

bullying.

On the other hand, a lack of studies in school

authorities and parents can be noted, which would be

fundamental to educate the most affected populations.

However, it can be seen that there are technological

tools for teachers to identify the nature of the

psychological impact experienced by students, such

as automated speech emotion recognition (Iliou &

Paschalidis, 2011), video games, MOOCs and 3D

Virtual Reality (Sousa & Goncalves, 2021).

4.2 Types of Application and Artificial

Intelligence

This study found that Machine Learning (ML) is one

of the most widely used Artificial Intelligence (AI)

techniques in the creation of technological tools to

fight bullying and cyberbullying. Its use is found in

apps and other types of applications to detect

language patterns used by victims and bullies, and in

systems for the identification of profiles in social

networks. It is important to emphasize that some AIs

are combined, such as CbPIS: Cyberbullying Profile

Identification System with Users in Loop (Chatzakou

et al., 2019) and Cyberbullying Detection and

Prevention: Data Mining and Psychological

Perspective (Parime & Suri, 2014).

On the other hand, there is only one study on

speech emotion recognition, which is very important

in the branch of psychology. It allows to identify the

psychological impact and understand the emotions of

bystanders and consequently their coping styles in

bullying episodes. It could introduce strategies that

provide students, who witness bullying, with positive

roles to counteract it (Iliou & Paschalidis, 2011).

4.3 Types of Application and Types of

Harassment

Figure 2 compares the criteria EC6: Types of

Application and EC8: Types of harassment, in order

to know the tools to fight the different types of

harassment. The obtained results indicate that there

are many tools that use artificial intelligence to fight

bullying, cyberbullying and social bullying, such as

the studies of Dinakar et al., (2011); E. M. Onyema,

(2019); Reynolds et al., (2011); Soundar &

Ponesakki, (2016) it can be seen it in using machine

learning to detect cyberbullying.

Moreover, to a lesser extent, there are tools such

as serious games and MOOCs, to fight psychological

abuse, verbal and social bullying, as presented in the

work of Raminhos et al. (2015). However, very little

information was found on tools to fight sexual

bullying and verbal bullying.

Figure 2: Comparison between EC6: Types of Application

and EC8: Types of harassment.

A Systematic Literature Review on Technological Solutions to Fight Bullying and Cyberbullying in Academic Environments

417

4.4 Phases and Area of Study

Figure 3 compares the criteria EC16: Phases and

EC22: Area of study, in order to know how research

is being carried out in relation to the technology

developed for bullying and cyberbullying. As a result,

the area of computer science, psychology and

electronics, are conducting multiple researches that

are mostly in the phase of analysis, implementation

and testing, as presented by Cohen et al. (2014) and

Silva et al., (2018). The education area presents, to a

lesser extent, studies in the analysis and testing phase.

On the other hand, in the area of medicine, no

research, promoting new technologies has been

found.

Figure 3: Comparison between EC16: Phases and EC22:

Area of study.

5 CONCLUSIONS

Nowadays, bullying and cyberbullying have

increased due to the use of technological devices,

causing severe consequences for the victims and the

surrounding community. For this reason, there is a

need to create tools and technical solutions to fight

this problem.

This research is an advance in state of the art in

this domain, which can help to define what types of

tools are currently being developed and which are not,

to identify research gaps and to create new solutions

or improve existing ones, to obtain greater

effectiveness when used with children and

adolescents in the school and social environment.

The methodology proposed by Barbara

Kitchenham was used to perform the review, which

consists of three phases: planning, conducting, and

reporting the review. This SLR was conducted with

32 primary studies from several digital libraries such

as Redalyc, IEEEXplore, Scielo, ACM Digital

Library, SpringerLink, Science Direct, PUBMED.

Most of the created tools are used in the school

environment for students and teachers (MOOCS,

Apps, Serious Games). However, there are few tools

aimed at other environments and users (parents and

authorities). On the other hand, for the creation of

detection systems, artificial intelligence such as data

mining and machine learning are used to detect

bullying and cyberbullying, especially in social

networks. In addition, this SLR has found that there

are not many tools to combat sexual and verbal

harassment. Therefore, most studies are in the

analysis phase in computer science, psychology, and

electronics.

This work has made it possible to know the state

of the art of this problem and the variety of tools

aimed at different populations to reduce bullying and

cyberbullying in other areas of daily life, especially in

children and adolescents.

ACKNOWLEDGEMENTS

This work is part of the research project “Fog

Computing applied to monitoring devices used in

assisted living environments. Case study: platform

for the elderly”, hence, the authors thank to DIUC of

Universidad de Cuenca for its academic and financial

support. Also, the authors would like to thank to

CEDIA for the academic support given to the present

research, development, and innovation work through

its CEPRA program, especially for the

“Implementation and Deployment of Learning

Capsules to Combat Bullying and cyberbullying in

Boys, Girls and Adolescents” fund.

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