A CRITICAL ANALYSIS ON CYBERBULLYING AND ITS EFFECTS IN INDIA BY - ROSY KUMAR & PRAVEEN ANANDHAN
A CRITICAL ANALYSIS ON
CYBERBULLYING AND ITS EFFECTS IN INDIA
ABSTRACT
Cyber bullying is becoming a major
concern surrounding adolescents and undergraduate populations because of the
increased use of the internet and social networking sites. It’s one of the
major causes of depression worldwide in the current era. The advances in
internet and Information Communication Technology (ICT) has facilitated cyber
bullying. It’s crucial to remember that cyber bullying is not just about “kids
being kids” – it can have serious psychological consequences on adult as well. There
are many different ways in which cyber bullies reach their victims, including
instant messaging over the internet, social media etc. There are various forms
of cyber bullying including harassment, impersonation, and cyber stalking. Like
bullying, cyber bullying is a serious problem which can cause the victim to
feel inadequate and overly self-conscious, along with the possibility of
committing suicide. In this research, the sampling method used is convenient
sampling and the sample size is 212 people. The sample frame included friends,
families and people in my neighbourhood. The findings from this research can be
used to learn and acquire more knowledge about cyber bullying and the struggles
the cyber bullying victims face in their day-to-day lives. The other important
finding is to see whether there is any correlation between cyber bullying and
academic, social, and emotional development. Cyber bullying incidents can be
reduced by creating a safer digital environment that requires a collective
effort from individuals, families, schools and online platforms to cultivate a
culture of respect and understanding for each other.
KEYWORDS: Cyber
bullying, Adolescents, Harassment, Cyber stalking, Suicide
INTRODUCTION
When the thought of bullying arises,
many people think of physical altercations or face-to-face harassment. Cyber
bullying is a relatively new term that takes on a whole new form of bullying. Cyber
bullying is a form of bullying that occurs through electronic technology
including texting, email, messaging through social media, etc. Bullying is not
a new phenomenon, but the widespread adoption of new communication technologies
has enabled the migration of bullying behaviour to cyberspace, a phenomenon
widely characterised as cyber bullying. Usage of social media has increased in
recent times among teenagers after the COVID-19 pandemic. Cyber bullying is of
growing concern to parents, police, educators and the public in general because
of its increased prevalence and the fact that it has been implicated as a
factor in several teen suicides. The Indian Computer Emergency Response Team
(CERT-In) has led to a reduction in cyber-attacks on government networks due to
its advancement in tackling the nation’s cyber security. Cyber Surakshit Bharat
is an initiative from the Ministry of Electronics and Information Technology
(MeitY) that pointed at creating a robust cyber security ecosystem in India. As
a part of Indian Government Initiatives on Cyber security, to safeguard
critical information relevant to national security, economic development, and
public health, India has established the National Critical Information
infrastructure protection centre. A National Cyber Security Strategy 2020 is
still under development at the Indian government cyber security department
National Security Council Secretaries by the office of the National Cyber
Security Coordinator. The aim is to increase the quality of cyber security
audits will help improve cyber awareness. Victims of cyber bullying usually
suffer psychological disturbances and have low self-esteem. There is a positive
relationship between cyber victimisation and low self-esteem. Feelings of
loneliness and insecurity are more prevalent. They lose trust in everything and
everybody around them. There will be a drop of social behaviour and tend to
isolate themselves. They usually find it hard to concentrate on studies and
suffer from brain fog .Many Research concludes that these people's minds are
full of dark thoughts and almost 90 per cent of people suffer insomnia, change
of appetite and a state of fear and upset all the time. Survey and Research
found that 85 % of Indian kids are prone to cyber bullying and which is the
highest in the world. This is found to be twice the international average. Many
laws are created on the ground of cyber security but these are not implemented
effectively. People are still not aware of what is cyber bullying and hence do
not show any importance towards it. There is increased use of internet after Covid
-19 pandemic. Teenagers suffer bullying mainly because of their appearance. Out
of 10, 7 of the young people experience cyber bullying before they hit the age
of 18. After India, Brazil and the United States are marked the next highest
level for cyber bullying in the survey among 27 countries. Russia, Chile, Japan,
and France are figured at the bottom of the list .The law and punishments in
the latter are very strict and people are more civilised and the technology is
well secured.
REVIEW OF LITERATURE
Usha Mary Sharma ,Seema Ghi Singh, Esther (June 2014) aim to study the crime related to cyber and the cyber-crime
detection methods and classification methods have come up with varying levels
of success for preventing and protecting data from such attacks. Data was
collected through questionnaires. From this research, found the common areas
where cyber-crime occurs usually and also email related crimes .Case studies
regarding cyber-crimes were also mentioned in this research.
Tommy K.H.Chan, Zach W.Y.Lee (March 2021) aims to study cyber bullying in
social networking sites. The main purpose of the study is to consolidate the
existing knowledge through a literature review and analysis. The self-reported
survey method was used to solicit respondent’s prior experience with cyber
bullying victimisation and bystanders.10 research questions were found for the
future study and learnt the growing evil in the society.
Qing Li (25 May 2010) aims to explore high school student’s beliefs and behaviours
associated with cyber bullying. It also aimed at studying the aftermath of the
bullying. Data was collected from 12 students through personal interviews. One
finding is that over 40%would do nothing if they were cyber bullied, and only 1
in 10 would inform adults. Students feel reluctant to report cyber bullying to
adults in schools for various reasons.
Ghada M. Abaido (26 Sep 2019) aimed to explore the pervasiveness of cyber bullying among
university students ,its nature and venues, and their attitude towards
reporting cyber bullying in contrast to remaining silent. Data were collected
from 200 students from UAE University. It was found that 91% of the study
sample confirmed the existence of acts of cyber bullying on social media with
Instagram being the highest followed by Facebook.
Hillary Noll (2016) aims to discuss the impact of cyber bullying on today’s youth and to
explore the high school student’s experiences being an victim and to study the
relationship between these victim and suicidal thoughts. The Data was collected
through survey using both quantitative and qualitative questions. It was found
that almost all the victims face negative emotional impacts and sometimes even
suicidal thoughts.
Yehuda Peled (March 23 2019) aimed to investigate the influence of cyber bullying on the
academic, social, and emotional development of undergraduate students. It’s
objective is to provide additional data and understanding of the influence of cyber
bullying on various variables affecting undergraduate students. The data were
collected using the revised cyber bullying survey which evaluates the frequency
and media used to perpetrate cyber bullying. Correlation analysis were
conducted .It was found that 57% of the students had experienced cyber bullying
at least once or twice through different social media, instant messaging was
found to be the most common means of cyber bullying among the students.
Chengyan Zhu, Shiqing Huang, Richard Evans and Wei Zhang (March 11, 2021)
aimed to study the
impact of cyber bullying among adolescents and children and also focused on the
national and regional effects of cyber bullying. This systematic review also
examines the global situation, risk factors, and preventive measures taken
worldwide to fight cyber bullying among adolescents and children .Data was
collected through a systematic review of available literature and additional
records were identified from cyber bullying Research Centre and United Nation
Children’s Fund. It was found that verbal abuse was the common type of bullying
Michelle F.Wright, Shanmukh V. Kamble and Shruti P.Soudi aimed to examine the relationships
among cyber aggression involvement and cultural values .The data was collected
from 480 adolescents from India. The findings revealed that individualism and
collectivism were related positively to peer attachment. In addition,
individualism was associated positively with cyber aggression perpetration and
cyber victimisation, whereas these were negative for collectivism.
Laura Marciano, Peter J Schulz,Anne-Linda Camerini aims to meta -analytically summarise
56 longitudinal studies on cyber perpetration ,cyber victimisation, and related
factors in children and adolescents. Data collected from previous literature. It
was found that there were spill over effects i.e offline bullies who continue
to bully online as well as victims being bullied in the school yard also
experience episodes of bullying in cyber bullying.
Marizen Ramirez, Anthony Paik, Octav Chipara, Padmini Srinivasan, Karen
Heimer, Corinne Peek-ASA, Shelly Campo (April 2019) aimed to study the prevalence and
risk factors associated with cyber bullying and their links with offline
bullying, violence and delinquency. Data was collected from 164 adolescents
using personal interview method. The major findings of this research are that
they introduced many policies for the prevention of cyberbullying. Another
important finding is that offline bullying victims usually turns into online
victims too.
Mary Woeps (May 2020) aim is to review both online and offline prevention methods
in order to identify what works in preventing cyber bullying from happening to
young people. It also aimed at discussing the role of parents, schools in the
life of victims. The method used here is an empirical research method and
reviewed old research works also. It was found that the relationship between
adolescents and their parents is very important to prevent them from becoming a
victim and also less likely to engage in bullying behaviours.
R.Lavanya, Kalpana G. Prasad (2014) aims to study the prevalence of cyber bullying and to
also find its nature and impact. The data was collected through a survey method
conducted among students belonging to age 15 and 19 years. It was found that
over 85% of teenagers access cyberspace through their smartphones which has
exposed them to the brunt of cyber bullying.
Apoorva Bhangla and Jahanvi Tuli (2021) aimed to study cybercrime and its
legal framework. Data was collected from old books and through review of
literature. The important finding is that there is need of the hour to evolve
societal and cultural norms and development of information technology. Other
steps like digital literacy and data security are important. Strict laws with
reference to women were also introduced.
Mohammed I. Alghamdi (2020) aimed to study the impact of cyber-crimes and possible
measures to be taken to curtail its spread. This study also examines various
forms of cyber-crimes. The data was collected from previous literature studies.
It was found that harmonisation of cybercrime is needed for regulation and
legislation across the country. Also found the common computer crimes in the
world.
Michael Pittaro (2007) aims to analyse the online harassment and intimidation. The
data was collected through survey method. This paper founded the glimpse into
the deviant behaviours and tactics associated with cyber stalking crimes,
legislative intervention measures, and preventative initiatives created
specifically to curtail this emerging global crime.
Adesoji Ademiluyi, Chuqin Li, Albert park (2022) aimed at exploring implications and
preventions of cyber bully on social media .The data was collected through
review of previous literature. It was found suicidal thoughts were more
prevalent among victims and identified the detention methods for monitoring
cyber bully.
Conor Mc Guckin, Trijntje Vollink, Francine Dehue (November 2015) aims to discuss about the problem of cyber
bullying which has increased in recent times. The data was collected through
review of previous literature. It was found that cyber bullying has become more
prevalent and found the various ways of cyber bullying. It was found that cyber
bullying was a serious problem and talked about the preventive methods.
Premill D’ Cruz, Ernesto Noronto aimed to study the impact of cyberbullying in India. It also
discussed the work experiences of call agents in International call centres
especially among women. The data was collected through a survey method. It was
found from the maintenance of records that male were mostly the bully.
Lalita Minochqa, Sherayas Minocho (2017) aimed to study the prevalence of cyber
stalking and safety of teenagers on the internet. The data was collected from
200 students. It was found that exploitation of children in cyberspace can
create havoc on the victim’s mind which leads to disastrous consequences.
Brian Weismann (2011) aims at studying the increased level of cyber bullying among
school students. The data was collected through a survey method. Totally 118
surveys were conducted. Principals of 66 schools responded .It was found that
through this study it was easy to understand the concept of cyber bullying in a
better way .It was found that most of the cyber bullying victims were middle
aged people as they are more exposed to social media.
OBJECTIVES
? To study the causes of cyber bullying
? To discuss the ways to prevent
teenagers from becoming a victim of cyber bullying
? To analyse how cyber bullying had
increased in recent times
? To study the effects of cyber
bullying on the victim’s mental health
? To discuss how government can educate
people about the harm cyber bullying does
METHODOLOGY
The research method followed here is
descriptive and empirical research. A total of 200 samples have been collected
out of which all samples have been collected through convenient sampling
methods. The sample frame is in and around Poonamallee, Chennai, Tamil Nadu.
The independent variables are age, gender, educational qualifications,
occupation, and Living area. The dependent variables used here are the causes
of cyber bullying, ways to prevent teenagers from becoming a victims of cyber
bullying, how cyber bullying increased in recent times, effects of cyber
bullying on the victim’s mental health. The statistical tools used here is
Percentage analysis, Bar charts, Pie charts, Chi-square and ANOVA.
DATA AND ANALYSIS
FIGURE 1
Legend Fig 1 shows
the graph of respondent’s opinion regarding the causes of cyber bullying.
FIGURE 2
Legend Fig 2 Shows that graph of respondent’s opinion on ways to
prevent from becoming a victim of cyber bullying
FIGURE 3
Legend Fig 3. Shows the graph of different gender
respondent’s opinions regarding the causes of cyber bullying.
FIGURE 4
Legend Fig 4. Shows the graph of respondents living
in different areas and their opinion on causes of cyber bullying.
FIGURE 5
Legend Fig 5. Shows the graph of respondents of
different gender and their opinions regarding the ways to prevent from becoming
a victim of cyber bullying.
FIGURE 6
Legend Fig 6 shows
the graph of respondents with different occupations and their opinions
regarding the ways to prevent from becoming a victim of cyber bullying.
FIGURE 7
Legend Fig 7 shows the graph of respondents living
in different areas and their opinions regarding the ways to prevent from
becoming a victim of cyber bullying.
FIGURE 8
Legend Fig 8 shows
the graph of respondents of different age groups and how they rate the
increasing issue of cyber bullying in recent times.
FIGURE 9
Legend Fig 9 shows
the graph of respondents of different educational qualifications and how they
rate the increasing issue of cyber bullying in recent times.
FIGURE 10
Legend Fig 10 shows
the graph of respondents of different occupations and how they rate the
increasing issue of cyber bullying in recent times.
FIGURE 11
Legend Fig 11 shows
the graph of respondents living in different areas and how they rate the increasing
issue of cyber bullying in recent times.
FIGURE 12
Legend Fig 12 shows
the graph between respondents of different age groups and their opinion whether
cyber bullying is a punishable crime.
FIGURE 13
Legend Fig 13 shows
the graph between respondents of different gender and their opinion whether cyber
bullying is a punishable crime.
FIGURE 14
Legend Fig 14 shows
the graph between respondents of different educational qualifications and their
opinion whether cyber bullying is a punishable crime.
FIGURE 15
Legend Fig 15 shows
the graph between respondents of different occupations and their opinion
whether cyber bullying is a punishable crime.
FIGURE 16
Legend Fig 16 shows
the graph between respondents living in different areas and their opinion
whether cyber bullying is a punishable crime.
FIGURE 17
Legend Fig 17 shows
the graph of respondents belonging to different age groups and their opinion on
the effects of cyber bullying on the victim in terms of insomnia.
FIGURE 18
Legend Fig 18
shows the graph of respondents belonging to different genders and their opinion
on the effects of cyber bullying on the victim in terms of insomnia.
FIGURE 19
Legend Fig 19 shows
the graph of respondents belonging to different age groups and their opinion on
the effects of cyber bullying on the victim in terms of suicidal thoughts.
FIGURE 20
Legend Fig 20 shows
the graph of respondents belonging to different genders and their opinion on
the effects of cyber bullying on the victim in terms of suicidal thoughts.
RESULTS
Fig 1 shows
that almost 35 per cent of respondents responded that the victim might turn himself
as a bully to vent out the anger and almost equal number of people chose
revenge motive and due to addiction. Fig
2. Shows that almost 47 per cent of respondents responded by raising
awareness and setting up privacy control. Fig
3. Shows that most of the female respondents chose psychological distress
as the main cause and male respondents chose the option victims might turn into
a bully to vent out his anger. Fig 4. 90 per cent of the urban respondents
responded to psychological distress and rural respondents responded because of
a revenge motive. Fig 5.shows that
most of the females and males chose raising awareness and setting up privacy
control is important compared to others. Fig
6. Shows that most of the unemployed respondents I.e. studying part of the society
and respondents working in private sectors felt that raising awareness and
setting up privacy control in all the devices we use is important. Fig 7. Shows that most of the respondents living in urban areas
felt that raising awareness and setting up privacy control in all the devices
we use is important. Fig 8. Shows
that respondents belonging to the age group less than 20 years chose 7 which
means moderately increased and respondents of age group 21-30 years chose 9
implicating that cyber bullying has increased in recent times. Fig 9 Shows that most of the undergraduate
students rated 7 i.e. moderately increased and post graduate students rated 9
which means highly increased. Fig 10
Shows that most of the unemployed respondents rated 6 and 7 i.e. moderately
increased and respondents working in the private sector rated 9 and 10 which
means highly increased. Fig 11 Shows
that most of the respondents living in urban areas rated 6 and 7 i.e.
moderately increased and respondents living in rural areas rated 9 and 10 which
means highly increased. Semi urban area respondents rated 8 which is also
highly increased. Fig 12 Shows that
respondents belonging to the age group less than 20 years responded neutral
that is they don’t have proper answers for this question and respondents
belonging to the age group 31-40 years agree that it is a punishable offence. Fig 13. Shows that most of the female
respondents agreed that it is a punishable offence. Male respondents disagreed
that it is not a punishable offence. Fig
14 Shows that most of the undergraduate respondents and postgraduate
respondents agreed that it is a punishable offence. Fig 15 Shows that most of the respondents working in private
sectors agreed that it is a punishable offence. Almost equal number of
unemployed respondents gave neutral answers. Fig 16 Shows that most of the respondents living in urban areas
agreed that it is a punishable offence.
Fig 17 shows that respondents belonging to the age group less than 20 years
responded neither agree nor disagree and respondents belonging to the age group
31 to 40 years strongly agreed that insomnia is one of the effects of cyber
bullying. Fig. 18 shows that most of
the female respondents neither agree nor disagree and male respondents agreed
that insomnia is one of the effects of cyber bullying. Fig 19 shows that equal
number of respondents belonging to the age group less than 20 years agreed as
well as disagrees and respondents of age group 31-40 years agreed that suicidal
thoughts are more prone among victims of cyber bully. Fig 20 shows that most of
the female respondents agreed and male respondents disagreed that suicidal
thoughts is one of the effects of cyber bullying.
DISCUSSIONS
Fig 1 shows
that most of the people opted for option 3 i.e. victim might turn himself as a
bully to vent out his anger. This may be because people usually are mentally
disturbed after undergoing a difficult phase of their life being a victim so
they tend to bully others. Fig 2 shows
that respondents feel that awareness is still needed regarding cyber bullying
as people are still not aware of cyber-crimes and its seriousness. Fig3. Females usually have mood swings
and hormonal imbalance so this may be the reason for them to choose
psychological distress. Males usually are the ones who are more aggressive
compared to females. So this may be the reason for them to choose the option
victim might turn himself as a bully to vent out the anger. Fig 4.Urban people are more aware of cyber bullying and its causes
and most of the people in urban areas usually suffer from mental disturbance
like depression etc.. So this may be the reason for them to choose
psychological distress. Fig. 5 Shows
that most of the females and males chose raising awareness and setting up
privacy control is important compared to others. This may be because the
awareness among common people about cyber bullying is still less and people
tend to take the issue of cyber bullying lightly. Fig 6 Shows that most of the unemployed respondents i.e. studying
part of the society and respondents working in private sectors felt that
raising awareness and setting up privacy control in all the devices we use is
important. This may be because the awareness among common people about cyber
bullying is still less and people tend to take the issue of cyber bullying
lightly. Fig 7 shows that most of
the respondents living in urban areas felt that raising awareness and setting
up privacy control in all the devices we use is important. This may be because
the awareness among common people about cyber bullying is still less and people
tend to take the issue of cyber bullying lightly. Fig 8. Shows that respondents belonging to the age group less than
20 years chose 7 which means moderately increased and respondents of age group
21-30 years chose 9 implicating that cyber bullying has increased in recent
times. Almost all the respondents rated above 5. Internet usage and cyber
bullying are directly proportional. Usage of the internet has increased in
recent times hence cyber bullying also increased. Many people try to misuse the
technology for their pass time and cause trouble to the other fellow citizens. Fig 9.Shows that most of the undergraduate
students rated 7 i.e. moderately increased and post graduate students rated 9
which means highly increased. Internet usage and cyber bullying are directly
proportional. Usage of the internet has increased in recent times hence cyber
bullying also increased. Many people try to misuse the technology for their
pass time and cause trouble to the other fellow citizens. Fig 10 .Shows that most of the unemployed respondents rated 6 and
7 i.e. moderately increased and respondents working in the private sector rated
9 and 10 which means highly increased. Internet usage and cyber bullying are
directly proportional. Usage of the internet has increased in recent times
hence cyber bullying also increased. Many people try to misuse the technology
for their pass time and cause trouble to the other fellow citizens. Fig 11 .Shows that most of the
respondents living in urban areas rated 6 and 7 i.e. moderately increased and
respondents living in rural areas rated 9 and 10 which means highly increased.
Semi urban area respondents rated 8 which are also highly increased. Internet
usage and cyber bullying are directly proportional. Usage of the internet has
increased in recent times hence cyber bullying also increased. Many people try
to misuse the technology for their pass time and cause trouble to the other
fellow citizens. Fig 12 Shows that
respondents belonging to the age group less than 20 years responded neutral,
that is they don’t have proper answers for this question because maybe this age
group people are the ones who bully themselves so they responded neutral. Respondents
belonging to the age group 31-40 years agreed that it is a punishable offence.
This may be because these respondents are middle aged people who are well aware
of the seriousness of this issue and have a broader view on this issue of cyber
bullying. Fig. 13 shows that most of
the female respondents agreed that it is a punishable offence. This may be
because these respondents are well aware of the seriousness of this issue and
have a broader view on this issue of cyber bullying. Male respondents disagreed
that it is not a punishable offence. Past surveys given by various scholars
conclude that males are the major bully in these cyber-crimes compared to
females so maybe they would have disagreed.
Fig 14 Shows that most of the undergraduate respondents and postgraduate
respondents agreed that it is a punishable offence. This may be because these
respondents are well aware of the seriousness of this issue and have a broader
view on this issue of cyber bullying.
Fig. 15 shows that most of the respondents working in private sectors
agreed that it is a punishable offence. This may be because these respondents
are well aware of the seriousness of this issue and have a broader view on this
issue of cyber bullying. Almost equal number of unemployed respondents gave
neutral answers. Since these people don’t have any jobs and in order to pass
their time, they indulge in such activities as matters of fun and joy and later
tend to get addicted to it. So this may be the reason for them to give neutral
answers since they themselves are involved in this. Fig 16 Shows that most of the respondents living in urban areas
agreed that it is a punishable offence. This may be because these respondents
are well aware of the seriousness of this issue and have a broader view on this
issue of cyber bullying. Fig 17
shows that respondents belonging to the age group 31 to 40 years strongly
agreed that insomnia is one of the effects of cyber bullying. This may be
because these people are middle aged and hence they are well aware of the
aftermath trauma that everyone undergoes after being a victim of some criminal
offences. Fig 18 shows that female
respondents responded neither agree nor disagree. This may be because females
are usually the victims of these online crimes. Some women come forward to talk
about their incident in order to create awareness while some don’t. Fig 19 that an equal number of
respondents belonging to the age group
less than 20 years agreed as well as disagreed. There are two groups of people,
one who end their life after a difficult phase in their life while other strive
in hard times and set an example to the others. So some people agreed that
suicidal thoughts are more prone among the victims because this age group
people are usually victims of these online crimes. Respondents of age group
31-40 years agreed that suicidal thoughts are more prone among victims of cyber
bully. This may be because these respondents are well aware of the seriousness
of this issue and have a broader view on this issue of cyber bullying. Fig 20 shows that female respondents
agreed. This may be because females are usually the victims of these online
crimes and they themselves experience the aftermath of these cyber incidents.
CHI- SQUARE ANALYSIS 1
NULL HYPOTHESIS: There is no
association between age and the causes of cyber bullying.
ALTERNATE HYPOTHESIS: There is
association between age and the causes of cyber bullying.
INTERPRETATION:
The calculated P value is 0.000. Since the P value is less than 0.05 null
hypothesis is rejected at any 5% level of significance. So there is an
association between age and the causes of cyber bullying.
CHI- SQUARE ANALYSIS 2
NULL HYPOTHESIS: There is no association
between gender and the causes of cyber bullying.
ALTERNATE HYPOTHESIS: There is
association between gender and the causes of cyber bullying.
INTERPRETATION:
The calculated P value is 0.000. Since the P value is less than 0.05 null
hypothesis is rejected at any 5% level of significance. So there is an
association between gender and the causes of cyber bullying.
CHI- SQUARE ANALYSIS 3
NULL HYPOTHESIS: There is no
association between respondents with different educational qualifications and
the causes of cyber bullying.
ALTERNATE HYPOTHESIS: There is an
association between respondents with different educational qualifications and
the causes of cyber bullying.
INTERPRETATION:
The calculated P value is 0.000. Since the P value is less than 0.05 null
hypothesis is rejected at any 5% level of significance. So there is an
association between respondents with different educational qualifications and
the causes of cyber bullying.
CHI- SQUARE ANALYSIS 4
NULL HYPOTHESIS: There is no
association between respondents with different occupations and the causes of cyber
bullying.
ALTERNATE HYPOTHESIS: There is an association
between respondents with different occupations and the causes of cyber bullying.
INTERPRETATION:
The calculated P value is 0.000. Since the P value is less than 0.05 null
hypothesis is rejected at any 5% level of significance. So there is an
association between respondents with different occupations and the causes of cyber
bullying.
CHI- SQUARE ANALYSIS 5
NULL HYPOTHESIS: There is no
association between respondents with different monthly incomes and the causes
of cyber bullying.
ALTERNATE HYPOTHESIS: There is an
association between respondents with different monthly incomes and the causes
of cyber bullying.
INTERPRETATION:
The calculated P value is 0.000. Since the P value is less than 0.05 null
hypothesis is rejected at any 5% level of significance. So there is an
association between respondents with different monthly incomes and the causes
of cyber bullying.
ONE WAY ANOVA 1
NULL HYPOTHESIS: There is no significant difference between respondent’s opinion whether cyber
bullying is a severe and punishable crime or not and respondent’s age.
ALTERNATE HYPOTHESIS: There is a significant difference between respondent’s opinion whether cyber
bullying is a severe and punishable crime or not and respondent’s age.
INTERPRETATION:
The calculated P value is 0.035. Since P value <0.05, null hypothesis is
rejected. So there is a significant difference between the respondent's opinion
whether cyber bullying is a severe and punishable crime or not and the
respondent's age.
ONE WAY ANOVA 2
NULL HYPOTHESIS: There is no significant difference between respondent’s opinion whether cyber
bullying is a severe and punishable crime or not and respondent’s gender.
ALTERNATE HYPOTHESIS: There is a significant difference between respondent’s opinion whether cyber
bullying is a severe and punishable crime or not and respondent’s gender.
INTERPRETATION:
The calculated P value is 0.001. Since P value <0.05, null hypothesis is
rejected. So there is a significant difference between the respondent's opinion
whether cyber bullying is a severe and punishable crime or not and the
respondent's gender.
ONE WAY ANOVA 3
NULL HYPOTHESIS: There is no significant difference between respondent’s opinion whether cyber
bullying is a severe and punishable crime or not and respondent’s educational
institutions.
ALTERNATE HYPOTHESIS: There is a significant difference between respondent’s opinion whether cyber
bullying is a severe and punishable crime or not and respondents' educational
institutions.
INTERPRETATION:
The calculated P value is 0.033. Since P value <0.05, null hypothesis is
rejected. So there is a significant difference between the respondent's opinion
whether cyber bullying is a severe and punishable crime or not and the
respondent's educational institutions.
ONE WAY ANOVA 4
NULL HYPOTHESIS: There is no
significant difference between respondent’s opinion whether cyber bullying is a
severe and punishable crime or not and respondent’s occupations.
ALTERNATE HYPOTHESIS: There is a
significant difference between respondent’s opinion whether cyber bullying is a
severe and punishable crime or not and respondents' occupations..
INTERPRETATION:
The calculated P value is 0.334. Since P value <0.05, null hypothesis is
rejected. So there is a significant difference between the respondent's opinion
whether cyber bullying is a severe and punishable crime or not and the
respondent's occupations.
ONE WAY ANOVA 5
NULL HYPOTHESIS: There is no significant difference between respondent’s opinion whether cyber
bullying is a severe and punishable crime or not and respondent’s monthly
incomes.
ALTERNATE HYPOTHESIS: There is a significant difference between respondent’s opinion whether cyber
bullying is a severe and punishable crime or not and respondents' monthly
incomes.
INTERPRETATION:
The calculated P value is 0.00. Since P value <0.05, null hypothesis is
rejected. So there is a significant difference between the respondent's opinion
whether cyber bullying is a severe and punishable crime or not and the
respondent's monthly incomes.
SUGGESTION
Research on the effects of cyber
bullying in India could focus on several key areas. One approach is to
investigate the psychological impacts on adolescents, exploring issues like
anxiety and depression through surveys and interviews. Cultural factors could
be examined to understand regional differences, while studies on the
effectiveness of existing anti-cyber bullying programs in schools may reveal
gaps that require new strategies. Additionally, research could delve into
gender differences in experiences, the correlation between cyber bullying and
academic performance, and the effectiveness of India's legal frameworks.
Exploring social media platforms' roles and conducting longitudinal studies to
track long-term effects on victims could provide further insights. Lastly,
assessing community awareness and proposing educational programs could enhance
prevention efforts.
CONCLUSION
Cyber bullying continues to be a
disturbing trend not only among adolescents but also undergraduate students and
postgraduate students .Students use the internet as a medium and use it with
great frequency in their everyday lives. The purpose of this study is to
explore the experiences of people who have been victimised by cyber bullying. The
findings revealed that there is correlation between cyber bullying and
academic, social, and emotional development. Through this research, it has been
found that there are many ways and means through which an individual commit
crimes in cyberspace. The findings of this study are important and useful for
social workers to gain insight into the experiences faced by the victims of
cyber bullying. Cyber Crimes are an offence and are punishable by laws. It is
not the computers that are harming and attacking organisations, instead it is
the humans who are exploiting the technology to cause damage. So it is
necessary to be aware of these alarming crimes in cyberspace and think before
posting anything in the media.
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1
Rosy Kumar, Assistant Professor,
Saveetha School of Law, Saveetha Institute of Medical and Technical Sciences
(SIMATS), Email Id:rosykumar24@gmail.com,
Contact No: 8098174415
[2] Praveen
Anandhan, Reg No:- 132301058, B.A LLB.(Hons) 2nd Year, Saveetha School of Law,
Saveetha Institute of Medical and Technical Sciences (SIMATS), Email Id:praveenanandhan10@gmail.com,
Contact No: 8015558755