Volume 14.
Number 1.
March 2025 http://dx.
org/10.
17977/um023v14i12025p1-13 Social Dominance Orientation as a Predictor of Cyber Aggression Behavior During the 2024 Indonesian General Election on Social Media X Zefanya Angelique Napitupulu1.
Jati Fatmawiyati2 Department of Psychology.
Faculty of Psychology.
Universitas Negeri Malang
Article Information Submitted date
05-09-2024
Revised date
06-02-2025
Accepted date
10-02-2025
Keywords:
social dominance orientation.
cyber aggression.
Indonesian General Election Kata kunci:
orientasi dominasi sosial.
agresi siber.
Pemilu Indonesia 2024.
Correspondence concerning this article should be addressed to Zefanya Angelique Napitupulu.
Semarang Street.
No.
Malang.
East Java.
Indonesia 65145.
Email:
zefanyaangelique@gmail.
Abstract Cyber aggression has become a significant concern during the 2024 Indonesian General Election.
Social dominance orientation is one of the factors suspected to correlate with cyber aggression.
Based on this premise, this research aims to investigate the predictive relationship between social dominance orientation and cyber aggression in the context of the 2024 Indonesian General Election on social media X.
The research employs a quantitative correlational approach with a sample of 286 X users aged 22Ae40 years, selected using purposive sampling techniques.
The measurement tools utilized in this research are the Social Dominance Orientation-7 (SDO-.
and the Cyber Aggression Questionnaire for Adolescents (CYBA).
The data analysis technique applied is simple linear regression analysis.
The results reveal that social dominance orientation predicts or contributes 10.
7% to cyber aggression during the 2024 Indonesian General Election on the X (R2 = .
=33.
p < .
Abstrak Agresi siber menjadi masalah yang cukup menjadi perhatian pada masa Pemilu Indonesia 2024.
Orientasi dominasi sosial menjadi salah satu faktor yang diduga berkolerasi dengan perilaku agresi siber.
Berdasarkan hal tersebut, penelitian ini bertujuan untuk menyelidiki hubungan prediktif antara orientasi dominasi sosial dengan perilaku agresi siber dalam konteks Pemilu Indonesia 2024 di media sosial X.
Penelitian menggunakan pendekatan kuantitatif korelasional dengan jumlah responden yang menjadi sampel sebanyak 286 pengguna X berusia 22Ae40 tahun dengan teknik purposive Alat ukur yang digunakan dalam penelitian ini adalah skala Social Dominance Orientation-7 (SDO-.
dan Cyber Aggression Questionnaire for Adolscents (CYBA).
Teknik analisis data yang digunakan adalah analisis regresi linier sederhana.
Hasil menunjukkan bahwa orientasi dominasi sosial memprediksi atau berkontribusi sebesar 10.
7% terhadap perilaku agresi siber pada masa Pemilu Indonesia 2024 di X (R2 = 0.
= 33.
INTRODUCTION
Elections are a key element in a countryAos democratic system.
In Indonesia, elections are not merely a mechanism to determine who will hold power but also represent the pinnacle of public political participation in shaping the nationAos direction and vision (Alvons, 2.
Amid the continuously evolving political dynamics, it is important to emphasize that elections should be conducted peacefully and Healthy elections are characterized by diversity of opinions and political pluralism, ensuring that citizens have the right to voice their opinions and choose their representatives without 2 | Napitupulu & Fatmawiyati - Social Dominance Orientation.
fear or influence from intimidation, discrimination, repression, violence, or divisive rhetoric.
Election outcomes conducted in an environment that enables freedom of expression and association are considered to reasonably reflect public participation and societal aspirations with a high degree of accuracy (Alvons, 2.
Therefore, it is crucial for all stakeholders in the electoral processAicandidates, political parties, and the general publicAito maintain attitudes that prioritize tolerance, dialogue, and openness.
Unfortunately, in practice, amidst the dynamics of democracy, significant challenges arise, one of which is online attacks or cyber aggression.
Mardianto .
explains that various terms are used to describe online attack behaviors, with differences in terminology across studies stemming from diverse scientific approaches.
This reflects the growing research focus on aggressive behaviors in the digital realm.
Identifiable terms include hate speech .
yberhate, online hate speec.
, online attacks or cyber aggression .
yberbullying, electronic aggressio.
, and cyber violence .
yber victimization, cyber harassmen.
Cyber aggression is a commonly used term that provides a more general definition of online attack behaviors.
Garcya et al.
defines cyber aggression as intentional behavior aimed at harming an individual or group of people through devices and the Internet.
Garcya et al.
identifies three dimensions of cyber aggression: impersonation, visual-sexual cyber aggression, and verbal cyber aggression and exclusion.
Impersonation involves imitative behaviors, such as using someoneAos account without permission or adopting another personAos identity on social media without consent.
Visualsexual cyber aggression refers to visual and sexual aggression behaviors, such as sharing photos or screenshots of vulgar conversations on social media without the concerned individualAos consent.
Verbal, cyber aggression and exclusion encompass verbal aggression behaviors, such as posting negative comments aimed at harming others online, defamation, ostracizing, or belittling others with the intent to cause harm.
A key characteristic of cyber aggression is targeting individuals or collective identities that possess, or are perceived by the aggressor to possess specific characteristics Hawdon et al.
, and this behavior often occurs sporadically and is triggered by social or political events (Kaakinen et al.
, 2.
Hate speech on social media is a form of cyber aggression that arises from dissatisfaction with specific individuals or groupsAo behavior, statements, activities, performance, or lifestyles (Bada et al.
According to a Circular Letter from the Indonesian National Police Chief No.
06/X/2015 concerning the Handling of Hate Speech (Surat Edaran Kapolri No.
06/X/2015 tentang Penanganan Ujaran Kebencian.
Suroso, 2.
, hate speech is defined as actions involving violations such as defamation, insults, blasphemy, unpleasant conduct, provocation, incitement, and the dissemination of false information, which can have negative impacts leading to discrimination, violence, loss of life, or social conflict.
The regulation and criminal accountability for hate speech through social media are stipulated in Law of the Republic of Indonesia No.
11 of 2008 concerning Electronic Information and Transactions (Undang-Undang Republik Indonesia No.
11 Tahun 2008 tentang Informasi dan Transaksi Elektroni.
Article 28 Paragraph .
, which states.
AuAny Person who knowingly and without authority disseminates information aimed at inflicting hatred or dissension on individuals and/or certain groups of community based on ethnic groups, religions, races, and intergroupsAy (Suroso, 2.
Individuals proven to meet the elements of such criminal acts, under Law of the Republic of Indonesia No.
19 of 2016 concerning Amendments to Law No.
11 of 2008 (UndangUndang Republik Indonesia No.
19 Tahun 2016 tentang Perubahan atas Undang-Undang No.
11 Tahun 2.
Article 45A Paragraph .
, may face a maximum imprisonment of 6 years and/or a maximum fine of Rp1,000,000,000 (Suroso, 2.
Therefore, cyber aggression, including hate speech.
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should not be committed as explicit legal provisions govern it.
With clear and firm legal regulations, society is expected to use social media more wisely and responsibly.
Kardiyasa et al.
explain that cyber aggression has become an increasingly alarming phenomenon, particularly during election campaign periods.
This is reflected in the rise of verbal violence, insults, the spread of hoaxes, and rhetoric in political dialogue and competition.
X, formerly known as Twitter, is one of the most popular and influential social media platforms in Indonesia.
often serves as a medium for the rapid and widespread dissemination of cyber aggression.
Through features such as retweets, quote tweets, and mentions, pejorative, intolerant, or provocative messages can quickly spread, influencing public opinion and the overall political atmosphere.
During the 2019 General Election, there were more than 200,000 mentions of hate speech targeting both presidential candidate pairs on X (Setiawandari & Munandar, 2.
According to recent data collected by Monash University and AJI Indonesia (Muhamad, 2.
, over approximately five months (September 2023AeJanuary 2.
X ranked first in the number of hate speech incidents during the 2024 election campaign, with 120,381 tweets, followed by Facebook with 56,780 and Instagram with 4,472.
Furthermore, in a subsequent three-month period (January 2024AeMarch 2.
X remained in first place with 48,502 tweets, followed by Facebook with 24,394 and Instagram with 565.
The rapid development of information and communication technology, mainly through social media, has created a broader space for spreading cyber aggression.
Jati .
explains that cyberspace, or the digital public sphere, provides an environment that facilitates access to algorithms tailored to specific interests or issues deemed appealing by its users.
These digital platforms ultimately become arenas for individuals or groups to disseminate messages that provoke conflict and undermine unity.
This phenomenon highlights that X is a significant space for individuals or groups to express negative attitudes toward the three presidential candidate pairs before, during, or after the election period.
In these times, politics often becomes a battlefield filled with emotions and tensions, which, unfortunately, are frequently exploited by certain parties to disseminate messages that have the potential to divide society.
Indonesia, as a country with diverse cultures, religions, and ethnicities, is particularly vulnerable to divisions that could be triggered by cyber aggression.
Severe forms of cyber aggression can lead to legal consequences.
If hate speech is not addressed effectively and efficiently following applicable legal provisions, severe impacts such as social conflict may arise, potentially leading to acts of discrimination, violence, or even threatening individualsAo lives.
Beran et al.
also emphasize that the psychological impact of cyber aggression on victims can reach a level of severity comparable to that experienced by victims of sexual harassment.
One factor influencing cyber aggression is social dominance orientation (Castellanos et al.
, 2024.
Celuch et al.
, 2022.
Winiewski et al.
, 2.
Social dominance orientation is explained within the framework of social dominance theory, proposed by Sidanius and Pratto .
This theory posits that the primary factor driving prejudice and intergroup discrimination is social dominance orientation.
Individuals with high social dominance orientation tend to believe in a societal division into two groups: high-status groups and low-status groups, where high-status groups are perceived as winners possessing power and positive attributes.
Social dominance orientation consists of two main dimensions.
SDO-D and SDO-E, and two subdimensions: pro-trait and con-trait (Ho et al.
, 2.
SDO-D
reflects support for hierarchical dominance within society, while SDO-E reflects support for group Pro-trait and con-trait describe the direction of statements in the items.
High scores on protrait indicate high levels of social dominance orientation, whereas high scores on con-trait indicate low levels.
4 | Napitupulu & Fatmawiyati - Social Dominance Orientation.
A preliminary study was conducted to complement these findings using an open-ended questionnaire distributed to 20 X users via Google Forms.
The results showed that X users in Indonesia frequently engage in cyber aggression related to the 2024 Indonesian General Election for various reasons that reflect social dominance orientation.
First, many users felt that their political group was superior to others, which led them to believe they had the right to attack political opponents online.
Second, there was a perception that cyber-attacks could strengthen their groupAos social position by weakening opponents through online intimidation and harassment.
Furthermore, some respondents indicated that cyber aggression effectively maintained the status quo and prevented changes that could threaten their groupAos dominance.
Celuch et al.
showed that young adults in six countries (Finland.
France.
Poland.
Spain, the UK, and the US) exhibited a positive correlation between social dominance orientation and acceptance of cyber aggression behavior.
The study found justifications for cyber aggression among individuals who believe in social dominance orientation.
Other previous studies (Castellanos et al.
, 2024.
Winiewski et al.
, 2.
also found a positive correlation between hate speech behavior and social dominance orientation.
Social dominance orientation refers to an individualAos attitude toward inequality among social groups (Pratto et al.
, 1.
An individual with a social dominance orientation believes that some groups are significantly superior to others.
Based on the explanation above, social dominance orientation may be related to cyber aggression for the following reasons.
Individuals with high social dominance orientation tend to have a strong need to maintain and reinforce social hierarchies.
In the digital context, they may use cyber aggression to assert power and maintain their dominant position, especially against individuals or groups perceived as threats.
The competitive and hierarchical worldview held by individuals with high social dominance orientation often legitimizes the use of aggression to achieve goals or maintain status, including in the form of cyber aggression.
With its anonymity, social media provides an ideal platform for these individuals to engage in cyber aggression without fear of immediate consequences.
Previous research (Celuch et al.
, 2.
also shows that social dominance orientation correlates with various forms of aggressive behavior and prejudice, so it is unsurprising that individuals with high social dominance orientation also tend to engage in cyber aggression.
Furthermore, moral disengagement theory explains that individuals with high social dominance orientation may justify their aggressive behavior by viewing it as acceptable or moral in pursuit of a greater goal, such as maintaining or enhancing their social status.
As far as has been explored, research on the relationship between social dominance orientation and cyber aggression has never been conducted in Indonesia.
Previous research has been conducted in several Western countries, including Finland.
France.
Germany.
Switzerland.
Poland.
Spain, the UK, and the US (Castellanos et al.
, 2024.
Celuch et al.
, 2022.
Winiewski et al.
, 2.
This motivates investigating the relationship between social dominance orientation and cyber aggression, specifically in the Indonesian General Election period context.
Based on the previous discussion, this research hypothesizes a predictive relationship between social dominance orientation and cyber aggression behavior during the 2024 Indonesian General Election on X.
With an understanding of the predictive relationship between social dominance orientation and cyber aggression behavior on X during the 2024 Indonesian General Election, it is hoped that this research will provide valuable insights for stakeholders, including the government, social media platforms, political parties, and civil society, in efforts to maintain the integrity of the general election and strengthen the foundations of democracy in Indonesia.
In doing so, a conducive public space can be created as a meaningful and constructive forum for discussion.
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METHODS
This research investigates the predictive relationship between social dominance orientation and cyber aggression behavior in the political context of online media.
This research employs a quantitative approach to examine the predictive relationship between the independent variable, social dominance orientation, and the dependent variable, cyber aggression.
The sampling was conducted using a non-probability sampling method with purposive sampling.
This technique was employed because not all population members have the same opportunity to be included in the sample.
Sugiyono .
states that purposive sampling is based on specific criteria or considerations.
In other words, the sample is selected based on criteria predetermined, including individuals aged 22Ae40 years, which corresponds to the early adulthood to middle adulthood range (Santrock, 2.
, who use X and have sent tweets, retweeted, or liked posts containing hate speech related to the 2024 Indonesian Election.
In this research, the sample size was determined using the Lemeshow formula, as the total population size was unknown or considered to be unlimited.
Based on the Lemeshow formula, the minimum sample size for representativeness is 96.
To improve the quality and representativeness of the results, the sample size was increased.
The final sample size obtained was 312 X users, which was later processed for extreme data removal, resulting in a final sample of 286 respondents.
The measurement of social dominance orientation was conducted using the Social Dominance Orientation-7 (SDO-.
scale developed by Ho et al.
based on the social dominance theory formulated by Pratto et al.
and Sidanius and Pratto .
The SDO scale was subsequently adapted into Indonesian by Arifianto .
The SDO-7 scale consists of two dimensions: SDO-D .
upporting the existence of hierarchy in societ.
and SDO-E .
upporting equality in societ.
, as well as two sub-dimensions for each: pro-trait .
haracterized by a high SDO valu.
and con-trait .
haracterized by a low SDO valu.
CFA on this SDO scale resulted in a model consisting of 16 items with good factor loadings () ranging from .
513 to .
The measurement of cyber aggression behavior was conducted using the Cyber Aggression Questionnaire for Adolescents (CYBA) scale, developed by Garcya et al.
and adapted by Hamida et al.
Modifications were then made to adjust the general form of the scale to suit the context of the research, which is the 2024 Indonesian general election.
The adapted CYBA instrument consists of 12 items, with modifications made.
A pilot sample of 50 respondents was used.
The method used to assess the content validity of the modified CYBA scale was expert judgment, which was evaluated using AikenAos V validity index.
This research involved three experts, with a Likert scale used for assessment, ranging from 1 to 5.
AikenAos V value obtained was .
944, indicating that the items in the modified CYBA scale adequately represent the cyber aggression construct.
The trial results of the modified CYBA measurement tool showed validity ranging from .
472 to .
689, with a significance level of 5% (> .
CronbachAos alpha reliability was .
829 (> .
, which is considered acceptable.
Data was collected by distributing a Likert scale questionnaire via Google Forms online on the The collected data will be analyzed using descriptive and inferential statistical analysis with SPSS version 26 to examine the predictive relationship between the SDO variable and cyber-aggression Assumption tests include the one-sample Kolmogorov-Smirnov normality, linearity, and Glejser heteroscedasticity tests.
Hypothesis testing used simple linear regression to examine the predictive relationship between social dominance orientation and cyber aggression.
RESULTS
The respondents of this research are X users who have ever posted a tweet, retweeted, or liked a post containing hate speech related to the 2024 Indonesian General Election.
The demographic characteris- 6 | Napitupulu & Fatmawiyati - Social Dominance Orientation.
tics of the subjects include gender and age.
The data in Tables 1 and 2 show the distribution of gender and age among the research respondents.
There are 141 male subjects .
3%) and 145 female subjects .
7%).
The age distribution of the subjects ranges from 22 to 40 years.
The age distribution is relatively even, with the lowest number of subjects being 9 at 40 and the highest number being 19 at 31, 33, and 37.
Table 1.
Gender Gender Frequency Percentage Male Female Total Table 2.
Age Age Frequency Percentage Total The categorization results show that social dominance orientation is generally high, with an average of 39.
This indicates that most respondents tend to have a high social dominance orientation.
Individuals with a high social dominance orientation tend to view society as divided into two hierarchies: high-status groups and low-status groups.
They regard high-status groups as winners, possessing power and positive attributes (Arifianto, 2.
Meanwhile, the level of cyber aggression falls into the moderate category with a percentage of 45.
5%, indicating that the cyber aggression behavior exhibited by X users during the election period is categorized as moderate.
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Table 4 below.
More specifically, as shown in Table 5, the categorization results for social dominance orientation in both males and females indicate that both groups fall into the high category, meaning that both males and females strongly support inequality (SDO-D).
Table 3.
Hypothetical Data Variable Min.
Max.
M SD
Social dominance orientation 16
112 64 11
Cyber aggression 60 36 8 Table 4.
Categorization Variable Level Interval
Frequency Percentage Very high
80 < X
High
69 < X < 80
Social dominance orientation Moderate 59 < X < 69
Low
48 < X < 59
Very low
X < 48
Very high
48 < x
High
40 < X < 48
Cyber aggression Moderate 32 < X < 40
Low
24 < X < 32
Very low
X < 24
Table 5.
Social Dominance Orientation Categorization Variable Level Interval
Frequency Percentage Very high
80 < X
High
69 < X < 80
Male
Moderate 59 < X < 69
Low
48 < X < 59
Very low
X < 48
Very high
48 < X
High
40 < X < 48
Female Moderate 32 < X < 40
Low
24 < X < 32
Very low
X < 24
The first assumption test in this research is the normality test.
The normality test was conducted using the one-sample Kolmogorov-Smirnov test.
Based on the normality test in Table 6, in the Kolmogorov-Smirnov section, the significance value for the social dominance orientation variable is .
> .
, and for cyber aggression is .
> .
Both variables show p > .
05, which means it can be concluded that the social dominance orientation variable (D.
= .
p = .
and cyber aggression (D.
= .
p = .
are normally distributed.
8 | Napitupulu & Fatmawiyati - Social Dominance Orientation.
Table 6.
Normality Test Kolmogorov-Smirnov Shapiro-Wilk Statistics Significance Statistics Significance Social dominance orientation Cyber aggression The second assumption test is the linear relationship between the independent and dependent variables.
Based on Table 7, the social dominance orientation and cyber aggression variables have an F value of F.
, .
= 34.
p < .
05 in the linearity column, or a deviation from the linearity value of F.
, .
= 1.
p > .
05, indicating that there is a linear relationship between the social dominance orientation variable and cyber aggression.
Table 7.
Linearity Test Significance Deviation from linearity 43 1.
Linearity Total The final assumption test in this research is the heteroscedasticity test, which uses the Glejser test.
Based on Table 8, the social dominance orientation score did not affect the absolute unstandardized residuals .
= .
268 or p > .
, meaning there was no heteroscedasticity issue in the research data.
Table 8.
Heteroscedasticity Test Variable Significance Social dominance orientation Based on Table 9, the analysis results show that the average score for social dominance orientation is M = 71.
SD = 10.
091, and the average score for cyber aggression is M = 38.
SD = 7.
The correlation test results indicate that social dominance orientation and cyber aggression behavior have a weak relationship, r = .
n = 286.
p < .
two-tailed.
The direction of the relationship between the two variables is positive, meaning that the higher the social dominance orientation, the higher the cyber aggression behavior.
Table 9.
Descriptive and Correlation Tests Variable Social dominance orientation 71.
Cyber aggression After the assumption tests were met, the next step was hypothesis testing.
The regression analysis results in Table 10 show that social dominance orientation significantly predicts cyber aggression behavior in X users ( = .
= 5.
p < .
95% CI of B [.
alternative hypothesis Social dominance orientation also significantly explains the proportion of variance change in cyber aggression behavior in X users.
R2 = .
= 33.
p < .
Social dominance orientation has a positive regression coefficient toward cyber aggression behavior, meaning that the high- Jurnal Sains Psikologi.
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er the social dominance orientation score, the higher the cyber aggression behavior, and vice versa.
The contribution of social dominance orientation to cyber-aggression behavior in X users during the 2024 election period is .
107 or 10.
7%, with the remaining 89.
3% influenced by other factors besides social dominance orientation.
Table 10.
Hypothesis Test Variable 95% CI (Constan.
Social dominance orientation .
Note.
= 33.
p < .
R2 = .
DISCUSSION
This research involved 286 respondents, consisting of 145 females .
7%) and 141 males .
3%).
This indicates a fairly balanced representation between female and male respondents, allowing for a more representative analysis of both genders.
In terms of age, the distribution of respondents is relatively even, with an age range of 22 to 40 years.
Each age group has a varying number of respondents, ranging from 9 to 19 individuals.
This suggests that no particular age group dominates, meaning that the results of this research can reflect the perspectives and behaviors of various stages of early adulthood to mid-adulthood.
The correlation coefficient of .
326 indicates a significant but weak positive relationship between social dominance orientation and cyber aggression.
This is consistent with the theory suggesting that individuals with high social dominance orientation are more likely to exhibit aggressive behaviors, including in online contexts.
Social dominance theory (Sidanius & Pratto, 1.
explains that individuals with high social dominance orientation tend to support ideologies and policies that reinforce or maintain social hierarchies.
In the context of elections, individuals with high social dominance orientation may be more likely to use social media to attack political opponents and strengthen their positions.
This aligns with previous research that found social dominance orientation associated with aggressive behavior and prejudice (Celuch et al.
, 2022.
Pratto et al.
, 1.
Social dominance orientation is a psychological concept that describes the extent to which individuals support social hierarchies and the dominance of certain groups over others.
Social dominance theory (Sidanius & Pratto, 1.
posits that individuals with high social dominance orientation tend to support ideologies and policies that reinforce or maintain social hierarchies.
Conversely, cyber aggression is aggressive behavior conducted through digital media such as the Internet and social media.
Forms of cyber aggression include identity impersonation, sexual visual aggression, as well as verbal aggression, and social exclusion (Garcya et al.
, 2.
Social dominance orientation can be used to anticipate an individualAos social and political attitudes.
By understanding how individuals orient themselves in terms of social dominance within a community, we can predict individualsAo tendencies in choosing and providing preferences for candidates in elections, as well as their attitudes toward various social policies (Arifianto, 2.
This research indicates that psychological factors such as social dominance orientation play an important role in cyber aggression behavior.
This is in line with the research by Barbovschi and Staksrud .
, which found that the desire for power and self-protection often drives cyber aggression behavior.
This phenomenon can also be explained through the concept of moral disengagement (Bandura, 2.
, where individuals justify their aggressive behavior as something natural or even moral for a greater cause.
10 | Napitupulu & Fatmawiyati - Social Dominance Orientation.
Several factors influence how an individual or group can become a target of cyber aggression.
Research by Obermaier and Schmuck .
found that vulnerable or minority social groups are more likely to become targets of hate speech.
Additionally, involvement in expressing political opinions in public spaces can increase the likelihood of becoming a target of hate speech (Costello et al.
, 2.
Active engagement on social media is also positively correlated with the likelihood of being targeted by hate speech (Costello et al.
, 2.
Apart from examining the target side, the factors of cyber aggression behavior can also be viewed from the perpetratorAos perspective.
Understanding what motivates perpetrators to accept and support hate speech can serve as an avenue for identifying the factors behind cyber aggression behavior.
A study conducted in six different Western countries showed that acceptance of hate speech is related to several psychological and behavioral factors, including frequency of internet use, frequency of exposure to hate speech content, membership in online communities, institutional trust, acceptance of violence, social dominance orientation, empathy, and age (Celuch et al.
, 2.
Research by Barbovschi and Staksrud .
found that of the two identified objectives for engaging in cyber aggression .
elf-protection and powe.
, perpetrators of cyber aggression tend to justify their actions as a means to gain power and self-protection.
This aligns with concept by Bandura .
of moral disengagement, in which individuals use cognitive restructuring to transform inherently negative or immoral behavior into behavior that appears more positive by engaging in moral justification.
Individuals cognitively perceive such behavior as normal, justified, or performed for a higher moral From the explanations provided, several conclusions can be drawn regarding why social dominance orientation is related to cyber aggression.
First, individuals with a high social dominance orientation tend to have a strong need to maintain and reinforce social hierarchies.
In the digital context, they may use cyber aggression as a tool to assert their power and maintain their dominant position.
For example, they may attack or belittle individuals or groups they perceive as a threat to their status (Sidanius & Pratto, 1.
Second, social dominance orientation is often associated with a competitive and hierarchical worldview.
This perspective can legitimize using aggression to achieve goals or maintain status.
In the online world, individuals with high SDO may feel that cyber aggression is a legitimate way to protect or expand their power (Pratto et al.
, 1.
Third, social media provides a broad and anonymous platform for expressing views and engaging in behaviors that might not occur in face-to-face interactions.
Individuals with high social dominance orientation may exploit this anonymity to engage in cyber aggression without fear of direct consequences.
They may use social media to intimidate, ostracize, or belittle others to reinforce their dominance (Celuch et al.
, 2.
Fourth, previous research has shown that social dominance orientation correlates with various forms of aggressive behavior and prejudice.
Therefore, it is unsurprising that individuals with high SDO also tend to engage in cyber aggression (Celuch et al.
, 2022.
Pratto et al.
, 1.
Finally, according to the theory of moral disengagement (Bandura, 2.
, individuals may justify their aggressive behavior by perceiving it as acceptable or moral to achieve a greater goal.
Individuals with high social dominance orientation may use this moral justification to legitimize their cyber aggression, viewing it as a legitimate way to protect or strengthen their social status (Bandura, 2.
Overall, social dominance orientation influences how individuals perceive the world and interact with others.
In the digital context, this orientation can motivate aggressive behavior, including cyber aggression, to maintain or expand their dominance over others.
This suggests that social dominance orientation is an important factor that needs to be considered to understand and address cyber aggression (Bandura, 2016.
Celuch et al.
, 2022.
Pratto et al.
, 1994.
Sidanius & Pratto, 1.
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CONCLUSION
A weak positive relationship between social dominance orientation and cyber aggression was found during the 2024 Indonesian presidential election on X.
As social dominance orientation is high and cyber aggression is moderate, the contribution of social dominance orientation to cyber aggression behavior among X users during the 2024 election is .
107 or 10.
7%, indicating that other factors 3% of the variance.
These findings are crucial for election cyber aggression management and reduction.
Cyber aggression should be reduced by addressing psychological and social causes.
Interventions to decrease social dominance or cyber aggression could improve the social media environment.
These findings can help the government, social media platforms, and political parties develop targeted educational and intervention strategies.
Future research should collect data during the campaign or before election day.
Statistics show that social media cyber aggression peaks during this Cyber aggression increases during the campaign due to more political interactions and contests online.
Researchers can better understand cyber aggression related to social dominance orientation and other election-related factors by collecting data during this period.
This will help develop better cyber aggression prevention and response techniques during these critical times.
REFERENCES