Abstract

Social media memes play a pivotal role in propagating discourses and, in turn, influencing the thought-construction of the public. Many users are involved in cyberbullying and hate speech, particularly by using insensitive language and negative stereotyping in social media memes against women. This study analyzed the misogynistic modes used in memes to understand their social and psychological influence on the audience. This study integrates forensic linguistics and forensic psychology to analyze the data that comprises three memes selected from social media platforms. The textual and visual elements of memes are analyzed to reveal the underlying meanings and intentions against women, which lead to the objectification of women and stir up psychologically harmful misogynistic mindsets among the viewers. This study finds that memes are being utilized as powerful tools to spread misogyny via hate speech and deriding visuals under the mask of entertainment.

Keywords

Cyberbullying, Hate-speech, Forensic Linguistics, Forensic Psychology, Misogyny, Insensitive Language, Negative Stereotyping, Deriding Visuals

Introduction

Memes, often considered humorous, play a key role in spreading harmful discourses on social media platforms such as Instagram and Facebook. In the digital world, memes are becoming a powerful mode of communication and therefore carry the audacity to affect the psychological well-being of those who are victimized and tormented. In memes, multiple modes such as text, images, videos, charts, and graphs combine to express cyber-bullying and hate speech against women. The current study combines forensic linguistics and forensic psychology to analyze the way these social media memes construct and spread hate and impact the emotional and mental state of the intimidated ones. The visual and linguistic elements used in memes are not only humorous but also harmful and offensive, which may raise serious concerns among women regarding their identity and social well-being. This normalization of distorted patterns and harmful content against women leads to severe mental health challenges such as stress, anxiety, depression, and tension.

Research Problem

Cyber-bullying and hate speech on social media are against human rights. Memes are perceived as harmless entertainment, but they play a significant role in spreading hate speech, especially against women. These memes may cause serious emotional and psychological distress to the victims. Although platforms have policies to control abusive and intimidating behaviors, harmful content often remains undetected because it appears in multiple forms. Memes can contribute to spreading negativity towards women by disguising harmful messages as jokes or humor, apparently making them harmless. The current study aims to analyze the multiple modes of text, images, videos, and drawings to discover the psychological impacts on the offended audience. This research aims to explore the contribution of memes caricaturing women in cyber-bullying and hate speech and its psychological effects on the victims. It also aims to highlight the roles forensic psychology and forensic linguistics can play to improve the detection of cyber-bullying and hate speech, and the legal response system.

Research Questions

This study aims to answer the following research questions:

1. How do social media memes contribute to cyberbullying and hate speech against women?
2. How do misogynistic social media memes cause disturbance to women's psychology?

Research Objectives

The study aims to:

• Analyze how social media memes representing women contribute to cyberbullying and hate speech
• Highlight misogynistic social media memes as a cause of disturbance to women's psychology

Literature Review

Social media has become a key platform for stirring discourses among the general public with the emergence of digital communication. However, social media also facilitated the spread of harmful materials by cyber-bullying and hate speech, especially against women. A meme is the cultural information distributed by imitation for the sake of fun or entertainment. The term "meme" has been derived from the Greek linguistic term mimema, meaning "imitated," and was introduced in 1976 by British evolutionary biologist Richard Dawkins in his work The Selfish Gene. The social media memes, often regarded as humor or satire, are used as online vehicles for harassment to normalize false or harmful discourses. This study examines multimodal aspects of cyber-bullying and hate-speech against women on social media and analyzes how visual and textual elements contribute to their influence. The recognition of engagement of text, images, and rhetorical devices in meme creation can uncover the implicit biases of digital communication, which typically reinforces stereotypes and discrimination of gender. The examination of these components is necessary to discern patterns of hate speech and cyberbullying, and essential for crafting counter-narratives that advocate for digital literacy and a secure online space. Cyber-bullying refers to the use of digital platforms to threaten or harass people and may include direct attacks, public humiliation, and the spread of harmful and false information. Cyber-bullying can be defined as an aggressive and offensive act, intentionally carried out against a victim, using electronic means of communication, repeatedly and over time (Smith et al., 2008). Hate speech is any form of communication that discriminates, provokes violence, or promotes enmity against a group based on characteristics such as gender, race, ethnicity, or religion. Hate-speech is defined by the UN Strategy and Plan of Action on Hate Speech as "any kind of communication in speech, writing or behaviour, that attacks or uses pejorative or discriminatory language with reference to a person or a group on the basis of who they are, in other words, based on their religion, ethnicity, nationality, race, colour, descent, gender or other identity factor."

Zulqarnain (2024) asserts that multiple modes of communication in the newspaper can cause a threat to the reputation of an offended entity. His study primarily addressed the twenty-five political cartoons from two Pakistani newspapers, such as Dawn and Minute Mirror, to examine how defamation occurs in newspapers. The current study does not particularly examine the forensic aspects of psychology, but aims to discover the forensic perspectives of the multiple modes of social media memes against women. It also delves into the exploration of the disturbance caused by memes to women's psychology.

Elahi (2022) claims that cyberbullying or language crimes in the form of speech acts are committed in social media memes, which violate basic human rights. This study has mainly focused on the operationalization of the speech acts of humiliation, threat, warning, and abuse, in the form of cyber-bullying, in designing and publishing memes from the perspective of forensic linguistics. However, the current study explores multiple modes of text, images, graphs, and drawings to analyze the psychological impacts on women forensically.

Febriana and Budiarto (2019) created a Twitter database that helps to detect hate speech and cyberbullying in the Indonesian language. In order to classify tweets, their study used Latent Dirichlet Allocation (LDA) for topic extraction and sentiment analysis, underscoring the difficulties in identifying hate speech, particularly during politically charged events. Their methodology of research and dataset highlights the importance of linguistic patterns in detecting offensive content, which is relevant to the multimodal analysis of hate speech in social media memes. While this study particularly focused on text-based analysis, the current research explores the multimodal aspects of social media memes to detect hate speech against women.

Ibrahim et al. (2024) suggest a fine-grained cyberbullying classification model that combines multiple-layer perceptrons (MLP) with neurosophic logic. They emphasized the use of social media forensics in the detection of cyberbullying, with a focus on ensemble approaches and machine learning-based techniques that improve classification. MLP is one of them, and it works well in capturing the intricate connections between different types of cyberbullying. The findings show that neutrosophic logic offers a more sophisticated method and greatly increases detection accuracy. Constructing on this basis, the current study intends to investigate hate speech and cyberbullying directed towards women in social media memes using the frameworks of social semiotic multimodality and cognitive distortion theory, offering an in-depth multimodal analysis of cyberbullying patterns and their psychological effects.

Multi-modal discourse analysis offers a theoretical framework for studying how various semiotic resources (images, charts, drawings) build meaning in digital texts. In the case of internet memes, MDA can be used to discover how visual elements engage with textual elements to perpetuate stereotypes and ideological biases. Through the study of linguistic and visual options in memes, the current research aims to uncover implicit bias and the use of humor to legitimize hate speech.

Cao et al. (2021) proposed the DisMultiHate framework, which aims to disentangle target entities in multimodal memes for better hateful content classification and explanation. Their methodology illustrated that one could improve the detection of hate speech, particularly context-dependent and subtle forms of hate speech, through the awareness of the interaction among various modal aspects at work. In contrast, the current study explores how the same type of multimodal memes that target women influence public mindset and affect mental health, and proceeds to interpretation and implications.

Sajid (2023) claimed that social media memes serve as a powerful tool in reinforcing dominant gender norms. The main purpose of this study was to examine gender ideology with a semiotic focus on both males and females. It primarily addressed 50 memes from two social media platforms (Twitter and Reddit) to analyze their linguistic and visual aspects. The current research study mainly focuses on the detection of cyberbullying and hate speech in social media memes mainly targeting women by using Multi-model Analysis.

The psychological effect of cyberbullying by means of memes is profound. Victims tend to suffer from emotional distress, anxiety, and depression. The anonymity and widespread reach of social media enhance these effects, making it difficult for victims to be free from the harassment. The repetitive aspect of cyberbullying can cause long-term psychological harm to victims' self-esteem and mental health. Aguilera-Carnerero and Tegal (2023) analyzed Islamophobic and misogynistic memes, describing how memes employ symbolic imagery and humor as agents to advance prejudice. Their research study addressed religious and gendered stereotypes. Expanding on this, the present study specifically examines memes that attack women on various platforms, employing semiotic material such as emojis, pictures, and profanity to create humor and spread harm under the cover of humor. The present research purports to contribute to these studies by carrying out a thorough multimodal analysis of social media memes targeting women. Through its combination of forensic psychology and linguistics, the study aims at revealing the subconscious mechanisms by which such content gets into victims' minds and identifying strategies for their detection and prevention.

Research Methodology

This section comprises research design, followed by the method of data collection, population, sampling, data collection procedure, and conceptual framework.

Research Design

The current study adapts a qualitative research approach, using multimodal analysis to analyze the qualitative data, memes targeting women, gathered through Instagram and Facebook. The research is narrative in nature and examines both the linguistic and visual elements of selected memes.

Population of the Study

The population of the study contains memes caricaturing the negative image of women, to bulldoze their identity, dignity, and social respect, published on Instagram and Facebook. These memes feature content that negatively affects women's psychology and spreads contempt against them. These social media platforms are selected because of their high meme-sharing activity and the prevailing online gendered harassment.

Sample of the Study

This study utilizes purposive sampling to collect memes largely targeting women on two social media websites, i.e., Facebook and Instagram. The research is focused on analyzing a total of 03 memes, with two memes selected from Facebook and one from Instagram. The memes are chosen based on specific multimodal features (images, text, and characters).

Data Collection Procedure

This study takes the research data from two widely used social media websites, Facebook and Instagram. It is collected by searching and downloading memes manually from public accounts, pages, and posts, and using keywords related to gender, such as "women, women memes, hate speech, cyberbullying, and women hate memes".

Data Analysis Method

The data for this research study have been analyzed by using the approach of Multimodal Analysis. Multimodal Analysis has been employed to analyze memes collected through social media platforms, i.e., Facebook and Instagram, because the selected memes combine multiple modes such as textual, visual, and semiotic resources to convey meaning. This analysis mainly focuses on cyberbullying and hate speech against women occurring by combining these visual and verbal modes in memes.

Theoretical Framework

The theoretical framework of the study is based on three key theories, i.e., Cognitive Distortion Theory (CDT) by Aaron Beck (2023), General Strain Theory (GST) by Robert Agnew (1992), and the Social Schema Theory of Crime by Ronald L. Simsons et al. (2014). These theories explain both the production of cyberbullying and hate speech in social media memes targeting women as well as their psychological impacts.

Cognitive Distortion Theory

The Cognitive Distortion Theory (CDT) by Aaron Beck (1960) serves as a part of the conceptual framework of this study to examine texts, images, and other visuals in social media memes that contribute to cyberbullying and hate speech against women.

Cognitive Distortion Theory explains the negative impacts of distorted thinking, such as biased mindsets and irrational thought patterns, on our understanding and reasoning. Furthermore, it also examines the contribution of these distorted perceptions towards mental health problems and psychological strains. These distorted thoughts are categorized by overgeneralizations, exaggerations, misinterpretations, and other errors in logical reasoning. In online communication, such distorted cognitive processes not only encourage individuals to create harmful content but also negatively affect the psyche of individuals who internalize this content.

Cognitive distortion refers to the consistently inappropriate, negative, biased, and inaccurate thinking patterns. These thought patterns are different from reality and lead to several mental health challenges, such as depression, anxiety, and negative self-perception. Cognitive distortion patterns develop negative emotions and create a cycle of negative thoughts and beliefs about a person's own self, others, and even the world. Beck (1960) recognized different types of distortions, including overgeneralization, personalization, labeling, dichotomous thinking (all-or-none thinking), catastrophizing, filtering, and emotional reasoning.

In relation to social media memes contributing to cyberbullying and hate speech against women, overgeneralization might occur when a meme suggests that all women behave in a similar way based on different forms of incidents. Similarly, labeling may also appear in these social media memes. Labeling occurs when memes assign harsh and unflattering labels to women, reinforcing harmful stereotypes. Additionally, cognitive distortion theory explains the psychological processes involved in the production and consumption of memes targeting women. Content creators can share their own distorted beliefs in meme stories, consciously or unconsciously representing sexism, prejudice, or hostility.

At the same time, people who share such memes can undergo cognitive distortions like confirmation bias, accepting harmful stereotypes because they conform to existing prejudices. This cyclical process is the cause of hate speech and cyberbullying against women on social media platforms. This theoretical approach also conforms to the psychological effects of memes on the targeted individuals. Victims of hate speech and cyberbullying can internalize the manipulated versions they receive and experience self-blame, diminished self-esteem, or helplessness. Thus, cognitive distortion theory not only offers a model for examining the harmful effects of memes but also identifies the psychological implications for both victims and perpetrators in the online landscape.

General Strain Theory (GST)

General Strain Theory by Robert Agnew (1992) elaborates on traditional strain theories by paying attention to the way diverse sources of psychological strain lead individuals to deviant or aggressive behavior. Agnew (1992) identifies three main types of strain: failure to attain goals, removal of positive stimuli, and exposure to negative stimuli. These strains elicit negative emotions like frustration, anger, or depression, which can lead to maladaptive coping responses such as aggression, deviance, or emotional withdrawal.

GST is relevant to the current study in two ways. Firstly, it explains how perpetrators of hate speech memes could be releasing their own frustration or emotional distress through online aggression. Secondly, it accounts for the psychological impacts on targeted women, who feel strain from repeated exposure to hateful online content. Such strain can result in declining mental health or social withdrawal, which reflects the coping strategies explained in GST.

Social Schema Theory of Crime

The Social Schema Theory of Crime by Simsons et al (2014) incorporates social learning and cognitive psychology to illustrate the influence of repeated exposure to negative experiences on cognitive frameworks or schemas. Simons et al. (2014) set out three core schemas that encourage antisocial behavior: hostile interpersonal perspective, preference for immediate rewards, and detachment from conventional norms. These schemas are often developed from exposure to angry, neglectful, or abusive environments, such as online spaces.

In this context, social media memes act as agents of schema reinforcement, particularly when they normalize misogyny, dehumanization, or victim-blaming. It also explains that repeated exposure to such memes can lead to internalization of aggressive worldviews, resulting in desensitization to hate speech or even active engagement in online harassment. Therefore, this theory supports the argument that online content on social media has the ability to shape cognitive orientations that promote gender-based cyber violence.

By applying all these theories, this study analyzes how social media memes not only indicate but also strengthen cyberbullying and hate speech against women, and contribute to a culture of digital misogyny.

Data Analysis

This session includes a multi-modal, forensic, and psychological analysis of three social media memes that contribute to cyberbullying and hate speech against women. The analysis mainly focuses on the use of text, imagery, language, and implied meaning in the detection of emotional harm, sexism, control, hate speech, and psychological consequences through these selected memes.



This meme depicts a situation where two people (one is a woman and the other is a man) are in a car being driven on the road. The title being mentioned promotes the concept associated with women that women are very talkative, and also portrays it as a cause of accidents on roads. "New seat belt design" implies that this new design will keep women silent.

In multimodal analysis, this meme shows the visual (woman silenced) and textual mood for irony. The man is smiling in the image, which symbolizes the dominance of men over women. The humor is created by showing safety measures as an instrument for male dominance. The title of the meme is written in simple language with catchy vocabulary in order to attract viewers. The main message of the designer has been delivered by the black-colored text in a bold style. There is no specific capitalization pattern used in the meme. The language of the meme conceals the multitasking inability of the driver (man), who is not capable of maintaining his concentration on the driving while listening to the conversation of the woman sitting beside him. The implication of "45% fewer car accidents" with the talkative nature of women highlights exaggeration and simplification of complex issues. This kind of harmful message, conveyed through memes as humor, promotes negativity and hate against women. The positioning of man in the driving seat shows his dominance and control. The characters in the car are suggestive of a potential relationship between the two: husband and wife. In addition, there is shock and wonder in the woman's eyes, implying that she has a subordinate role. The positioning of the meme's title at the center and top of the image leaves a lasting impression on viewers' minds.

From the perspective of forensic linguistics, the title of the meme reflects linguistic violence. It is an example of coded hate speech in which the underlying meaning is discriminatory without the use of offensive or violent language. These kinds of memes highlight issues of emotional abuse and control suffered by women in families, online communities, and public places.

From a forensic psychological perspective, this meme has negative psychological impacts on women. It shows the barrenness of women in the expression of freedom and promotes gendered oppression. The male viewers might perceive it as control dynamics in which women's voices need to be controlled, while it evokes fear and humiliation in the minds of women. Overall, the meme appears funny, but it conveys a harmful message that negatively impacts the psychological health of women.



The meme employs a multimodal mix of a sad male face after a fight and a caption that suggests domestic violence. The text and image of the meme portrayed a threatening implication that the emotional loss the man had in the ring will be vested upon his wife. The weeping eyes and beaten face serve as affective cues drawing attention to common cultural knowledge of masculinity and gender roles.

From a forensic linguistic point of view, the meme contains an aggressive illocutionary act in which the speaker makes an explicit statement. The effect of the statement is paramount on the audience. It promotes domestic violence through the use of humor, which downplays the severity of the act. The humor is implicature-based in the meme. The audience assumes this statement, "wife will pay," as a metaphor for physical harm. This metaphor makes the violent act appear as a normal and even justified response to anger in a humorous way.

From a Forensic Psychological point of view, this meme supports negative gender relations and encourages toxic masculinity. It also discourages empathy and justifies violent behavior as a means of expression for masculinity. Forensic psychology suggests that continuous exposure to such material can make abusive reactions look normal. In addition, the meme could be a representation of the cultural acceptability of gendered violence, particularly in patriarchal societies where dominance by males and emotional repression are acceptable. This is in line with critical discourse analysis (CDA), where power relations are strengthened subtly through common language and the media. The caption itself is not showing very aggressive language, but the meaning is clear. It shows violence as a result of failure faced by a male partner, which is then inflicted upon a powerless partner, supporting the gender hierarchy and justifying physical abuse.

Overall, this meme is a two-tiered example of hate speech and cyberbullying wrapped in humor. The multi-modal design of meme, emotional picture, and text provides a normalization of violence in a humorous way that should trouble linguistic and psychological experts alike.



This meme presents an image of women with the label "Two dustbins in one frame." The caption of the meme equates women with garbage. According to multimodality, the image and caption collaborate with each other to create a visual metaphor. The facial expressions of women do not matter in the message the meme is conveying. The caption is relating women to a container carrying waste, a disdainful and contemptuous object. The visuals used in the meme are comparing the presence of women with an unworthy thing. Also, the meme illustrates hate speech as metaphorical derogation. The "dustbin" metaphor used in the meme not only suggests that women are worthless but also that the containers of dirt are. This kind of language conveys misogynistic ideologies with the help of semantic derogation, implicitly linking the identity of women with moral contamination or pollution. The caption used in the meme narrates that the readers consider the women in the image well-deserving of this label. It also commits misogyny to a socially shareable joke in a humorous way.

The illocutionary effect used in this meme is mocking and contemptuous. It promotes the concept of gender bias and body shaming. The perlocutionary effect can involve humiliation, emotional damage, and psychological trauma, particularly when aimed at actual individuals or when the meme becomes viral. The meme uses dehumanization strategies, which are typical in hate speech and can cause desensitization or justification of violence against the group targeted.

From a forensic psychological perspective, the meme helps to normalize cyberbullying and online harassment against women. The use of dustbins as a point of comparison is a typical illustration of social exclusion and marginalization with profound effects on self-esteem, body image, and mental health of women. The constant exposure to this type of content can contribute to internalized misogyny among women. It also reinforces patriarchal control among men. Psychological research has indicated that repeated representations of women as disposable in social media memes are linked to higher levels of acceptance of gender violence. Furthermore, humor is added as a double layer of moral detachment, enabling people to watch and forward the content without feeling guilty, bad, or any type of hesitation. The violent tone of the meme hides under the lightness of the joke, enabling hate speech to move freely under the cover of humor and entertainment. This meme, therefore, is a prominent example of how language, image, and humor can work together to promote misogyny and encourage oppressive ideologies within digital discourse.

Conclusion

This session includes findings and recommendations of the study, along with a brief final conclusion.

Findings

The analysis of the selected social media memes

uncovered the following key findings:

1. The memes repeatedly used offensive and violent language against women, often wrapped in humor. The use of modal verbs, imperatives, and dehumanizing metaphors was common among these social media memes targeting women.
2. The multimodal elements in these selected memes, such as offensive language, exaggerated facial expressions, objectification of women, and use of sarcastic tone, strengthened the gender bias in the messages being conveyed.
3. This study has found that visual cues in the selected data were used in the memes to devalue women. Meme designers are causing serious damage to the women under the mask of entertainment, which may lower the reputation and cause danger to the self-esteem of the offended entity being mentioned.
4. The content used in these memes revealed common characteristics of cyberbullies, such as a lack of empathy, sexism, misogyny, domestic violence, body shaming, and sexual harassment, which have been found in the data. The continuous exposure to such kinds of memes can negatively affect the self-esteem and mental health of women.
5. This study revealed that overgeneralization, exaggeration, and misrepresentation of the women may cause mental strain to the offended entity and can cause severe forensic outcomes in the legal domain.
6. The current study has also found that the meme designers use the linguistic tools, removal of positive stimuli, and exposure to negative stimuli, to highlight the negative side of the women and hide their positive aspects by utilizing multiple modes in their social media posts.
7. The forensic psychological aspects of the study have found that the continuous violence and aggression against women becomes a social schema in a particular society. The meme designers are committing a social crime by developing a negative portrayal of women and normalizing a disdainful image of women, which may cause social insecurities, gender inequality, suppression, misogyny, dehumanization, and violence.

Discussions

The key findings of current research integrate with previous studies in forensic linguistics and psychology that highlight the use of offensive linguistic and visual cues in memes as a powerful tool to propagate misogyny. The meme creators promote discrimination by disguising cyberbullying and hate speech under the fancy mask of entertainment. The memes analyzed as data showed a pattern of subtle sexism, which appears humorous at the surface level but contains threatening implicit messages that support patriarchal norms. The memes also had indications of deindividuation, where users conceal themselves behind anonymity to verbalize aggression without any ownership and regardless of their ethical, moral, social, and psychological consequences. These cyberbullying practices against women have broader social impacts, which include promoting a digital culture where misogyny is tolerable and even celebrated. The impacts of these behaviors on women include anxiety, depression, isolation, and self-doubt, particularly when the content of the meme satirizes real-life problems experienced by women.

Recommendations

This study mainly focused on analyzing memes from two social media platforms, Facebook and Instagram. Further research can be conducted by taking a similar type of memes published on other social media platforms.

The scope of the study was confined to the analysis of cyberbullying and hate speech in social media memes targeting women. The memes included in the data highlighted common traits of cyberbullying, such as sexism, domestic violence, and body shaming. This observation encourages future researchers to explore more multimodal analysis frameworks, such as auditory and interactive elements in GIFs, videos, and comments. Further research can be done to identify universal expressions of online misogyny by comparing gendered hate speech in memes with cultural and regional contexts.

Future researchers can investigate male user responses to such social media memes that mainly target women. The behavioral research can be conducted on the said research problem of online groups on social media.

Conclusion

The research concludes that social media memes are not just humorous but also act as powerful tools to promote cyberbullying and hate speech, especially against women. The use of exaggerated language and visuals in memes creates a negative impact on women's mental health. A forensic linguistic and forensic psychological multimodal analysis is very important to uncover the underlying meanings in these social media memes and understand their real-world consequences. Moreover, the textual and visual modes used in the memes promote traditional gender norms. This study highlighted the need for awareness, education, policy-making, and psychological support to counter the propagation of misogyny via memes and to promote a more respectful cyberspace.

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