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Abstract

The rise of parody Facebook pages in Bangladesh, such as Anwar TV, Jamela Television, Osomoy TV, Bahattor TV, The Delhi Star, and Channel Nai, represents a striking development in the digital media landscape. These pages mimic mainstream television channels through humour, irony, and multimodal parody, producing counter-discourses that contest established narratives of authority, credibility, and truth. This proposal outlines a research project aimed at analysing the multimodal discursive practices of such parody pages between January and October 2025. Using Kress and van Leeuwen’s (2006) visual grammar and Barthes’ (1977) semiotics, the study will explore how parody integrates textual and visual resources to challenge mainstream media authority in Bangladesh. The project will contribute to discourse studies by situating multimodal satire within a Global South, postcolonial context, offering new insights into the politics of humour, media critique, and digital counter-publics.

Keywords: parody, multimodal discourse analysis, social media, satire, Bangladesh, critical discourse

Introduction

In the contemporary Bangladeshi media landscape, social media parody pages have emerged as popular sites for humour, critique, and resistance. Pages such as Anwar TV, Jamela Television, Osomoy TV, Bahattor TV, The Delhi Star, and Channel Nai mimic the aesthetics of mainstream news outlets while offering exaggerated, ironic, and satirical takes on current events. These parody platforms are not mere entertainment; they represent alternative modes of discourse that contest the credibility, authority, and ideological positioning of mainstream Bangladeshi news media.

The rise of parody in South Asian social media reflects broader global patterns where satire functions as political commentary and popular critique (Baym, 2005; Chovanec, 2021). However, unlike Western cases such as The Onion or The Daily Show, scholarship on parody and humour in Bangladeshi or Global South contexts is sparse. As multimodal texts, parody posts combine language, images, logos, fonts, and editing styles to produce a “mock-authoritative” aesthetic that simultaneously ridicules and critiques media discourse. This study situates itself at the intersection of multimodal discourse analysis, humour studies, and critical media studies, aiming to explore how Bangladeshi parody pages reimagine news through irony and satire.

Literature Review

Research on multimodal discourse analysis (MDA) emphasises how meaning is constructed through the interaction of semiotic resources such as language, visuals, and layout (Kress & van Leeuwen, 2006). MDA has been widely applied to advertising, news discourse, and digital communication but remains underutilised in Bangladeshi contexts.

Parody and satire in digital media have been studied as tools of resistance and critique, particularly in relation to politics and propaganda (Chovanec, 2021; Tsakona & Popa, 2011). In the Global South, humour often functions as a safer mode of dissent in environments where direct criticism of authority may be risky (Chakrabarti, 2022). South Asian media parody—especially in Pakistan and India—illustrates how digital satire constructs alternative narratives of governance and public life (Ninan, 2012). Yet, Bangladesh remains largely absent from this growing body of scholarship.

Critical discourse perspectives on media highlight how mainstream journalism may reinforce hegemonic ideologies and power relations (Fairclough, 1995; van Dijk, 1998). Parody pages, by imitating and exaggerating news forms, expose these hidden biases while entertaining audiences. The semiotic manipulation of fonts, colours, and “breaking news” formats creates a simultaneous sense of credibility and absurdity. Scholars such as Barthes (1977) have shown how images anchor and relay meaning, a framework useful for unpacking parody visuals.

Thus, this study fills a gap by combining multimodal analysis with humour and parody research in a Bangladeshi context. It will contribute to discourse studies by situating non-Western, vernacular parody practices within global academic debates on media and ideology.

Research Questions

1. How do Bangladeshi parody Facebook pages use multimodal resources (visuals, typography, logos, and editing) to imitate mainstream news aesthetics?

2. In what ways do these parodic strategies create irony, humour, and critique?

3. What ideological or cultural commentaries are embedded in these multimodal parody practices?
   
   

Objectives

1. To analyze the multimodal strategies employed by Bangladeshi parody news pages.

2. To identify how parody constructs credibility while simultaneously undermining it

3. To explore how humour and satire function as resistance discourses in the Bangladeshi digital sphere.

4. To contribute to the under-researched field of Global South parody media in discourse studies.

Methodology

Corpus: Approximately 150 parody posts (images, memes, and short video captions) will be manually collected from selected Facebook parody news pages (Anwar TV, Jamela Television, Osomoy TV, Bahattor TV, The Delhi Star, Channel Nai). The data will cover a ten-month period (January–October 2025).

Sampling: Purposeful sampling will be used to capture posts that parody major political, social, or cultural events. Screenshots will ensure preservation of both text and visual elements.

Analytical Framework:

1. Kress and van Leeuwen’s (2006) Visual Grammar will guide the analysis of visuals (composition, salience, colour, typography, logos).

2. Barthes’ (1977) semiotics will support the study of how text and image interact to produce irony and humour.

3. Thematic analysis will code recurring patterns such as exaggeration, mimicry of logos, satirical headlines, and parody of “breaking news” aesthetics.
   
   

Analysis Procedure:

1. Identify visual-textual elements that parody mainstream media (e.g., fake logos, colour schemes).
   
   

2. Examine interaction between caption/headline and image.
   
   

3. Interpret ideological critiques embedded in humour (e.g., commentary on corruption, media bias).
   
   

Ethical Considerations

The data will be drawn from publicly available Facebook pages. No private information will be collected. Screenshots will anonymize user comments where necessary. The researcher will remain reflexive about their positionality as both an academic and a digital media consumer.

Expected Contributions

This research will:

1. Advance discourse and multimodal studies by applying them to underexplored South Asian contexts.

2. Offer insights into how humour and parody act as subtle forms of critique in politically sensitive media environments.

3. Contribute to the growing literature on digital satire, propaganda, and public discourse, with a unique focus on Bangladesh.
   
   

References

Barthes, R. (1977). Image, music, text (S. Heath, Trans.). Hill and Wang.

Baym, G. (2005). The Daily Show: Discursive integration and the reinvention of political journalism. Political Communication, 22(3), 259–276. https://doi.org/10.1080/10584600591006492

Chakrabarti, S. (2022). Political satire and resistance in South Asia. Journal of South Asian Popular Culture, 20(2), 145–162. https://doi.org/10.1080/14746689.2022.2034756

Chovanec, J. (2021). Parody as critical discourse: Satirical news in the age of post-truth. Discourse & Society, 32(3), 313–329. https://doi.org/10.1177/0957926520975867

Fairclough, N. (1995). Media discourse. Arnold.

Kress, G., & van Leeuwen, T. (2006). Reading images: The grammar of visual design (2nd ed.). Routledge.

Ninan, S. (2012). The media as a political actor in India and Pakistan. Asian Journal of Communication, 22(2), 115–128. https://doi.org/10.1080/01292986.2011.642399

Tsakona, V., & Popa, D. E. (2011). Humour in politics and the politics of humour. John Benjamins.

van Dijk, T. A. (1998). Ideology: A multidisciplinary approach. Sage.

*Han, J., & Zappavigna, M. (2023). Multimodal rhythm in TikTok videos: Exploring a recontextualization of the Gillard ‘misogyny speech’. Multimodality & Society, 4(1), 58-79. https://doi.org/10.1177/26349795231207228 (Original work published 2024)

*Logi, L., & Zappavigna, M. (2021). A social semiotic perspective on emoji: How emoji and language interact to make meaning in digital messages. New Media & Society, 25(12), 3222-3246. https://doi.org/10.1177/14614448211032965 (Original work published 2023)

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Abstract

The past decade has seen a proliferation of social media platforms as spaces for satire and political commentary across South Asia. In Bangladesh, where mainstream media often face political pressures, digital humor has become a vital outlet. As one analyst observes, memes and political cartoons have become “the unofficial voice of Bangladesh’s digital generation,” evolving from simple jokes into powerful vehicles for political satire and social change. For example, during the July 2025 mass protests, “meme artists and political illustrators became unlikely frontline responders,” using Facebook pages and graphic art to mobilize citizens in the absence of uncensored media. This trend parallels observations from other regions: researchers note that in many non-Western contexts, satire often fills the gap left by constrained traditional media, “express[ing] social reality in contexts where other forms of journalism might be suppressed”. Indeed, satire on social media has emerged globally (e.g., Last Week Tonight, Daily Show), often attracting younger audiences and playing a “vital role” in public discourse where open debate is limited. In India, for instance, satirical YouTubers and comedians are explicitly described as “speaking truth to power” when mainstream media becomes “lapdog media” for the government.

In Bangladesh, the phenomenon of digital satire has recently expanded from memes to entire parody news pages on Facebook. These pages (for example, Anwar TV, Jamela Television, The Delhi Star, Osomoy TV, Bahattor TV, Channel Nai, among others) deliberately mimic mainstream Bangladeshi news outlets’ style and branding. Although termed “parody,” they often present themselves as pseudo-news channels to satirize politics and society. Facebook has already documented networks of imitation news sites in Bangladesh – including fake pages styled after BBC Bangla and local media – used for misinformation. Parody pages operate similarly on the surface: “designed to look like authentic news pages,” complete with logos and layouts. Unlike disinformation outlets, however, these parody sites use irony and humor to critique rather than deceive.

This proposal outlines a study of how such Bangladeshi parody news Facebook pages construct meaning through multimodal discourse – combining images, typography, layouts, and text – to convey satire, credibility, and critique. It situates the research in a gap of current scholarship: despite calls for more global and non-Western focus, little academic work has examined digital political satire in South Asia using systematic discourse analysis. Using frameworks by Kress & van Leeuwen (visual grammar) and Barthes (image semiotics), this study will analyze posts from January through October 2025 to answer how visual and textual elements on these pages create ironic commentary on Bangladeshi politics and media. The findings will contribute to discourse studies by elucidating an under-researched phenomenon of multimodal political parody in a Bangladeshi (postcolonial, Global South) context.

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1. Abstract

2. Introduction

2.1 Background

Artificial Intelligence (AI) is rapidly permeating educational assessment, introducing tools from automated essay scorers to generative language models like ChatGPT and Google’s Gemini. In ELT contexts, AI-powered systems (for example, ETS’s e‑rater, Grammarly, and AI chatbots) can automate feedback on writing and generate test items, promising efficiency and scalability. Studies note that such tools offer personalized instruction and save teacher time through automated grading and feedback. However, the success of these technologies depends on teacher adoption. As one review emphasizes, “teachers’ attitudes matter significantly – their trust in and understanding of AI can determine whether these tools are meaningfully incorporated into curricula, assessments, and professional development”. This study thus focuses on ELT faculty, examining their perceptions, readiness, and resistance regarding AI-assisted assessment. By capturing instructors’ views, we aim to understand how AI might be integrated responsibly into language testing.

2.2. Problem Statement

Although AI holds promise for more objective, efficient ELT assessment, its impact hinges on teacher acceptance. Past research has often centered on AI’s technical capabilities, leaving a gap in understanding educators’ perspectives. For example, a systematic review found that most studies “revolve more around the technical abilities of AI systems” than on “human factors” like instructor trust or needs. Without addressing teacher concerns, AI integration risks superficial use or outright rejection. Teachers may resist AI for many reasons, from ethical worries (e.g., bias or cheating) to practical issues like lack of training or resources. If faculty feel AI tools undermine their professional judgment or fear losing control over assessment, they are unlikely to use them. Thus, this study investigates the underexplored problem of ELT teachers’ readiness and resistance to AI in assessment, recognizing that institutional support and training may be critical to successful adoption.

2.3. Research Questions

1. What are ELT teachers’ perceptions of the use of Gen-AI like ChatGPT, quiz-generation platforms, in language assessment?

2. To what extent are ELT teachers ready to adopt AI in their assessment practices?

3. What factors contribute to ELT teachers’ resistance or hesitancy to using AI in assessments?

4. How does institutional support (training, policy, resources) influence faculty readiness and resistance?

5. What ethical or pedagogical concerns do teachers associate with AI-based assessment (e.g., fairness, integrity, bias)?
   
   

2.3. Research Objectives

• To explore ELT faculty’s perceptions and understanding of AI’s role in assessment.

• To identify indicators of teachers’ readiness for AI integration (e.g., familiarity, confidence).

• To examine the nature and sources of resistance to AI-based assessment among instructors.

• To assess how institutional support (training, infrastructure) shapes attitudes toward AI use.

• To recommend frameworks or policies that foster responsible AI integration in ELT assessment.
  
  

3. Literature Review

5.1 AI in ELT Assessment

AI-enabled assessment tools are already present in language teaching. For instance, automated writing evaluation (AWE) systems like ETS’s e-rater use natural language processing to score essays, while platforms like Quillionz and other AI content generators can rapidly create reading quizzes or grammar exercises. Such systems promise to streamline test creation and provide immediate feedback, supporting formative assessment. In practice, teachers recognize these benefits: Nguyen et al. (2024) found that Vietnamese EFL instructors noted that an AI quiz-maker saved time in quiz preparation. Similarly, Korean secondary teachers reported using ChatGPT to create materials and tailor instruction, appreciating its time savings and adaptability.

However, research also notes challenges. AI-generated questions or scores may lack cultural/contextual appropriateness or deep alignment with course goals. Some educators worry about reliability: for example, concerns emerged over ChatGPT output accuracy and the risk of students over-relying on AI for answers. Other issues include academic integrity, since AI can produce plausible essays that may evade plagiarism detection. In sum, AI tools in ELT assessment are promising but imperfect; scholars emphasize that “the indispensable role of human judgment” remains key to ensuring quality, relevance, and ethical standards.

5.2 Teacher Attitudes and Technology Adoption

Teachers’ acceptance of new assessment technologies is shaped by both personal and contextual factors. The Technology Acceptance Model (TAM) suggests that perceived usefulness and ease of use drive technology adoption (Davis, 1989). In educational settings, faculty members’ self-efficacy (confidence in using tech) and perceptions of AI’s pedagogical value influence willingness to adopt. For example, a recent meta-analysis found that teachers’ self-efficacy and perceived usefulness were key predictors of AI adoption, while complexity and ethical concerns could deter them. Similarly, a study of Vietnamese veteran EFL teachers noted that although most saw the benefits of AI tools, actual adoption depended on factors like their digital skills and institutional support. In particular, researchers observed that “adoption varies due to factors like digital proficiency, institutional support, and educators’ willingness to embrace change”.

Institutional context also matters. Teachers with access to training, supportive policies, and peer networks tend to feel more prepared to experiment with AI. Thus, readiness is not only personal but also structural. In sum, theory and evidence indicate that ELT teachers’ attitudes toward AI will hinge on how useful they find the tools, how easy they are to use (which relates to confidence and training), and whether their school or department provides adequate support.

5.3 Resistance to Educational Innovation

Despite potential benefits, many educators resist new technologies. This resistance can stem from multiple sources. Practical and resource barriers—such as limited time, funding, or training—amplify resistance to AI use. For example, teachers often cite a lack of time to learn new systems and insufficient professional development as obstacles. Ethical and quality concerns also play a role. Many instructors fear that AI may introduce bias, compromise fairness, or enable student cheating. For instance, teachers worry that AI-generated content may misrepresent student ability or be used to “work around” assignments, thus undermining academic integrity. Other studies highlight concerns over loss of authenticity in student work and overreliance on technology, potentially eroding critical thinking.

Personal attitudes are also relevant. Some educators may feel threatened by AI, fearing deskilling or loss of control. Ertmer (1999) categorizes these as second-order barriers, beliefs, and attitudes that hinder tech use. Technological complexity itself can be off-putting; teachers who find AI tools confusing are less likely to adopt them. According to a recent survey, Bangladeshi English teachers with greater familiarity and confidence in using ChatGPT were more positive, whereas those less open to students using it tended to be more hesitant themselves.

In summary, common sources of resistance include:

• Technical and Resource Barriers: Insufficient training, time, or infrastructure can discourage teachers.

• Ethical/Integrity Concerns: Fears about plagiarism, bias, and loss of academic standards make some educators wary.

• Psychological Factors: Low self-efficacy or distrust in AI’s alignment with pedagogy can impede use.

• Change Aversion: Teachers may worry that AI tools will undermine their expertise or replace core teaching roles (Selwyn, 2019).
  
  

5.4 Gaps in Research

Although AI in education is widely discussed, few empirical studies focus on ELT teachers’ own experiences with AI-based assessment. Most existing research is either student-centered or evaluates AI tool performance. The systematic review by Jakes (2025) notes a critical gap: studies have “little empirical evidence… on how EFL teachers view the reliability, fairness, and pedagogical benefits of AI-generated materials,” instead emphasizing technical aspects. Recent small-scale studies offer some insights: for example, veteran EFL instructors in Vietnam reported both enthusiasm for AI’s potential and difficulties with digital skills and ethical issues. In Bangladesh, early findings show that most English teachers would recommend ChatGPT for language learning, yet many remain hesitant without further training. Still, these are initial explorations, and none specifically target high-stakes ELT assessment. Thus, there is a pressing need to understand faculty readiness and resistance to AI-driven evaluation methods. This study addresses that gap by centering on teachers’ perspectives in ELT assessment contexts.

6. Theoretical Framework

This research is guided by two complementary models of technology adoption. The Technology Acceptance Model (TAM) (Davis, 1989) posits that users’ perceived usefulness and ease of use determine their intention to adopt a technology. In line with TAM, we will examine teachers’ perceived benefits of AI assessment tools and their confidence in using them. Factors such as self-efficacy and technological complexity (often linked to ease of use) are highlighted in recent literature as key to AI adoption. The Concerns-Based Adoption Model (CBAM) (Hall & Hord, 2011) will help interpret teachers’ attitudes at different stages: from initial awareness and personal concerns, through management issues (e.g., training), to ultimate focus on students’ outcomes. By applying TAM and CBAM together, we can analyze not only whether teachers intend to use AI (and why) but also how and why they experience resistance as they learn about and potentially implement AI-based assessment.

4. Methodology

7.1 Research Design

A mixed-methods exploratory design will be used. First, a quantitative survey (with Likert-scale items) will gauge broad patterns of attitude, readiness, and concern across a wide sample of ELT teachers. This will be followed by qualitative interviews to delve into the nuances of those perceptions.

7.2 Data Collection

• Survey: A structured questionnaire will be distributed online to English language faculty across universities and colleges in Bangladesh and other Asian contexts. We aim for at least 100 respondents. The survey will measure constructs from TAM/CBAM (e.g. perceived usefulness, anxiety), readiness indicators, and specific concerns about AI in assessment.
  
  

• Interviews: Based on survey responses, we will conduct 15–25 semi-structured interviews with volunteer teachers. Participants will be purposively selected to represent diverse backgrounds (e.g., varying experience levels, comfort with technology). Interview questions will explore experiences with AI tools (such as ChatGPT, automated grading software), perceived challenges, and expectations about AI in testing.
  
  

7.3 Analytical Framework

• Quantitative Analysis: Survey data will be analyzed using statistical software (SPSS). We will compute descriptive statistics to summarize attitudes and conduct reliability analysis (Cronbach’s alpha) on scales. Regression or correlation analyses will identify predictors of readiness and resistance (e.g., does tech self-efficacy predict willingness to use AI?).
  
  

• Qualitative Analysis: Interview transcripts will be coded thematically following Braun and Clarke’s (2006) approach. This involves familiarizing with the data, generating initial codes, and grouping codes into themes relevant to TAM/CBAM dimensions (e.g. “perceived usefulness,” “personal concerns,” “system management issues”). NVivo software may assist in managing the coding process. Themes will be iteratively reviewed and refined. We will triangulate these findings with the survey results to build a comprehensive picture of teacher attitudes.
  
  

4.4. Ethical Considerations

• Informed Consent: All participants will receive information sheets explaining the study’s aims, procedures, and their rights. Written consent will be obtained before data collection.
  
  

• Anonymity and Confidentiality: No identifying information will be collected in surveys. Interviewees will be given pseudonyms, and any personal data will be kept confidential.
  
  

• Voluntary Participation: Participation is entirely voluntary. Teachers may decline or withdraw at any stage without penalty.
  
  

• IRB Approval: The research protocol will be submitted to the institutional review board for ethical clearance prior to data collection.
  
  

• Data Security: Survey and interview data will be stored securely (password-protected files) and used solely for academic analysis.
  
  

5. Implications and Contribution to Knowledge

This study will have several important outcomes:

• Illuminate Barriers: By detailing the practical, psychological, and ethical barriers ELT teachers face, it will shed light on why AI tools may be underused in assessment.
  
  

• Inform Training and Policy: The findings will suggest what kind of training, support, and policies (for example, AI literacy programs, clear guidelines on AI use) are needed for faculty to adopt AI effectively.
  
  

• Advanced Theory: Empirical data on teacher readiness will contribute to theories of technology adoption (TAM/CBAM) by applying them in the specific context of language assessment.
  
  

• Global South Relevance: Focusing on Asian (Bangladeshi) ELT contexts, this research will add to knowledge about AI adoption in under-studied regions, offering insights that may differ from Western-centric studies.
  
  

• Practical Recommendations: Ultimately, the study will recommend frameworks and best practices for integrating AI into language assessment in ways that respect teachers’ expertise and ethical standards. These insights aim to help educational leaders implement AI in assessment smoothly, ensuring technology serves pedagogy rather than hindering it.
  
  

6. References 

Ertmer, P. A. (1999). Addressing first- and second-order barriers to change: Strategies for technology integration. Educational Technology Research and Development, 47(4), 47–61. https://doi.org/10.1007/BF02299597

Fullan, M. (2001). The new meaning of educational change (3rd ed.). Teachers College Press.

Hall, G. E., & Hord, S. M. (2011). Implementing change: Patterns, principles, and potholes (3rd ed.). Pearson Education.

Sampson, D. G., Ifenthaler, D., & Spector, J. M. (2021). Digital assessment: AI and analytics in education. Springer.

Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Additional sources cited above are drawn from recent literature on AI and education (see text for citations).

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Here is the Abstract and Keywords of the research:

Abstract 

This study investigates the role of Facebook memes as pragmatic tools of resistance in contemporary Bangladesh. Amid state censorship and violent crackdowns on student-led protests, social media has emerged as a key platform for dissent. In particular, humorous and satirical memes offer a subversive discursive space, enabling users to critique authority, mobilize support, and express solidarity. Drawing on a multimodal framework that combines Attardo’s General Theory of Verbal Humor (GTVH) and Forceville’s theory of multimodal metaphor, this research aims to analyze how language, image, and cultural references interact within memes to construct political critique. The study will curate and examine a corpus of 100–150 widely circulated Facebook memes, including those from the July 2024 uprising, using qualitative discourse analysis. It seeks to identify the verbal and visual mechanisms of humor, satire, and symbolism embedded in the memes and how they operate as strategic acts of digital resistance. This research contributes to the scholarly understanding of political humor, digital activism, and multimodal communication in semi-authoritarian contexts. It also serves as a linguistic documentation of contemporary Bangladeshi meme practices of political resistance.

Keywords: Political Memes, Digital Resistance, Pragmatics, Multimodal Discourse, Humor and Satire, Bangladesh, Contemporary Facebook Memes

 Here is the Abstract and Keywords of the research:

Abstract 

This study investigates the role of Facebook memes as pragmatic tools of resistance in contemporary Bangladesh. Amid state censorship and violent crackdowns on student-led protests, social media has emerged as a key platform for dissent. In particular, humorous and satirical memes offer a subversive discursive space, enabling users to critique authority, mobilize support, and express solidarity. Drawing on a multimodal framework that combines Attardo’s General Theory of Verbal Humor (GTVH) and Forceville’s theory of multimodal metaphor, this research aims to analyze how language, image, and cultural references interact within memes to construct political critique. The study will curate and examine a corpus of 100–150 widely circulated Facebook memes, including those from the July 2024 uprising, using qualitative discourse analysis. It seeks to identify the verbal and visual mechanisms of humor, satire, and symbolism embedded in the memes and how they operate as strategic acts of digital resistance. This research contributes to the scholarly understanding of political humor, digital activism, and multimodal communication in semi-authoritarian contexts. It also serves as a linguistic documentation of contemporary Bangladeshi meme practices of political resistance.

Keywords: Political Memes, Digital Resistance, Pragmatics, Multimodal Discourse, Humor and Satire, Bangladesh, Contemporary Facebook Memes