E-literary creativity on the dark web: Covid-19 Whatsapp bot's interactive storytelling in WhatsApperature

The paper situates electronic literature within touch-screen reading and social media affordances, focusing on automatic interactive narratives used to combat Covid-19 misinformation in Nigeria. It examines the Nigeria Centre for Disease Control (NCDC) and UNICEF’s multilingual SMS-based WhatsApp chatbot, launched on the U-Report platform in November 2020, as a form of digital literary practice termed "WhatsApperature." The study is limited to the Covid-19 WhatsApp Bot’s narratives on WhatsApp (English version), exploring how health communication is appified and how human–bot interaction in a meta-interface supports combating rumors. The author frames the investigation around why WhatsApp bot is chosen, how the bot’s discourse and technotext relate to the reader, and how to build such a bot, employing Pedro Barbosa’s wreader theory and HCI approaches.

The essay connects WhatsApp chatbot storytelling to the lineage of SMS/mobile narratives, notably Japan’s keitai shousetsu (e.g., Yoshi’s Deep Love and Mei’s The Red Thread), whose popularity led to adaptations in film, manga, and anime. It references contemporary African WhatsApp storytelling such as South Africa’s Uk’shona Kwelanga (a WhatsApp drama series driving significant engagement). The author reviews work on WhatsApp’s popularity and healthcare use (Varrela 2021; Mars et al., 2019), its role as a black box of viral misinformation (Wang, 2018), and positions the bot within post-digital practices where algorithms and bots act as authors (Balpe, Portela, Pisarski, Swirski). The theoretical backdrop includes Pedro Barbosa’s wreader theory (reader as co-author via interactive input, originating from systems like Syntext), techno-discursive analysis (Paveau), and perspectives on gamified, multicursal storytelling (Smed et al., Ensslin). Emoji’s communicative functions in digital discourse are discussed (Gawne & Daniel).

The study employs techno-discursive analysis (examining language, semiotics, code, and platform affordances) and Human–Computer Interaction approaches (symmetric/ecological linguistics and interactivity) to analyze the Covid-19 WhatsApp bot’s English-language technotext. The author describes WhatsApp’s multimodal creative affordances (text input, emojis, attachments, voice, etc.) and outlines bot deployment and creation via WhatsApp’s API, coding options, and chatbot builders. The bot’s interactive narrative is mapped using Twine, revealing an arborescent design with 56 multi-hyperlinks connecting 31 passages, and multiple choice models (binary, five-choice, eight-choice/octanary, and quaternary). Pedro Barbosa’s wreader theory is used to interpret the reader’s triadic role (reading, writing, rewriting) through inputs such as YES/NO/A–H and NEXT, showing co-authorship with the bot/algorithm. Emoji functions within the MAIN MENU are analyzed as pointing, emblematic, and action markers that extend and translate the technotext, contributing to prosodic meaning.

• The NCDC–UNICEF WhatsApp chatbot is the first Nigerian multilingual SMS-based interactive bot operating across major mobile networks and social platforms, offering narratives to counter health misinformation in five languages (English, Pidgin, Hausa, Yoruba, Igbo). • WhatsApp’s ubiquity in Nigeria makes it an effective medium: 93% of the country’s 28 million social media users use WhatsApp (Varrela, 2021). • The bot’s interactive design, mapped with Twine, comprises 56 multi-hyperlinks linking 31 passages and employs multiple choice models, including an octanary MAIN MENU. • Emojis embedded in the MAIN MENU function as pointers, emblems, and action cues (e.g., ✔, 👍, 👎, ⛔, ❓, 💞📣, 📱➡️, 👉), enhancing comprehension, prosody, and narrative aesthetics. • The bot is hosted on the dark/deep web and accessed via WhatsApp API, making it non-searchable on standard mobile networks. • Despite platform popularity, the bot itself appears underutilized; requests to U-Report Nigeria, UNICEF Nigeria, and NCDC for usage statistics and source code were unsuccessful, suggesting limited engagement or unavailable data. • The platform supports procedural creativity and gamified reading, positioning readers as co-authors (wreaders) who influence narrative flow through inputs.

Findings indicate that WhatsApp’s interactive, multimodal affordances and the bot’s structured choice models can effectively engage users and counter misinformation by guiding them through curated narratives. The techno-discursive analysis shows that emojis and concise menu options enhance clarity and persuasion, while the wreader framework explains how users’ inputs co-create the narrative, fostering agency and immersion. Hosting on the dark/deep web via API underscores a post-internet production context, yet limits discoverability. The mapped narrative complexity (56 links/31 passages) demonstrates robust design for iterative engagement, with MAIN MENU loops facilitating repeated access to critical information. Overall, the bot exemplifies appified health communication and e-literary practice, where gamified reading and HCI principles enhance understanding and adherence to verified Covid-19 guidance.

The study concludes that interactivity among wreader, symmetric language (linguistic and extra-linguistic signs), and the technology of discourse (WhatsApp bot) produces prosodic meaning and supports a holistic understanding of the technotext. It describes the WhatsApperature system’s functionality and automatic interactive narrative, emphasizing multimodality, multicursal structures, and multiple-choice models within a dark web/post-digital context. Barbosa’s wreader theory substantiates the reader’s co-author role, while emojis reveal the narrative’s pathos, tonality, and aesthetics. The author suggests WhatsApp bots can serve as platforms for digital literary creation and gamified reading in pedagogy. Stable network connectivity is recommended to ensure smooth interaction with the bot.

• Lack of disclosed source code and usage statistics from U-Report Nigeria, UNICEF Nigeria, and NCDC limits assessment of reach and impact. • The bot is not searchable on mobile networks due to dark/deep web hosting, affecting discoverability. • Network glitches can disrupt reading fluidity and interaction. • Emoji interpretation may vary across cultures, potentially affecting comprehension. • WhatsApp is described as a black box of viral misinformation, presenting contextual challenges. • The analyzed bot version generates only text and emoji, limiting multimodality compared to full platform capabilities.