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WEEK 8 – Have You Ever Posted on Social Media During an Emergency?

Have you ever posted on social media during an emergency?

Maybe it was sharing information about a flood in your area, reposting evacuation notices during a wildfire, or checking whether friends and family were safe after a natural disaster.

Social media is often associated with entertainment, memes, and everyday communication. However, during times of crisis, these platforms can become something much more important. When traditional communication systems fail or become overwhelmed, people increasingly turn to platforms such as Facebook, Twitter, YouTube, and WhatsApp to share information, seek help, and coordinate responses (Bruns & Burgess, 2014).

There is something remarkable happening every time a disaster unfolds online. Information no longer flows only from governments, journalists, or emergency services. Ordinary citizens become active participants in collecting, verifying, and distributing information. In many cases, people on the ground can provide updates faster than official organisations.

This process is often described as crowdsourcing. Crowdsourcing refers to the collection of information, knowledge, or resources from a large group of people, usually through digital platforms (Howe, 2008). During natural disasters such as the Haiti earthquake, the Japan tsunami, the Queensland floods, and the Black Saturday bushfires, volunteers used social media and collaborative mapping tools to gather real-time information from affected communities. The result was a new form of crisis communication that relied on networks of ordinary people rather than solely on traditional authorities.

The rise of crowdsourcing challenges conventional understandings of communication during emergencies. Traditionally, information moved through hierarchical structures, from governments and emergency services to the public. Social media has transformed this process into a networked model where information can travel rapidly between citizens, communities, journalists, and institutions (Bruns & Burgess, 2014).

This shift reflects broader changes in digital communities. Online networks allow people to come together around shared goals, even if they have never met. Boyd (2010) describes these spaces as networked publics — publics that are restructured by networked technologies and shaped by the interactions of connected users. During crises, these temporary communities often emerge quickly, sharing information, coordinating aid, and solving problems collectively.

Volunteer programmers, digital activists, and local residents frequently collaborate to create tools and resources that assist disaster response efforts. Jenkins (2006) argues that digital communities often generate collective intelligence, where knowledge is produced through the contributions of many individuals rather than a single authority. Crowdsourcing demonstrates how collective intelligence can be mobilised in times of crisis to solve problems and distribute critical information.

However, crowdsourcing is not without its challenges. While social media enables rapid information sharing, it also creates opportunities for misinformation and rumours to spread. In fast-moving emergencies, inaccurate information can cause confusion, panic, or even place people at risk. Information shared by the crowd may be fast, but it is not always reliable (Bruns & Burgess, 2014).

This creates an important tension. On one hand, crowdsourcing empowers citizens and allows communities to respond quickly when official systems are overwhelmed. On the other hand, emergency response requires accurate and trustworthy information. The same platforms that enable collective intelligence can also amplify mistakes.

The question, then, is not simply whether crowdsourcing is useful during disasters.

WHEN CRISIS STRIKES, SHOULD WE TRUST OFFICIAL SOURCES, OR THE COLLECTIVE KNOWLEDGE OF THE CROWD?

References

boyd, d. (2010). Social Network Sites as Networked Publics: Affordances, Dynamics, and Implications. In Z. Papacharissi (Ed.), Networked Self: Identity, Community, and Culture on Social Network Sites. Routledge.

Bruns, A., & Burgess, J. (2014). Crisis Communication in Natural Disasters: The Queensland Floods and Twitter. In K. Weller, A. Bruns, J. Burgess, M. Mahrt & C. Puschmann (Eds.), Twitter and Society. Peter Lang.

Howe, J. (2008). Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business. Crown Business.

Jenkins, H. (2006). Convergence Culture: Where Old and New Media Collide. New York University Press.

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WEEK 7 – Have You Ever Received a Rude Comment Online?

Have you ever received a rude comment online?

Maybe it was a mean reply on Instagram, an insulting comment on TikTok, or someone attacking your opinion in a discussion forum.

Social media is often celebrated as a space for connection, creativity, and community. It allows people to communicate, share ideas, participate in social causes, and engage with others across geographical boundaries.

But increasingly, social media is also becoming a site of conflict. Harassment, trolling, cyberhate, and abuse have become common experiences for many users. What should be a space for participation can quickly become a space of exclusion.

Digital citizenship is often understood as the ability to use digital technologies responsibly and positively to participate in society. According to the eSafety Commissioner and Mossberger et al. (2008), digital citizenship involves developing the skills and knowledge necessary to communicate effectively, create content, and contribute to society through digital technologies. Yet conflict on social media demonstrates that participation is not always equal. Power often shapes who gets to speak, who gets heard, and who feels safe enough to participate.

One of the most common forms of online conflict is harassment. Marwick and Caplan (2018) argue that online harassment is often networked rather than individual. Instead of a single person behaving badly, groups of users may coordinate attacks through practices such as doxing, intimidation, social shaming, and image-based abuse. These behaviours are designed not only to offend but also to silence and exclude particular individuals from online spaces.

Research suggests that these experiences are not distributed equally. Plan International's Free To Be Online report found that 59% of girls surveyed across 31 countries had experienced abusive or insulting language online. Similarly, Haslop, O'Rourke and Southern (2021) found that women and transgender individuals are disproportionately targeted by online harassment. Studies also show that online abuse often reflects offline inequalities related to gender, race, and sexuality.

This raises important questions about social media governance. Governance refers to the systems, rules, and regulations that shape how digital platforms operate. While governments can introduce laws such as Australia's Online Safety Act 2021, governance also occurs at a smaller scale through community guidelines, moderators, and platform policies. Social media companies occupy a powerful position because they effectively determine what content remains visible and what content is removed.

Some argue that stronger regulation is necessary to protect vulnerable users. Others worry that increased moderation may restrict freedom of expression. Platforms therefore face the difficult challenge of balancing safety, participation, and free speech while also pursuing commercial interests.

Conflict, then, reveals something important about digital communities. Rather than being neutral spaces, social media platforms are sites where power is constantly negotiated between users, moderators, corporations, and governments.

The question, then, is not simply whether online harassment is harmful.

WHO SHOULD BE RESPONSIBLE FOR MAKING SOCIAL MEDIA SAFE — INDIVIDUAL USERS, PLATFORM COMPANIES, OR GOVERNMENTS?

References

Marwick, A. E., & Caplan, R. (2018). Drinking Male Tears: Language, the Manosphere, and Networked Harassment.

Haslop, C., O'Rourke, A., & Southern, R. (2021). Online Harassment and Digital Citizenship.

Mossberger, K., Tolbert, C., & McNeal, R. (2008). Digital Citizenship.

Week 10 Lecture: Digital Citizenship and Social Media Conflict (2023).

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WEEK 6 – Do You Watch Twitch Streamers or Gaming Livestreams?

Do you play video games?

Whether it's competitive PvP matches, cooperative raids with friends, first-person shooters, or relaxing farming games like Stardew Valley, gaming has become one of the most popular forms of entertainment in the digital age.

But increasingly, playing games is only part of the experience. Millions of people now spend hours watching others play through livestreaming platforms such as Twitch and YouTube Gaming. For many players, gaming is no longer just about participation — it is also about spectatorship, community, and shared digital experiences.

There is something interesting happening every time you open a Twitch stream. You're not playing the game yourself, yet you're still part of the experience. Through live chat, donations, memes, and community discussions, viewers become active participants in gaming culture rather than passive audiences.

Gaming communities have always been social spaces. Historically, players gathered in arcades, local multiplayer settings, and online gaming networks to share experiences, strategies, and knowledge. As networked technologies evolved, these communities expanded beyond physical spaces and became increasingly digital. Hardwick (2023) describes gaming communities as social communities where players move between multiple overlapping groups based on shared interests, expertise, and knowledge.

This shift has been accelerated by livestreaming platforms such as Twitch, YouTube Gaming, and Facebook Gaming. What was once considered unusual — watching someone else play a video game — is now a major form of digital entertainment. Streaming is often live, platform-based, and highly profitable, while communities form around both streamers and the content they create (Hardwick, 2023).

Jenkins' (2006) concept of knowledge communities helps explain why these platforms have become so popular. According to Jenkins, digital communities are built through shared intellectual interests and emotional investments. Members voluntarily exchange information, collaborate, and collectively produce knowledge. Within gaming communities, viewers do far more than simply watch gameplay. They share strategies, discuss game updates, teach newcomers, and contribute to a collective understanding of the games they love.

However, gaming communities are not always welcoming spaces. Hardwick (2023) notes that the stereotypical image of the "gamer" is often associated with being young, male, and either white or East Asian. This perception has contributed to a masculine-dominated gaming culture where certain groups may feel excluded from participation. As gaming communities increasingly move online, issues such as harassment, gatekeeping, and toxic behaviour continue to shape who feels comfortable participating and whose voices are heard.

At the same time, livestreaming can create opportunities for inclusion and connection. Communities often form around streamers rather than games themselves. Many viewers return not only for the gameplay, but also for the sense of belonging that develops through regular interaction with streamers and other audience members. During periods of social isolation, these communities have provided spaces for friendship, support, and shared experiences.

This raises an interesting question about the future of gaming culture. If games were traditionally designed to be played, what does it mean when millions of people choose to watch instead? Has livestreaming expanded gaming into a richer and more social experience, or has it transformed play itself into a form of content consumption?

The question, then, is not simply whether game streaming is beneficial or harmful.

WHO BENEFITS MOST FROM THE RISE OF GAME STREAMING PLATFORMS — THE PLAYERS, THE COMMUNITIES, OR THE PLATFORMS THEMSELVES?

References

Hardwick, T. (2023). Gaming Communities, Social Gaming and Live Streaming. MDA20009 Digital Communities Week 8 Lecture.

Jenkins, H. (2006). Convergence Culture: Where Old and New Media Collide.

Suits, B. (1978). The Grasshopper: Games, Life and Utopia.

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WEEK 5 - Do you use Snapchat or Instagram filters?

There is something philosophically strange happening every time you open your front-facing camera on Instagram. The face staring back at you like smoothed, symmetrised, lit from within is not quite yours. And increasingly, that might be the problem.

Augmented reality filters are not new. AR has existed as a technology since the 1960s, and its mainstream proliferation tracks almost exactly with smartphone adoption. But 2016 marked a turning point: Snapchat's face-swap filters and Pokémon Go brought AR into everyday visual culture, and the stakes shifted from novelty to normativity. What began as a playful technological gimmick dog ears, rainbow tongues has since evolved into something far more structurally significant.

Rettberg (2014) offers a useful way into this. Filters, she argues, do not simply remove — like a coffee filter blocking grounds — they also add. They slow the passage of the "raw" image through a set of aesthetic values, and what emerges on the other side is flavoured by those values. The point is not just what filters block (blemishes, asymmetry, texture), but what they actively construct: a particular standard of legibility, of what a face is supposed to look like when it enters the social media frame. And crucially, that standard is not neutral. As Lavrence and Cambre (2020) observe, what began as conspicuous, playful editing has undergone a quiet shift toward ambient editing subtle alterations so normalised that their presence is no longer obvious, and their absence becomes the aberration.

The racial politics of this are worth sitting with. The so-called "Instagram face" — that smooth, vaguely undefined ethnicity that has come to dominate platform aesthetics — is, as critics have noted, distinctly white but ambiguously ethnic: a face that launders whiteness through the aesthetics of exoticism. Beauty and "surgery" filters are among the most popular on both Instagram and Snapchat, and many of them actively promote a homogenous, racially coded standard of attractiveness that disproportionately burdens women of colour with the labour of conforming to features that were never coded from theirs.

The downstream consequences of this ambient beauty regime are now entering the clinical literature. Rajanala, Maymone and Vashi (2018) coined the term "Snapchat dysmorphia" to describe a documented shift in cosmetic surgery consultations: where patients once brought photographs of celebrities to approximate an aspirational face, they now arrive with filtered selfies — images of themselves, altered — and request that their real face be made to match. The ideal is no longer someone else. It is a version of you that has never existed outside of an algorithm. Research by Burnell, Kurup and Underwood (2021) complicates this further: more frequent filter use correlates with greater body image concerns, but not necessarily with reduced satisfaction in the moment of use. This is Perloff's (2014) "mutually reinforcing relationship" — filter use and body dissatisfaction feed each other in a loop that is difficult to interrupt, because the harm is structural rather than acute.

This is where Fisher's (2020) concept of technological deskilling becomes useful. As AR tools grow more sophisticated on the back end, they require less and less critical engagement from the user. You do not need to understand how a filter reconstructs your facial geometry to use one. That opacity — the seamless, one-tap access to a computationally altered face is precisely what concentrates power in the hands of those who build and monetise the tools, while users are left with the affective consequences of an aesthetic system they did not design and cannot fully see.

None of this forecloses the more optimistic readings. Cyberfeminist thinkers from Donna Haraway to Sadie Plant have long argued that technology carries liberatory potential — that the cyborg figure, detached from material and societal expectations of the body, opens space for identity play and self-construction outside of inherited norms. According Coy-Dibley's in 2016 concept of "positive dysmorphia" gestures at this: the possibility that digital dis/embodiment could be used subversively, to try on identities rather than simply conform to them. But the evidence suggests that, in practice, beauty filters make this difficult. Users of Snapchat's beauty filters report finding it virtually impossible to "look ugly" within the system (Hawker & Carah 2020). The subversive potential of the technology is constrained by its design — and its design reflects the values of the platforms that profit from sustained aesthetic aspiration.

The question, then, is not simply whether filters are harmful. It is:

WHO DECIDES WHAT THE FILTERS LOOKS LIKE, AND WHO BEARS THE COST OF NOT BEING ABLE TO ACHIECE IT?

References

Rettberg, J. W. (2014). Seeing Ourselves Through Technology (Ch. 2). Palgrave Macmillan.

Lavrence, C., & Cambre, C. (2020). "Do I look like my selfie?": Filters and the digital-forensic gaze. Social Media + Society.

Rajanala, S., Maymone, M., & Vashi, N. (2018). Selfies — living in the era of filtered photographs. JAMA Facial Plastic Surgery.

Burnell, K., Kurup, A. R., & Underwood, M. K. (2021). Snapchat lenses and body image concerns. Body Image, 38.

Fisher, M. (2020). The smooth life: Instagram as a platform of control. Wi: Journal of Mobile Media.

Hawker, L., & Carah, N. (2020). Snapchat's augmented reality brand culture. Continuum.

Coy-Dibley, I. (2016). Digitised dysmorphia of the female body. European Journal of Women's Studies, 23(3).

Perloff, R. M. (2014). Social media effects on young women's body image concerns. Sex Roles, 71(11–12).

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WEEK 4 - Are We Freely Expressing Ourselves on Instagram or Working for Free?

We tend to think of posting selfies on social media as a form of self-expression but contemporary media research challenges this intuition. Microcelebrity, as a form of identity, exists almost exclusively within online spaces (Senft, 2012). Its core logic is not "be yourself" but rather the transformation of the self into a branded commodity, trading visibility for status and influence.

This brings us to a key concept: aesthetic templates. These templates are not spontaneously generated by users they are a set of poses, props, filters, and body practices normalised by microcelebrity culture, dictating which kinds of bodies, faces, and styles get amplified by the algorithm and rewarded with visibility. The problem is that Instagram users are unknowingly engaged in a form of unpaid labour (Marwick, 2013): carefully curating their personal brand and producing content that generates value for the platform, not for themselves.

The deeper tension lies in the structure of the prosumer (Ritzer & Jurgenson, 2010): Instagram users are simultaneously consumers (scrolling, liking, internalising aesthetic standards) and producers (uploading content, reinforcing those very standards). Fontenelle (2015) goes further, arguing that this co-production reproduces the power structures embedded in heteronormative advertising models. The content users "freely" post has, in many ways, already been pre-shaped by the platform's recommendation systems.

The public health implications are real and serious. When unachievable appearance ideals are endorsed and circulated by influencers under the guise of "health campaigns," and when users invest enormous time and money trying to close the gap between their idealised online image and their offline body (identity dissonance), this is no longer merely a question of aesthetic preference — it becomes a political question about whose bodies the algorithm deems worthy of visibility, and whose bodies are systematically marginalised for failing to conform to the dominant template.

Within this framework, "posting what you like" is not as innocent as it appears. Every time we post, we participate in the feedback loop that engineers platform aesthetics (Carah & Dobson, 2016) — feeding the algorithm with our data while simultaneously being trained by it to become more "photogenic" users. This is not a conspiracy theory; it is the structural reality of the platform economy.

References

Senft, T. (2012). Microcelebrity and the branded self. In A Companion to New Media Dynamics. Blackwell.

Marwick, A. E. (2013). Status Update: Celebrity, Publicity, and Branding in the Social Media Age. Yale University Press.

Ritzer, G., & Jurgenson, N. (2010). Production, consumption, prosumption. Journal of Consumer Culture, 10, 13–36.

Carah, N., & Dobson, A. (2016). Algorithmic hotness. Social Media + Society, 2(4).

Mavroudis, J. (2020). Digital citizenship and body modification on visual social media. Swinburne University.

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Week 3: Microcelebrity Culture, Aesthetic Labour and Body Image on Social Media

Social media platforms such as Instagram and TikTok have transformed the way people present themselves online. This week’s lecture explored concepts such as microcelebrity culture, aesthetic labour, pornification, and body dysmorphic disorder (BDD). These topics highlight how social media is deeply connected to identity, public health, and beauty standards.

One of the most interesting ideas discussed in the lecture was “microcelebrity”. According to Theresa Senft (2012), microcelebrity refers to individuals building a public online identity by branding themselves for visibility and attention. On platforms like Instagram, users often carefully edit photos, use filters, and follow aesthetic trends to gain likes and followers. This process can become a form of unpaid labour because users constantly market themselves online.

The lecture also introduced the idea of “aesthetic labour”. This refers to the work people do on their appearance to fit social expectations. On visual social media, users may change their poses, clothing, makeup, or even undergo cosmetic procedures to match popular beauty standards. I think this is especially visible among influencers who promote fitness, skincare, or fashion products. Many influencers appear perfect online, but these images are often highly edited and unrealistic.

Another important topic was “pornification”, where social media increasingly promotes sexualised body images. Research suggests that women are often encouraged to present themselves in ways that emphasise physical attractiveness for online attention (Drenten & Gurrieri 2019). Meanwhile, men are usually expected to present strength, athleticism, and dominance. These gender expectations can create pressure for users to conform to narrow beauty ideals.

I believe social media algorithms make this issue worse because content that matches mainstream beauty standards often receives greater visibility. This can negatively affect mental health, especially among young people. The lecture linked this to Body Dysmorphic Disorder (BDD), where individuals become extremely distressed about specific parts of their appearance. Constant comparison with influencers and celebrities may increase dissatisfaction with one’s real-life body.

Overall, this lecture demonstrates that social media is not only a communication tool but also a powerful system that shapes identity, beauty standards, and public health. Greater awareness and regulation may be needed to reduce harmful body image pressures online.

References

Drenten, J & Gurrieri, L 2019, ‘Sexualized labour in digital culture: Instagram influencers, porn chic and the monetization of attention’, Gender, Work and Organization.

Marwick, AE 2013, Status Update: Celebrity, Publicity, and Branding in the Social Media Age, Yale University Press.

Senft, T 2012, ‘Microcelebrity and the Branded Self’, in A Companion to New Media Dynamics, Blackwell.

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Week 2: Digital Citizenship? Hashtag Publics, Political Engagement and Activism 🌐

Digital citizenship as concept has moved beyond a technocentric notion of “appropriate” and basic technology use; on the other hand it now involves an intricately interweaved form of normative engagement, comportment, attitude and socio-political agency (for more detail on this contemporary mediatised web). Digital citizenship is often described as the ability to participate in society online in a competent way (Mossberger et al., 2008) but it is gradually being examined through platformisation—the concept referring to how social activities are put in accordance with the monetary and technical rationality of digital platforms (Helmond, 2015).

Although platforms refrain from declaring themselves as doing anything beyond behaving neutral and operating as "intermediaries," they are, in fact, ideological infrastructures that regulate political conversation by algorithm (Gillespie, 2010). The hashtag public is a direct reflection of this structural environment and its impact on political engagement. The nature of these ad-hoc digital assemblies enables participants to circumvent intermediaries the such as traditional institutional gatekeepers, resulting in a global and fluid form of activism (Bruns & Burgess, 2015). For example, movements like #BlackLivesMatter or #MeToo show how hashtags can work as discursive anchors mobilizing marginalized voices to organize collective action in opposition to conventional power mechanisms.

But the effectiveness of this activism is up for much debate. The same low barrier to entry that permits participation also enables slacktivism-performative acts that may lack enduring political ramifications—and subjects citizens to systemic hazards like algorithmic radicalisation and state-directed surveillance (Williamson, 2018). At its heart, digital citizenship is an ongoing trade-off between personal agency and the algorithmic limits of the online public sphere.

References

Mossberger, K., Tolbert, C. J., & McNeal, R. S. (2008). Digital Citizenship: The Internet, Society, and Participation. MIT Press.

2. Gillespie, T. (2010). The politics of ‘platforms’. New Media & Society, 12(3), 347-364.

3. Helmond, A. (2015). The platformization of the web: Making data platform ready. Social Media + Society, 1(2).

4. Bruns, A., & Burgess, J. (2015). Twitter hashtags from ad hoc publics to calculated publics. In Hashtag Publics: The Power and Politics of Discursive Networks.

5. Papacharissi, Z. (2015). Affective Publics: Sentiment, Technology, and Politics. Oxford University Press.

6. Van Dijck, J., Poell, T., & De Waal, M. (2018). The Platform Society: Public Values in a Connective World. Oxford University Press.

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Week 1: Case Study of Reality TV 📺

Have you ever seen a reality television program? Reality TV has grown to be one of the most popular forms in today's entertainment sector, from talent contests to dating shows. Many of these programs aim to feel "real" by showcasing competitors' unadulterated personalities, uncensored emotions, and impulsive reactions. Audiences are drawn to this authenticity because it gives them the impression that they are seeing real experiences rather than staged performances.

But is reality TV really "real"?

Image source: Adobe Stock (https://stock.adobe.com/)

Though academics contend that reality TV is frequently meticulously crafted through editing and production techniques, reality TV is widely described as unscripted television featuring common people in real-life settings (Nabi, 2007). In actuality, the genre thrives on theatrical behavior and exaggerated emotions that give the impression of authenticity, according to hypervisibility.

The fact that reality TV continues to receive high ratings worldwide despite the fact that many viewers claim to detest it is a crucial paradox. This implies that its entertainment value, escape potential, and social connection opportunities are what attract viewers (Lundy et al., 2008).

Furthermore, reality TV is no longer limited to television. Social media platforms facilitate communication between participants and viewers, transforming shows into multi-platform tales (Arcy, 2018). In Malaysia, social media sites like Facebook and WhatsApp serve as virtual publics where users interact and debate these initiatives, fostering the development of online communities. This illustrates the concept of the public sphere, where people congregate to share ideas and influence public conversation (Kruse, 2018).

However, these exchanges can make it difficult to distinguish between private and public life, which can occasionally result in problems like cyberbullying.

In conclusion, reality TV is a manufactured kind of television that influences viewers' perceptions of authenticity, identity, and social interaction rather than merely reflecting reality.

Image source: The Hollywood Reporter (2024). Retrieved from https://www.hollywoodreporter.com/business/digital/all-reality-tv-streaming-service-amc-networks-1236429969/

References

Nabi, R. L. (2007). Determining dimensions of reality: A concept mapping of the reality TV landscape.

Lundy, L. K., Ruth, A. M., & Park, T. D. (2008). Simply irresistible: Reality TV consumption patterns.

Arcy, J. (2018). The digital money shot: Twitter wars and transmedia storytelling.

Graham, T. (2011). Reality TV as a trigger of everyday political talk in the public sphere.

Kavka, M. (2019). Reality TV and hypervisibility.