Likes and Virality

A Proverb For The Social Media Age

As with most of my quirky and creative thoughts, this too occurred while I was walking my dog in the morning. This thought stayed with me long after the walk and it meant only one thing. I needed to find an outlet for it.

So, I tried to summarize my thought into a simple quote and posted it on Facebook this morning.

“One person’s handful of likes is another person’s viral post.” — A proverb for the social media age

The day went by and I didn’t think much about the quote until after I settled down for the evening. Since I often criticize myself for being verbose, I surprised myself when I read it again because this succinct summary was quite unlike me. So the more I thought about it, the more I wanted to give myself a pat on the back for summarizing a profound theory in ten words.

But above all that, to do better justice to the crux of my thought, I needed to dwell deeper.

As an experiment, I summoned ChatGPT and DeepSeek to interpret this quote for me. It was interesting that both interpreted the quote only in one way.

Loosely speaking, they both concluded that the quote means the following:

Digital success is relative. Social Media success is interpreted through the lens of individual expectations, cultural norms, and the specific social context of the user. The same number of likes may be thrilling for one user but disappointing for another, highlighting how subjective experiences shape perceptions of virality.

I was hoping that at least one of them would pick up on the other interpretation I was going for.

The arbitrariness and inequality of success, where identical content yields vastly different outcomes depending on who posts it.

I had to prompt both of them and once I did, they both agreed that this quote could also be interpreted the other way.

Next, I tasked them both with producing a thesis using this quote and write a “paper”.

I patiently worked with them both by instructing what I was looking for in the paper (not the actual content or research but more of how I wanted it structured).

Ladies and Gentleman, presenting the two papers generated by my AI assistants.

If you would like, you can comment under this post and guess which paper was produced by ChatGPT and which one was generated by DeepSeek.

PAPER 1

Viral Validation: A Comparative Analysis of Social Media Reception and Perception

Abstract

This thesis explores the relativity of digital validation and the disparities in social media virality through the lens of the proverb:

“One person’s handful of likes is another person’s viral post.”

This statement can be interpreted in two key ways:

1. The Subjectivity of Digital Success — The same level of engagement may feel monumental to one person but trivial to another. Social media creates highly personalized experiences of validation, shaped by psychological expectations, comparison biases, and individual benchmarks for success.
2. The Inequality of Virality — Two users posting identical content may receive drastically different levels of engagement due to algorithmic bias, influencer status, social capital, or platform-based visibility mechanisms. The concept of virality is not purely meritocratic but is often dictated by hidden systemic forces.

By analyzing social media engagement through psychology, algorithmic studies, and media theory, this thesis investigates how individual expectations, platform algorithms, and socio-cultural biases shape both perceptions of virality and actual digital reach.

Introduction

Social media engagement is both deeply personal and structurally biased. The same number of likes can be thrilling for one user and underwhelming for another, demonstrating the relativity of success. At the same time, identical content may experience vastly different levels of engagement when posted by different users, revealing systemic inequalities in digital visibility.

This thesis explores these two interpretations of the proverb through three key questions:

1. How do psychological factors shape individual perceptions of success on social media?
2. How do algorithms and digital hierarchies determine engagement?
3. How does social capital affect virality in an unequal digital landscape?

By examining these questions, we demystify the illusion of meritocracy in social media and explore how engagement is shaped by both personal psychology and platform structures.

Chapter 1: The Psychology of Digital Validation and Perception

1.1 Social Comparison and the Subjectivity of Digital Success

The first interpretation of the proverb reflects how individuals perceive engagement relative to their expectations. According to Social Comparison Theory (Festinger, 1954), people evaluate their success by comparing themselves to others. This applies directly to social media, where engagement metrics function as status indicators.

For instance, research by Chou and Edge (2012) found that Facebook users often perceive others as having more fulfilling lives based on curated online content. Similarly, Marwick & Lewis (2017) discuss how perceived engagement gaps can lead to self-doubt and feelings of inadequacy.

1.2 Dopamine Loops and the Psychological Trap of Engagement

Social media platforms exploit intermittent reinforcement (Kahneman & Tversky, 1979), where unpredictable engagement — like sporadic likes and shares — reinforces compulsive checking behavior. Montag et al. (2019) further argue that social media addiction is fueled by variable reward mechanisms, akin to gambling systems.

Additionally, the hedonic treadmill hypothesis (Brickman & Campbell, 1971) suggests that as users experience higher engagement, their benchmark for success increases, making previous levels of validation feel inadequate. This explains why one person’s 100 likes might feel like a major success, while another person finds the same number disappointing.

Chapter 2: Algorithmic Gatekeeping and Unequal Digital Visibility

2.1 How Social Media Algorithms Dictate Virality

The second interpretation of the proverb — where identical content posted by different individuals gets drastically different engagement — suggests that visibility is governed by platform algorithms rather than content quality.

Gillespie (2018) describes algorithms as the “custodians of the internet,” determining what gets amplified and what remains invisible. Bucher (2017) introduces the term “algorithmic imaginary,” where users falsely believe they have control over their reach when, in reality, platforms dictate visibility through opaque mechanisms.

Bakshy et al. (2012) conducted a landmark study on Twitter, demonstrating that early engagement velocity significantly impacts whether a post goes viral. This means that if an influencer and a regular user post identical content, the influencer’s post is far more likely to be algorithmically amplified.

2.2 Engagement Disparities and Platform Biases

Algorithmic bias does not impact all users equally. Research shows that race, gender, and geography influence social media engagement. Marwick & Lewis (2017) document how social media platforms disproportionately suppress content from marginalized creators, leading to systematic disparities in visibility.

Moreover, Pasquale (2015) introduces the concept of the “black box society,” where users are unaware of how their content is ranked, creating an illusion of fairness in digital engagement. This ties directly to the second interpretation of the proverb: engagement is not distributed equally, even when content quality is identical.

Chapter 3: Social Capital and Digital Privilege in the Attention Economy

3.1 Influencer Status and the Advantage of Pre-Existing Audiences

The second interpretation of the proverb also aligns with Bourdieu’s (1986) concept of social capital — the idea that individuals with pre-existing networks have greater access to visibility and resources.

Jenkins, Ford, & Green (2013) discuss how “spreadable media” disproportionately benefits those with larger followings, reinforcing hierarchical structures in digital engagement. Thus, an established influencer can post a mediocre meme and get thousands of likes, while an unknown creator may post brilliant content and get ignored.

3.2 The Illusion of Meritocracy in Virality

Many users assume social media operates on a meritocratic model, where the best content naturally rises to the top. However, research by boyd (2010) and Shifman (2013) debunks this myth, demonstrating that virality is often pre-determined by digital hierarchies and pre-existing audience reach.

Similarly, Zuboff (2019) argues that social media platforms manipulate visibility for profit-driven motives, further entrenching engagement disparities.

Conclusion: Rethinking Digital Success and Visibility

By integrating both interpretations of the proverb, this thesis demonstrates that virality is both psychologically relativeand structurally unequal. While individual users experience engagement differently based on expectations and comparisons, social media platforms actively create disparities in digital visibility through algorithmic bias and social capital hierarchies.

Recognizing these complexities helps demystify the illusion of digital meritocracy, encouraging a more nuanced understanding of online validation. Ultimately, this proverb serves as a powerful reflection of how the modern digital economy shapes both our expectations and our realities.

References

• Bakshy, E., Hofman, J. M., Mason, W. A., & Watts, D. J. (2012). Everyone’s an influencer: Quantifying influence on Twitter. Proceedings of the Fourth ACM International Conference on Web Search and Data Mining.
• Baym, N. K. (2015). Personal connections in the digital age. Polity Press.
• boyd, d. (2010). Social network sites as networked publics: Affordances, dynamics, and implications. In Z. Papacharissi (Ed.), A Networked Self: Identity, Community, and Culture on Social Network Sites. Routledge.
• Bucher, T. (2017). The algorithmic imaginary: Exploring the ordinary affects of Facebook algorithms. Information, Communication & Society, 20(1), 30–44.
• Chou, H. T. G., & Edge, N. (2012). “They are happier and having better lives than I am”: The impact of using Facebook on perceptions of others’ lives. Cyberpsychology, Behavior, and Social Networking, 15(2), 117–121.
• Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7(2), 117–140.
• Gillespie, T. (2018). Custodians of the internet: Platforms, content moderation, and the hidden decisions that shape social media. Yale University Press.
• Jenkins, H., Ford, S., & Green, J. (2013). Spreadable media: Creating value and meaning in a networked culture.NYU Press.
• Pasquale, F. (2015). The Black Box Society: The Secret Algorithms That Control Money and Information.Harvard University Press.
• Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. PublicAffairs.

PAPER 2

Doctoral Thesis: “One Person’s Handful of Likes is Another Person’s Viral Post: A Dual Lens on Relativity and Inequality in Social Media Success”

Abstract:

This thesis explores the sociocultural implications of the proverb, “One person’s handful of likes is another person’s viral post,” through two interconnected interpretations. First, it examines how success on social media is relative, shaped by individual expectations, cultural norms, and platform-specific metrics. Second, it investigates how success is arbitrary and unequal, as identical content can yield vastly different outcomes depending on who posts it and how algorithms mediate visibility. Drawing on theories of cultural capital, social comparison, and algorithmic bias, this research argues that social media metrics are not objective measures of worth but are instead deeply contextual, contingent, and often unjust. By integrating these interpretations, the thesis offers a comprehensive critique of digital culture and proposes pathways toward a more equitable and meaningful online world.

Introduction:

The proverb, “One person’s handful of likes is another person’s viral post,” encapsulates two critical dimensions of social media success: relativity and inequality. On one hand, success is relative, as users interpret metrics like likes and shares through the lens of their own goals, cultural context, and audience size. On the other hand, success is arbitrary and unequal, as identical content can yield vastly different outcomes depending on who posts it, when it’s posted, and how algorithms mediate visibility. This thesis integrates these two interpretations to provide a nuanced understanding of how value, perception, and success are constructed in digital spaces. By examining the interplay between individual agency, cultural hierarchies, and platform politics, this research sheds light on the fragmented and hierarchical nature of social media culture.

Chapter 1: The Relativity of Value in Digital Spaces

This chapter establishes the theoretical foundation for understanding value as a subjective and context-dependent construct in social media. Drawing on Pierre Bourdieu’s concept of cultural capital (Bourdieu, 1986), it argues that social media metrics function as a form of digital capital, whose value is determined by the social and cultural context of the user. For some, a handful of likes may represent a meaningful connection with a close-knit community, while for others, viral success is the benchmark of achievement.

The chapter also introduces the second interpretation of the proverb, highlighting how identical content can yield vastly different outcomes depending on who posts it. For example, a meme posted by an influencer with millions of followers is far more likely to go viral than the same meme posted by an average user with a small following. This dynamic reflects the uneven distribution of cultural and social capital in digital spaces, where success is often determined by pre-existing advantages rather than merit.

The chapter concludes by exploring how platform design influences the perception of value. For instance, Instagram’s emphasis on visual aesthetics and TikTok’s focus on virality create different expectations for success, further complicating the relativity and inequality of social media metrics.

Chapter 2: Social Comparison and the Psychology of Validation

Building on Leon Festinger’s social comparison theory (Festinger, 1954), this chapter examines the psychological mechanisms that drive users to seek validation through likes and shares. The proverb encapsulates the relativity of success, where users constantly compare their metrics to those of others. This comparison fuels both aspiration and anxiety, as users strive to meet or exceed the perceived standards of their peers.

The chapter also explores how the arbitrariness of success exacerbates these psychological dynamics. For example, a user might feel frustrated or demoralized when their post receives only a handful of likes, while someone else’s identical post goes viral. This frustration can lead to feelings of injustice and self-doubt, as users struggle to understand why their efforts are not rewarded equally.

Finally, the chapter examines how cultural factors influence the psychology of validation. In collectivist cultures, where group harmony is prioritized, a handful of likes from close friends may hold more value than viral success among strangers. In contrast, in individualist cultures, where personal achievement is emphasized, viral success may be seen as the ultimate goal.

Chapter 3: Platform Politics and the Algorithmic Mediation of Success

This chapter delves into the technological infrastructure that underpins social media metrics, arguing that platforms like Instagram, TikTok, and Twitter are not neutral spaces but are governed by algorithms that amplify certain types of content while marginalizing others (Napoli, 2019). The proverb reflects the uneven playing field created by these algorithms, where viral success is often contingent on factors beyond individual control, such as timing, trends, and platform biases.

The chapter examines how algorithmic bias exacerbates inequalities in social media success. For example, platforms might prioritize content from users who have already achieved viral success, creating a Matthew Effect where the rich get richer and the poor get poorer (Merton, 1968). This dynamic reinforces the proverb’s observation that identical content can yield vastly different outcomes depending on who posts it.

The chapter also critiques the commodification of attention, where users are incentivized to chase metrics that benefit the platform rather than themselves (Terranova, 2000). For instance, TikTok’s “For You Page” algorithm encourages users to create content that aligns with trending formats, often at the expense of originality or authenticity.

Chapter 4: Cultural Hierarchies and the Fragmentation of Digital Communities

This chapter explores how the relativity and inequality of success on social media mirror broader societal inequalities. Drawing on Stuart Hall’s work on cultural representation (Hall, 1997), it examines how race, gender, class, and geography influence who gets to go viral and who remains confined to a “handful of likes.” The proverb underscores the fragmentation of digital communities, where success is not universally accessible but is instead shaped by existing power structures.

The chapter also considers the role of niche communities in redefining success on their own terms. For instance, LGBTQ+ communities on platforms like Tumblr have created alternative metrics of success, such as fostering safe spaces and building supportive networks (Renninger, 2015). These communities challenge the hegemony of virality, demonstrating that success can be measured in ways that go beyond quantitative metrics.

Chapter 5: Redefining Success in the Age of Social Media

The final chapter proposes a reimagining of success that moves beyond quantitative metrics. It argues that the proverb invites users to question the values embedded in social media platforms and to seek more meaningful forms of connection and validation. Drawing on Couldry and van Dijck’s (2015) concept of social media as a public sphere, the chapter envisions a future where success is not measured by likes or shares but by the depth and authenticity of online interactions.

The chapter highlights alternative models of digital engagement, such as slow media, which emphasizes quality over quantity, and community-building, which prioritizes relationships over metrics. It also explores how creative expression can serve as a form of resistance against the commodification of attention.

References:

1. Bourdieu, P. (1986). The Forms of Capital. In J. Richardson (Ed.), Handbook of Theory and Research for the Sociology of Education (pp. 241–258). New York: Greenwood.
2. Festinger, L. (1954). A Theory of Social Comparison Processes. Human Relations, 7(2), 117–140. https://doi.org/10.1177/001872675400700202
3. Gillespie, T. (2014). The Relevance of Algorithms. In T. Gillespie, P. Boczkowski, & K. Foot (Eds.), Media Technologies: Essays on Communication, Materiality, and Society (pp. 167–194). MIT Press.
4. Napoli, P. M. (2019). Social Media and the Public Interest: Media Regulation in the Disinformation Age. Columbia University Press.
5. Terranova, T. (2000). Free Labor: Producing Culture for the Digital Economy. Social Text, 18(2), 33–58. https://doi.org/10.1215/01642472-18-2_63-33
6. Hall, S. (1997). Representation: Cultural Representations and Signifying Practices. Sage Publications.
7. Jenkins, H. (2006). Convergence Culture: Where Old and New Media Collide. NYU Press.
8. Couldry, N., & van Dijck, J. (2015). Researching Social Media as if the Social Mattered. Social Media + Society, 1(2). https://doi.org/10.1177/2056305115604174
9. Merton, R. K. (1968). The Matthew Effect in Science. Science, 159(3810), 56–63.
10. Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press.
11. Jackson, S. J. (2020). #HashtagActivism: Networks of Race and Gender Justice. MIT Press.
12. Renninger, B. J. (2015). “Where I Can Be Myself… Where I Can Speak My Mind”: Networked Counterpublics in a Polymedia Environment. New Media & Society, 17(9), 1513–1529. https://doi.org/10.1177/1461444814530095