Algospeak (2025) Explained: How Social Media Algorithms Influence Language Evolution And Understanding The Language Of Social Media Algorithms

Algospeak: How Social Media Is Transforming the Future of Language by Adam Aleksic delves into the powerful intersection of language and social media, revealing how the rise of algorithms has revolutionized communication online. Through a detailed exploration of linguistic evolution on platforms like TikTok, Instagram, and YouTube, Aleksic analyzes the development of a new type of speech — one heavily shaped by the forces of content moderation, censorship, and algorithmic filtering.

This article will offer an in-depth summary and analysis of the key themes of the book, including its critical examination of how algorithms influence not only what words we use but how we express ourselves in the digital age.

Algospeak by Adam Aleksic is a timely exploration of the ways in which algorithms shape human communication. The book investigates how social media platforms, driven by algorithmic forces, have led to the creation of a new sociolect — a set of language practices that exist primarily within online spaces.

As we increasingly rely on these platforms for entertainment, education, and socialization, our language adapts to fit the constraints and affordances that algorithms impose.

This transformation raises important questions about the direction of language in a digital age that is constantly evolving.

Background

Aleksic, a linguist, content creator, and cultural commentator, brings a wealth of experience in understanding how language spreads and evolves in modern contexts. His research interests focus on the intersection of social media, language, and society, and Algospeak is the culmination of years of observing how people adapt their speech to fit the ever-changing landscape of the digital world.

The author is not only an expert in linguistics but also a firsthand participant in the evolving social media ecosystem, which allows him to provide both a scholarly analysis and a personal perspective on the issue.

Summary

1. Introduction: Why Your Kids Are Saying “Unalive”

In the opening of Algospeak, Aleksic introduces the concept of linguistic evolution driven by the internet and social media, focusing on the term “unalive.” This word emerged as a euphemism for “kill” or “commit suicide,” originally intended to circumvent censorship on platforms like TikTok. The phenomenon of euphemistic language, a recurring theme in the book, reflects how language adapts to digital environments.

“Unalive” is a response to sensitive topics that are often censored or suppressed in digital spaces, such as discussions on mental health and suicide. While older generations might find it jarring, for younger users, particularly middle school students, “unalive” serves as a more palatable way to discuss difficult issues. This introduction sets the stage for how algorithmic-driven platforms like TikTok shape language.

The term began as a means to bypass censors and evolved into common vernacular, especially among adolescents. It’s also noteworthy that the term’s rise mirrors larger shifts in how language is commodified online and how social media platforms are influencing linguistic behavior.

Aleksic emphasizes that while some may see terms like “unalive” as trivializing important issues, they open up conversations in environments where discussing sensitive topics can be difficult. In fact, one study cited by Aleksic from 2023 noted that “unalive” helped normalize discussions about suicide, making them more accessible in educational contexts.

This chapter introduces the overarching theme of the book: how algorithms are not just influencing how we interact online but are actively shaping the evolution of language itself. This early exploration into how words like “unalive” gain traction underlines the book’s central thesis—that algorithms have created new pathways for words to spread faster and wider than ever before, often in ways that are hard to track or predict.

By making the reader reflect on the origins and spread of “unalive,” Aleksic successfully primes the reader for deeper discussions on the interplay between language and algorithms throughout the rest of the book.

The introduction hints that words born from these digital environments are often ephemeral but can have lasting impacts on how language evolves in the real world.

2. How to Play Linguistic Whac-A-Mole

In this chapter, Aleksic explores the dynamic nature of language in the age of algorithms, particularly the concept of “linguistic whac-a-mole,” a term he uses to describe the constant cycle of adapting language to avoid censorship. The analogy comes from the arcade game “Whac-A-Mole,” where players repeatedly strike emerging moles, which then pop up in new spots. Similarly, online users create new euphemisms or “coded language” to bypass content moderation systems, which constantly adapt to these new terms.

This chapter digs into how content creators, especially on platforms like TikTok, Instagram, and YouTube, engage in a perpetual battle against algorithmic censorship. As the platforms grow more sophisticated in identifying sensitive terms—whether related to violence, sexual content, or mental health—users invent new words and phrases to sidestep these restrictions.

Terms like “unalive” (from the previous chapter) and others emerge in response to these evolving censorship mechanisms. When one word is banned or suppressed, a new term springs up in its place, creating a never-ending game of linguistic adaptation.

Aleksic highlights the critical role of algorithms in this process, explaining how they don’t just moderate content but actively shape the way people communicate. For instance, words that trigger automatic suppression, like “suicide,” get replaced with euphemistic terms such as “unalive” to ensure that content isn’t removed or shadowbanned. This process is what Aleksic calls “algospeak,” the term he uses to describe the creative ways people circumvent algorithmic controls.

This new form of language allows users to communicate without the fear of their posts being censored, though the price of this innovation is the need for constant change.

Through examples like “leetspeak”—a hacker dialect from the 1980s that involved creatively altering words to bypass text filters—Aleksic traces the roots of this phenomenon. While leetspeak was initially used in text chat rooms to avoid detection, today’s version of this behavior is powered by algorithms that rely on machine learning and AI to suppress or flag content. The more sophisticated the algorithm, the more inventive users become with their linguistic strategies.

The key takeaway from this chapter is that linguistic creativity in the age of algorithms is not a new phenomenon, but it has evolved in response to the tools we use to communicate. Social media platforms, once seen as democratizing spaces for self-expression, have become heavily regulated, creating an environment where language is constantly adapted to meet the demands of these systems. As Aleksic notes, the ongoing cycle of linguistic innovation reflects the ever-evolving relationship between language and technology. By the end of the chapter, readers are left to ponder how much of our language today is genuinely organic, and how much of it is shaped by the invisible hand of algorithms designed to moderate and control online discourse.

This chapter sets the tone for the book’s overarching argument that algorithms are not just regulating content but are actively shaping the very structure of language itself, influencing what we say, how we say it, and when we can say it.

3. Sticking Out Your Gyat for the Rizzler

In this chapter, Aleksic delves into the rapidly evolving landscape of internet slang and how new phrases and trends emerge as a result of algorithmic influence. The phrase “sticking out your gyat for the rizzler” may seem perplexing at first glance, but it is a vivid example of how language, particularly slang, is shaped by digital communities and rapidly evolving social media trends.

Aleksic uses this phrase to highlight how short-form video platforms, especially TikTok, foster the creation of new terms that spread at a lightning pace, often becoming mainstream long before their meanings are fully understood by wider audiences.

At the core of this chapter is the idea of “rizz,” a term that refers to someone’s charisma or charm, particularly in romantic contexts.

This word gained traction through viral videos, memes, and influencer culture, becoming one of the many examples of how internet slang quickly permeates the collective vernacular. The rise of “rizz” and its various spin-offs showcases the power of social media algorithms to amplify and spread these new linguistic trends. As TikTok and Instagram recommend videos based on user behavior, they also promote the spread of specific memes and phrases, turning them into global phenomena.

Aleksic explains that words like “gyat” (short for “goddess, you are the one” or “goddamn you are attractive”) and “rizzler” (a play on “charmer”) come from the algorithmic ecosystem where content creators rely on viral trends to reach larger audiences. These terms are created as part of a cultural dialogue that blends humor, irony, and shared internet knowledge. However, the rapid evolution of these slang words is not without consequences.

As terms like “rizz” spread, they begin to lose their initial meaning, becoming diluted as they are adopted and redefined by different social groups.

The chapter also touches on the role of social media influencers in the process of linguistic change.

Influencers, driven by the need to stay relevant and engage their followers, are often at the forefront of creating and popularizing these terms. They introduce new vocabulary that may start as an inside joke or meme but soon becomes part of the wider digital lexicon. Aleksic reflects on how influencers use their platforms to push boundaries and experiment with language, knowing that the algorithm will reward them for engaging with the latest trends, no matter how absurd or niche the language may seem.

Furthermore, Aleksic draws parallels between the creation of new slang and the historical evolution of language.

Just as words like “bae” and “lit” have become mainstream terms over time, the digital era is accelerating the adoption of new expressions. Social media’s focus on short-form, viral content means that language is evolving faster than ever before. What was once a meme or joke may quickly turn into a widely recognized term, and the boundaries of what is considered “cool” or “acceptable” in language are continually shifting.

Aleksic’s argument in this chapter centers around the idea that social media platforms, particularly those driven by algorithms, are now the primary drivers of linguistic innovation. By continuously surfacing the latest trends and slang, they create an environment where language evolves at an unprecedented pace, driven not by traditional linguistic processes but by the whims of algorithmic recommendation systems.

This chapter ultimately underscores a central theme of Algospeak: the role of algorithms in shaping and influencing the future of language. By facilitating the rapid spread of new terms and phrases, algorithms have created a dynamic linguistic ecosystem where words are born, evolve, and sometimes fade away within the span of a few weeks or months.

Here are some phrases from the book Algospeak

1. “Sticking out your gyat for the rizzler”:

This phrase comes from the viral Rizzler song, a meme created on TikTok in 2023. “Gyat” is a slang term for “butt,” which originates from the African American English (AAE) pronunciation of “goddamn.” “Rizzler” refers to someone skilled in “rizz,” which is slang for seduction. The phrase refers to showing off one’s body or assets, particularly in a seductive or playful manner .

2. “Rizz”:

This term refers to one’s ability to seduce or charm someone. It became popular through TikTok, and by 2023, it was named the Oxford Word of the Year. The rise of “rizz” is part of a broader trend where words related to charm and attraction are normalized and spread through social media .

3. “Sigma”:

A “sigma” is described as a successful or independent male, often compared to the “alpha” male but with a more introspective or lone-wolf quality. The term is commonly used in Gen Z slang, especially in the context of memes and online humor .

4. “Skibidi” and “Ohio”:

These are examples of meme terms that have no intrinsic meaning but gain cultural significance through repetition in viral memes. “Skibidi” and “Ohio” were incorporated into the Rizzler song and became associated with Gen Alpha humor, often used in nonsensical or humorous contexts .

5. “Fanum”:

This term, like “skibidi,” serves as another meme word popularized by viral content. It doesn’t have a specific meaning but became part of the meme culture surrounding Gen Alpha and was popularized through memes like the Rizzler song .

These phrases are part of the rapid linguistic evolution that happens on social media platforms, where new words and phrases are introduced, amplified by algorithms, and spread to large audiences through memes and viral content

4. No Because What Happened to Your Attention?

In this chapter, Aleksic turns his focus to the increasingly fragmented nature of attention in the digital age, particularly in the context of how social media platforms have conditioned users to engage with content in short bursts.

He argues that the rise of TikTok and other short-form video platforms has had a profound impact on how we communicate, interact, and even think. This shift is not just about how we consume media, but how our brains have adapted to the demands of these platforms. The phrase “No because what happened to your attention?” encapsulates the irony and self-awareness of a generation raised on rapid-fire media, where deep focus and engagement are increasingly rare.

Aleksic explains how the design of platforms like TikTok, Instagram Reels, and YouTube Shorts has led to a reconfiguration of attention spans.

The algorithm’s focus on hyper-targeted, addictive content keeps users scrolling endlessly, making it difficult to sustain any one thought for too long. This has created a situation where users have become more accustomed to fleeting moments of entertainment or information, rather than prolonged engagement with more substantial content. While this may seem trivial, Aleksic points out that the way our attention is harnessed by these platforms shapes not just our consumption habits, but also our social interactions, language use, and even our cognitive patterns.

The chapter dives into the psychological effects of this new attention economy. Aleksic highlights the concept of “cognitive load,” referring to the mental effort required to process information. On platforms that deliver content in rapid, bite-sized pieces, cognitive load is minimized, but so is the depth of engagement. Instead of delving into long-form content that requires sustained attention, users are bombarded with a series of disconnected, attention-grabbing snippets.

Over time, this constant switching between topics and formats diminishes the ability to focus deeply on any one subject, resulting in a shallow form of knowledge and understanding.

One of the most notable consequences of this shift is the erosion of critical thinking skills. Aleksic argues that while platforms like TikTok might provide instant gratification and entertainment, they simultaneously foster a culture of passive consumption. Users are less likely to critically engage with content, and more likely to accept whatever is served up by the algorithm.

This is particularly dangerous when it comes to issues like misinformation or political discourse, where short-form, emotionally charged videos can dominate, shaping public opinion without giving people the chance to fully process the facts.

Aleksic also critiques the impact of social media on personal expression and language. With attention spans shrinking, the way people communicate has changed. Instead of engaging in thoughtful dialogue or nuanced expression, individuals have resorted to using quick, punchy phrases or memes to capture attention. The result is a culture of shorthand communication, where the emphasis is on being noticed rather than being understood.

Words like “unalive” and “rizz” (from previous chapters) are part of this shift—a move toward language that is quick, catchy, and optimized for the algorithm. While this may be efficient for grabbing attention, it also sacrifices clarity and depth in favor of instant gratification.

Furthermore, Aleksic discusses how the pressure to constantly perform for the algorithm affects users’ mental health. The need to constantly produce content that is engaging enough to be picked up by the algorithm fosters anxiety, as creators are forced to prioritize virality over authenticity. This cycle of content creation for the sake of algorithmic approval reinforces the notion that attention is a commodity to be captured at all costs, often leaving individuals feeling burnt out or disconnected from their own creative processes.

In examining the relationship between attention and language, Aleksic argues that the way we engage with social media is fundamentally altering how we speak. The need for brevity and impact in communication has led to the rise of more abstract, fragmented forms of expression. Instead of using language to explore complex ideas or convey deep emotions, users increasingly rely on language to get attention quickly, often at the expense of meaning.

Overall, the chapter underscores the deep and pervasive influence that algorithms have on our cognitive patterns and language use. The algorithmic systems that power platforms like TikTok are not just changing how we consume content—they are changing how we think, feel, and express ourselves. As the digital age continues to evolve, the pressures to capture attention in an increasingly fragmented and distracted environment will likely continue to shape the future of language and communication.

5. Why Everybody Sounds the Same Online

In this chapter, Aleksic explores how social media platforms and algorithms contribute to a homogenization of language and expression.

While the internet has long been celebrated for its ability to amplify diverse voices and bring different cultures into dialogue, Aleksic argues that the very systems that make this possible also enforce a uniformity of tone, style, and content that limits individual variation. The chapter investigates how platforms, particularly those with powerful recommendation algorithms like TikTok and Instagram, incentivize creators to conform to certain linguistic norms in order to succeed in the digital marketplace.

Aleksic begins by addressing the role of algorithms in shaping the type of content that users encounter.

These algorithms prioritize content that adheres to a specific set of expectations: viral trends, familiar formats, and language that aligns with what is currently trending. This creates a “feedback loop” in which users and content creators adopt the language and style that the algorithm rewards. Whether it’s the use of memes, catchphrases, or even specific visual aesthetics, creators end up sounding increasingly similar to one another as they try to replicate what has been successful for others.

A major point of discussion is the pressure on content creators to align their language and persona with what the algorithm deems “marketable.”

This leads to a situation where, regardless of individual background or intention, many users begin to speak in the same way—using similar slang, the same viral trends, and identical formats to gain attention. Aleksic highlights how this “sameness” is not just a result of social imitation, but rather an effect of algorithmic structuring. As social media platforms reward viral, attention-grabbing content, creators are conditioned to prioritize what will “perform” well in front of the algorithm, sacrificing originality and authenticity in the process.

The chapter goes on to explore the concept of “platform culture,” which refers to the way that social media platforms cultivate a specific type of language, style, and behavior.

Each platform has its own unique culture, dictated by both user preferences and algorithmic feedback. For example, TikTok is heavily focused on trends, viral dances, and memes, while Instagram might prioritize aesthetically pleasing content or “influencer” culture. Despite these differences, Aleksic argues that all platforms foster a general tendency toward conformity.

Whether through the forced brevity of TikTok videos or the consistent aesthetic of Instagram feeds, the need for content to adhere to specific formats and expectations means that individuality is often lost.

Aleksic also tackles the issue of algorithmic bias, which further contributes to linguistic homogeneity. Algorithms are not neutral; they are designed with certain priorities in mind, such as maximizing user engagement or promoting content that is most likely to go viral. This creates a bias toward content that fits within predictable, formulaic molds. For instance, content that appeals to a broad audience, uses popular slang, or conforms to established trends is more likely to be recommended. This reinforces the use of certain words and expressions, making it harder for unique or niche language to gain traction.

One of the most striking examples Aleksic uses to illustrate this homogenization is the prevalence of “influencer speak”—a distinct style of communication that has emerged on platforms like TikTok and Instagram. This language is characterized by certain vocal intonations, mannerisms, and catchphrases designed to capture attention and create a sense of community. While these practices help influencers connect with their audience, they also contribute to the homogenization of online speech.

The rise of “influencer language” means that many creators end up sounding the same, using the same expressions and language to stay relevant and attract views.

Aleksic concludes the chapter by examining the paradox at the heart of social media culture: the more connected we become, the more we tend to sound like each other. Social media was initially seen as a space for individuality and self-expression, but in practice, it has become a realm where conformity reigns.

The algorithm-driven nature of these platforms, coupled with the pressure to go viral, results in a linguistic culture where “sounding the same” is often the best strategy for success.

In this chapter, Aleksic’s central argument is clear: while social media platforms have democratized the production and dissemination of content, they have also created a landscape where linguistic originality is devalued. The desire to be noticed by the algorithm often leads creators to adopt a standardized, formulaic approach to communication, further contributing to the homogenization of online language.

6. “The Algorithm Really Knows Me”

In this chapter, Aleksic delves into the omnipresent role of algorithms in shaping how we communicate, consume content, and even think. Central to the chapter is the idea that algorithms on platforms like TikTok, YouTube, and Instagram are not just tools for sorting content—they are actively shaping our experiences and behaviors.

The chapter explores how the “algorithm” seems to know users intimately, tailoring content to their individual preferences, but Aleksic warns that this tailored experience comes with hidden costs, both in terms of personal freedom and linguistic innovation.

Aleksic begins by acknowledging the widespread belief that algorithms—especially those on social media—are incredibly sophisticated, capable of predicting our preferences and desires with remarkable accuracy. With platforms like TikTok, users are given content that aligns closely with their interests, often within seconds of opening the app. This personalization has led to a near-religious belief that the algorithm “understands” us. People frequently comment on how “the algorithm knows me better than I know myself,” which speaks to the powerful psychological effect these systems have on us. By analyzing our behavior—such as which videos we like, which we skip, and how long we watch them—algorithms build an increasingly precise profile of our preferences.

However, Aleksic points out that this personalization is a double-edged sword. While it creates an experience where users feel understood, it also reinforces a narrow and fragmented worldview. Algorithms are designed to maximize engagement, which often means prioritizing content that aligns with existing preferences, interests, and biases. This can lead to an echo chamber effect, where users are constantly fed content that confirms their beliefs and attitudes, while alternative perspectives are minimized or hidden.

Over time, this lack of exposure to diverse viewpoints can distort users’ understanding of the world and limit their ability to engage with new ideas.

In the realm of language, this personalization has profound implications. The algorithm does not just select content based on past behavior—it also shapes language by promoting certain words, phrases, and trends that are more likely to gain traction. As a result, language becomes more standardized, following the viral trends dictated by the algorithm. This phenomenon is what Aleksic refers to as the “algorithmic grammar,” a set of linguistic rules shaped by the need to go viral. These rules dictate not just the words we use, but also the tone, format, and style of our communication.

For instance, the use of catchy catchphrases, memes, and viral trends has become commonplace, as creators know that these elements are more likely to be favored by the algorithm.

The chapter also addresses the impact of algorithmic personalization on mental health. Aleksic notes that the more personalized our experience becomes, the more we may feel trapped by it. As we are continuously fed content that aligns with our preferences, we may lose sight of the broader world around us.

The algorithm doesn’t just personalize our content—it limits our exposure to ideas that challenge or provoke us. This can lead to a narrowing of perspective and a form of digital self-isolation, where users are only exposed to content that feels familiar and comfortable. Aleksic discusses how this can contribute to increased anxiety, particularly as individuals begin to see their lives through the lens of the algorithm.

They start to wonder whether their preferences are truly their own or if they are simply the result of constant algorithmic manipulation.

The chapter further explores how the algorithm’s “knowledge” of us is not based on an understanding of our true selves, but rather on data. Algorithms analyze the interactions we have with content—likes, shares, comments—but they have no real understanding of our internal lives. This creates a false sense of connection between users and the algorithm, leading people to anthropomorphize the algorithm and believe it understands them in a deeper, more personal way than it actually does.

Aleksic wraps up the chapter by exploring the implications of this algorithmic personalization for linguistic diversity.

As algorithms prioritize content that fits a particular mold, linguistic diversity is increasingly sidelined. In a world where words, phrases, and memes are constantly recycled and repackaged to fit the algorithm’s needs, unique forms of expression are lost. The pressure to create content that performs well in front of the algorithm leads to the rise of “safe” language—language that avoids controversy and adheres to what the algorithm perceives as socially acceptable.

This makes it harder for users to express themselves authentically or creatively, as they are constantly playing by the algorithm’s rules.

Ultimately, Aleksic argues that while the algorithm seems to “know” us in a personalized way, this knowledge is limited and ultimately reductive. The algorithm shapes not just what we see, but how we see and communicate with the world. In doing so, it molds language to fit its needs, creating a uniformity of expression that stifles individuality and creativity.

7. Wordpilled Slangmaxxing

In this chapter, Aleksic explores the explosion of new slang terms on social media, particularly within younger generations, and how these terms evolve and spread rapidly. The concept of “wordpilled slangmaxxing” is at the heart of the chapter, describing the process where slang terms are taken to their extreme, amplified, and recycled across platforms, becoming increasingly refined in their function.

The chapter touches on how the internet has transformed the way new slang emerges, how it spreads, and the specific role that algorithms play in amplifying this language.

“Wordpilled” refers to the way in which certain slang terms become concentrated or “pilled,” much like internet memes or viral trends.

These terms become heavily distilled and intensified as they circulate, with their meanings expanding and contracting based on the context they are used in. The idea of “slangmaxxing” refers to the process of maximizing or exaggerating the potential of these words. As slang evolves, it becomes more extreme and more codified within digital communities, growing beyond simple words to represent entire cultural ideologies or behaviors.

Aleksic uses specific examples to illustrate this concept, showing how terms like “rizz” (referring to charm or charisma) and “gyat” (a shorthand for “goddess you are the one”) begin as casual expressions but gain more intense meanings as they spread through social media.

They are “maxed out” by content creators who amplify the term’s usage, making it more pervasive. What was once a small, niche reference becomes a massive viral term, used by thousands, and then reinterpreted by various online subcultures. This pattern is central to the new form of linguistic creativity that social media platforms allow and promote. The more a word or phrase gets used, the more it mutates, each time recharged by the algorithm.

Aleksic explores how platforms like TikTok and Instagram serve as accelerators for these slang terms, emphasizing how algorithms fuel the spread of new words. The algorithm curates content based on the user’s preferences, which means that once a word or phrase starts to gain traction, it’s more likely to show up on a user’s feed.

This creates a feedback loop: the more people use the word, the more it spreads, and the more the algorithm promotes it. As a result, words can go from niche memes to mainstream slang in a very short period of time.

One interesting point Aleksic makes is the role of the algorithm in shaping the adoption of slang. Unlike traditional forms of language transmission, where words spread slowly across regions and communities, internet slang is often shaped by the algorithm’s bias toward content that is engaging, humorous, or attention-grabbing. The algorithm promotes content that fits these parameters, which often means that only the most extreme or hyperbolic slang terms make it to the forefront of digital culture.

Additionally, Aleksic discusses how the nature of wordpilled slangmaxxing is influenced by the desire for inclusion in online communities. New slang terms act as a linguistic marker, signaling that a person is in the know, that they are part of the in-group. Much like how a specific accent or dialect might signal cultural belonging in the real world, using the right slang online signals that someone is plugged into the current trends.

Words become a shorthand for shared cultural experiences and inside jokes, connecting people who use them and providing them with a sense of identity within a larger online community.

However, Aleksic also critiques the tendency for slang to become overused or commodified, where the constant amplification of certain terms leads to their eventual dilution. Words like “rizz” and “gyat,” which start with a specific cultural meaning, can lose their original context as they are appropriated by mainstream audiences. This process reflects a broader phenomenon in which niche internet language is co-opted by larger, more commercial forces.

As these terms become more mainstream, they are stripped of the subcultural edge they once held, becoming just another part of the digital vernacular.

At the heart of the chapter is the tension between linguistic innovation and the commodification of language. While the internet allows for greater creativity and linguistic experimentation, it also accelerates the commercialization of these terms, transforming them from markers of cultural identity into marketable tools. The role of algorithms in amplifying these words only exacerbates this process, turning slang into a commodity that can be packaged and sold.

Aleksic wraps up the chapter by reflecting on how wordpilled slangmaxxing is part of a larger trend of linguistic innovation driven by digital platforms and algorithms.

While the internet has undoubtedly democratized language, allowing for the rapid spread of new words and phrases, it has also created a linguistic environment where the forces of commerce and viral culture can dilute the very creativity they originally fostered.

8. It’s Giving Appropriation

In this chapter, Aleksic addresses a controversial and often complex issue: the intersection of language, culture, and identity on social media, specifically focusing on the phenomenon of cultural appropriation in language. The chapter examines how internet slang and phrases, especially those popularized by marginalized groups, can be appropriated by mainstream users in a way that strips them of their original meaning and significance.

The phrase “It’s giving” serves as a vehicle to explore these dynamics, as it is a term that has been widely used to express an evaluation of something—often by mimicking the cadence and tone of Black or queer vernacular.

Aleksic begins by explaining the concept of cultural appropriation, which refers to the act of taking or borrowing elements of a marginalized culture without understanding or respecting their historical context or significance.

While cultural appropriation has often been discussed in terms of fashion, music, and art, Aleksic argues that it is equally relevant when it comes to language. On social media platforms like TikTok, phrases and terms originating in Black, Latinx, or queer communities are frequently co-opted by mainstream users. Once these terms gain traction and are adopted by a wider audience, they lose their original context and often become disconnected from the cultural experiences that birthed them.

One of the central examples Aleksic uses is the phrase “It’s giving,” which emerged in Black and queer communities to describe an aesthetic or vibe. For instance, when someone says “It’s giving rich auntie energy,” they are describing a vibe or attitude that evokes a certain persona—often one that is confident, fashionable, and financially independent. This phrase, rooted in the vernacular of Black and queer communities, became widely popular on platforms like TikTok, where users began to apply it to a range of contexts, from fashion to entertainment to personality traits.

As “It’s giving” became more mainstream, it lost much of the cultural weight it initially carried. Aleksic argues that this shift is a form of linguistic appropriation.

When a phrase or slang term is adopted by those outside the culture it originates from, especially when it is used without acknowledgment of its roots, it becomes disconnected from the very experiences that shaped it. The term is no longer used to reflect a shared cultural identity but is instead commodified, often watered down to fit the mainstream’s consumption.

Aleksic highlights the importance of understanding the socio-political context behind certain words and phrases. The appropriation of language often results in the erasure of the struggles and histories that shape the meaning of those words. For example, when mainstream users, especially non-Black individuals, use phrases like “It’s giving” without recognizing its origins, they participate in a broader pattern of cultural exploitation that appropriates the labor of marginalized communities while simultaneously stripping away their significance.

The chapter also touches on the role of social media in accelerating this process. Algorithms play a significant part in the spread of cultural appropriation by promoting content that adheres to viral trends, regardless of the cultural sensitivity behind them. Once a phrase like “It’s giving” goes viral, it spreads across platforms and is used by millions without any understanding of its cultural background. This makes it difficult for marginalized communities to retain ownership over the language that is so closely tied to their identity and experiences.

Moreover, Aleksic points out that cultural appropriation in language is not just a one-way street. While marginalized groups may lose ownership over the language they created, they are often penalized for using the same words in certain contexts. For example, when Black creators use Black vernacular on platforms like TikTok, they often face content suppression or censorship. Meanwhile, when non-Black creators use the same words, they may face little to no consequences. This uneven power dynamic reinforces the larger societal structures of inequality, where marginalized voices are silenced while their cultural outputs are commodified and consumed by the dominant culture.

In discussing this issue, Aleksic emphasizes the need for greater cultural awareness and respect when it comes to language. Rather than simply adopting terms and phrases because they are “trendy,” users need to be mindful of the cultural origins of the language they use. He encourages a more responsible and respectful approach to language, one that acknowledges the significance of the words we use and the power dynamics at play in their appropriation.

Ultimately, Aleksic argues that linguistic appropriation is not just a matter of individual behavior; it is a systemic issue that reflects broader patterns of cultural exploitation and erasure. The algorithmic systems that govern social media platforms play a critical role in perpetuating these dynamics, as they prioritize viral content over cultural context and significance.

To counteract this, Aleksic calls for greater recognition of the cultural roots of language and for a more ethical, respectful approach to language use on social media.

Some similar phrases

“It’s giving ___” – This phrase is a popular format on social media used to describe the vibe or feeling that something or someone is emitting. For example, “It’s giving rich auntie energy” implies that something evokes the persona or vibe of a wealthy, independent, and sophisticated aunt. This expression highlights how language can shift based on societal trends and digital memes .
“It’s the ___ for me” – Another viral phrase often used to emphasize a specific trait or characteristic. It’s used to call attention to something that stands out, such as “It’s the nails for me,” meaning the nails are the most impressive or notable feature .
“The way you ___” – This is a construction often used on platforms like TikTok to express admiration, sarcasm, or a reaction to someone’s behavior. For example, “The way you danced last night!” expresses astonishment or approval based on someone’s actions .
“Not you doing ___” – This phrase is typically used to express surprise or disbelief in a playful or mocking way. It’s often used in a joking tone to draw attention to someone’s actions that are unexpected or overly dramatic .

These phrases are part of a larger trend of social media-driven language evolution, where catchy and relatable phrases are amplified and widely adopted due to their attention-grabbing nature.

9. What Are We Wearing This Summer?

In this chapter, Aleksic shifts his focus to the intersection of fashion, identity, and language, examining how social media platforms have reshaped the way we talk about style and personal expression. The chapter’s title, “What Are We Wearing This Summer?” refers not only to seasonal fashion trends but also to the way in which these trends are presented and discussed online.

Aleksic explores how platforms like TikTok and Instagram have created an environment where personal style is not just a form of self-expression but also a currency in the digital economy.

Aleksic begins by discussing the concept of “aesthetic curation,” which refers to how users on social media craft and present a specific image or identity for themselves, often through the lens of fashion. Social media platforms, particularly Instagram and TikTok, allow users to curate their lives in highly polished and visually appealing ways. The rise of influencers and content creators has made fashion and style a significant part of online identity.

On these platforms, users are constantly asking themselves: “What am I wearing today? How can I present myself to my audience in a way that gets noticed?” Fashion, therefore, becomes more than just clothing—it becomes a way to signal belonging, status, and influence.

Aleksic notes that the pressure to constantly update one’s aesthetic on social media can lead to an endless cycle of trend-chasing.

Fashion trends, particularly those popularized by influencers, spread rapidly across platforms and often become commodified within days or weeks. The speed at which these trends change is a direct result of the algorithmic nature of social media. The more a specific trend is engaged with—through likes, shares, comments, and views—the more the algorithm promotes it, further amplifying its reach.

This creates an environment where trends are fleeting, and users are continuously trying to keep up with the next “big thing.”

The chapter also examines how social media influencers shape the fashion discourse by creating content that centers around specific brands, aesthetics, or looks. Aleksic highlights how influencers often act as both trendsetters and consumers, promoting certain styles while simultaneously capitalizing on them for financial gain.

This dual role has led to a situation where personal style is heavily influenced by external pressures—the desire to be seen, to gain followers, and to be part of the larger cultural conversation. Influencers have become walking advertisements for brands, and their personal style is often a reflection of what is currently trending in the market.

One of the key insights of the chapter is the way that algorithms have amplified the “homogenization” of fashion. With the rise of viral fashion trends, many people find themselves wearing the same items, styling themselves in the same ways, and using the same language to describe their fashion choices.

The chapter refers to this as a “flattening” of style, where individuality is sacrificed in favor of what is popular or algorithmically favored. This is particularly evident in the way that certain aesthetics, such as the “soft girl” or “dark academia” look, become viral on TikTok and Instagram, only to be overrun by mass adoption and commercialization.

The chapter also explores how fashion trends on social media often play on stereotypes, gender norms, and cultural appropriation.

For instance, the rise of “cottagecore” as a fashion aesthetic was tied to a romanticized vision of rural life, which often overlooked the cultural significance and history of the styles being appropriated. Aleksic discusses how the algorithm-driven nature of social media makes it easier for trends to spread without much thought about their cultural context or the implications of their widespread adoption.

This cultural commodification of fashion can lead to the erasure of the original meanings behind certain styles, much like how slang terms are appropriated and disconnected from their roots.

Aleksic’s critical reflection on the commercialization of online aesthetics is tied to his larger argument about the impact of algorithms on language and culture. Fashion, like language, becomes a tool for social media platforms to keep users engaged and generating content. The more people engage with a particular trend, the more the algorithm promotes it, creating a cycle of endless consumption and re-consumption. In the process, style becomes less about personal identity and more about following a prescribed set of rules that the algorithm rewards.

The chapter concludes by emphasizing the need for greater awareness of the forces that shape our understanding of fashion and identity online. As influencers and everyday users alike participate in this cycle of aesthetic consumption, they must ask themselves whether they are truly expressing their individuality or simply conforming to an algorithmic vision of what is “in” at the moment.

The pressure to always look and act a certain way online, especially in relation to fashion, underscores the power of the algorithm in dictating not just language and behavior, but also personal style and self-expression.

10. OK Boomer

In this chapter, Aleksic examines the generational divide in language, focusing on the use of the phrase “OK Boomer” as a cultural marker and a symbol of the tension between younger and older generations, particularly in the context of social media. The phrase “OK Boomer,” which originated as a meme, quickly became a widespread rallying cry for Gen Z and Millennials in their interactions with older generations, often in response to criticisms of youth culture or social issues that younger generations care about.

Aleksic begins by explaining the origins of “OK Boomer,” noting that the term was initially popularized on platforms like TikTok, where younger users would use it as a humorous yet pointed response to perceived outdated or condescending viewpoints. The phrase gained traction as a way to dismiss the opinions of older individuals, particularly Baby Boomers, whose views were seen as disconnected from the realities of the modern world.

It was used to express frustration with older generations who seemed out of touch with issues like climate change, technology, and social justice movements.

At its core, “OK Boomer” serves as a linguistic tool for reclaiming agency in a world where older generations have historically held more power. Aleksic argues that the phrase reflects a larger cultural shift, in which younger generations are challenging traditional power structures and asserting their own voices. The meme itself functions as a form of resistance, allowing younger individuals to push back against the authority of older generations through humor and ridicule.

This resistance is amplified by the speed and reach of social media, where memes like “OK Boomer” can go viral almost overnight and become part of the larger cultural conversation.

One of the key points Aleksic makes in this chapter is that “OK Boomer” is more than just a meme; it is a reflection of the changing dynamics of power in society. The phrase highlights the generational divide between those who grew up in a pre-internet world and those who have never known a world without the internet. Aleksic notes that the internet, and particularly social media, has empowered younger generations to create their own cultural norms and language, which are often at odds with the more traditional values of older generations.

“OK Boomer” becomes a shorthand for this divide—a way for younger individuals to express frustration with a system they feel has been dominated by older individuals for too long.

Aleksic also discusses how the meme itself has evolved. What started as a humorous retort has now become a symbol of political and social commentary. As the phrase gained popularity, it began to take on new meanings and applications.

For some, it became a tool for mocking older generations, but for others, it became a way to critique the larger social, political, and economic systems that have been shaped by Boomers. The phrase, in this sense, functions as a critique of the status quo, a way to point out the flaws in systems that have been in place for decades. This transformation from a meme to a cultural critique underscores how language on social media is not just about individual expression, but also about collective identity and resistance.

However, Aleksic also explores the complexities of the “OK Boomer” phenomenon. While it is often used as a playful or sarcastic comment, it can also be seen as divisive. Older generations, particularly Baby Boomers, have criticized the use of the phrase as disrespectful and dismissive. Some have argued that it is a form of ageism, an attack on older people simply because of their age.

In this way, “OK Boomer” becomes a symbol not only of generational resistance but also of the broader cultural tensions that exist around issues of age, power, and social change. The phrase is, in a sense, a microcosm of the larger debates about generational conflict and the changing nature of societal power.

Aleksic concludes the chapter by reflecting on the broader implications of generational divides in language. He argues that while “OK Boomer” is a prime example of how social media can facilitate rapid linguistic innovation and the spread of memes, it also illustrates how language can be a tool for social and political resistance. The meme highlights the ways in which language evolves in response to social dynamics, particularly in the context of power and authority.

By challenging the linguistic and cultural norms of older generations, younger users are using language as a form of empowerment—reclaiming the narrative and reshaping the future of communication in the process.

11. Are We Cooked?

In the final chapter of Algospeak, Aleksic reflects on the broader implications of the linguistic shifts driven by social media and algorithms, asking whether the rapid evolution of language in the digital age signals the end of meaningful, authentic communication. The chapter explores the consequences of living in a world where algorithms dictate much of our online interactions and how the linguistic trends that emerge as a result of this algorithmic influence could affect future generations.

Aleksic begins by discussing the phrase “Are we cooked?”—a slang term that emerged as a humorous, existential reflection on the state of modern society. It’s used to express a sense of impending doom or the feeling that society, or the individual, is beyond saving.

The phrase, much like “OK Boomer” in the previous chapter, reflects a generational commentary, but it’s framed with a sense of humor and nihilism. In the context of the chapter, “Are we cooked?” becomes a metaphor for the way that language itself is being altered and commodified by algorithms.

The central argument of this chapter revolves around the notion that the proliferation of algorithmically driven language—what Aleksic refers to as “algospeak”—is leading to a future where our words and expressions are increasingly shaped by invisible, impersonal forces. The term “cooked” in this context reflects Aleksic’s concern that, like the food being cooked by a chef, language is being “prepared” and “served” according to the tastes of algorithms, not the organic needs of human expression.

In other words, the more we interact with platforms that prioritize viral content and engagement metrics, the more we risk losing the richness and diversity of language that comes from free, unconstrained communication.

Aleksic delves deeper into the role of algorithms in this process, pointing out that these systems are designed to maximize user engagement by promoting content that fits within certain parameters: content that is catchy, visually appealing, or in line with popular trends. As users, we are often complicit in this process, tailoring our language and behavior to fit what will resonate with the algorithm.

This, according to Aleksic, has profound implications for how we communicate. Language, once a dynamic and highly individualized expression of thought, has become a tool for gaining attention and maximizing social media engagement.

The chapter also explores the “cultural flattening” that results from this algorithmic shaping of language. As more people adopt the same phrases, memes, and trends to get noticed, individuality in language becomes less prominent. The internet, which was once a space for diverse voices and unique forms of expression, now tends to prioritize language that fits within the algorithmic mold. In this sense, the rise of algospeak signals a shift away from authentic, individual communication toward a more homogenized form of expression that is optimized for virality rather than meaningful interaction.

Aleksic addresses the tension between the democratizing potential of social media and the reality of how algorithms shape and constrain our language. While social media platforms have allowed for unprecedented access to global conversations and the amplification of marginalized voices, the algorithmic systems in place often serve to mute these voices in favor of more mainstream content.

For example, marginalized groups that use slang or language that doesn’t conform to mainstream standards may find their content suppressed or censored by platforms that prioritize engagement over authenticity. In this way, algorithms exacerbate existing inequalities, making it harder for non-mainstream voices to be heard.

In conclusion, Aleksic contemplates whether, in our pursuit of viral success and online validation, we have lost something essential in our language and communication. He asks whether the current trend toward linguistic commodification, driven by algorithms, is indicative of a future where meaningful communication is sacrificed for the sake of attention.

The question “Are we cooked?” thus serves as both a literal and figurative reflection on the state of language in the age of social media. Are we, as a society, losing the ability to communicate authentically and meaningfully in favor of language that is simply designed to perform well on the algorithm?

The chapter closes with a call to action for readers to think critically about the language they use online and the forces that shape it. While the algorithm has a powerful influence on how we communicate, Aleksic suggests that we still have the agency to reclaim our language and resist the pressures of algorithmic normalization. By being more mindful of how we use language and the ways in which we interact with social media, we can retain the richness and diversity of communication that algorithms often seek to suppress.

Some algospeak words

“Unalive” – A term used to avoid the word “suicide” or “kill”.
“Seggs” – A playful and euphemistic form of “sex,” widely used on platforms like TikTok.
“Kermit sewerslide” – A euphemism for “commit suicide,” with a reference to the Muppets.
“Zesty” – Used to refer to “gay,” circumventing platform restrictions on LGBTQ+ content.
“Corn” – A euphemism for “porn,” bypassing censorship.
“Grape” emoji (🍇) – Used as a replacement for “rape”.
“Ninja” emoji (🦸) – A stand-in for the n-word, using visual abstraction.
“Le$bian” – A playful and altered form of “lesbian” to bypass filters.
“T!ts” – A common, less explicit variation of the word “tits”.
“P3nis” – Used in place of “penis”.
“F!ght” – A modified version of “fight” used to bypass content moderation.
“F!ck” – The classic word “fuck” with phonetic alterations.
“A$$” – A modified version of “ass”.
“B!tch” – A commonly modified version of “bitch”.
“Voldemorting” – A term describing avoiding taboo words by using indirect language, such as referring to controversial topics without directly naming them.
“Mtherfcker” – A censored variation of “motherfucker”.
“Sh!t” – A variation of “shit”.
“L0ser” – A euphemistic variation of “loser”.
“L!ve” – Altered form of “live”.
“B!tch – Used instead of “bitch”.
“B00b” – A less explicit version of “boob”.
“Fk”** – A variation of the word “fuck” using asterisks to evade algorithmic Here are additional algospeak terms based on the book Algospeak: How Social Media Is Transforming the Future of Language by Adam Aleksic, expanding on the list:
“Fk”** – A variation of the word “fuck” using asterisks to evade algorithmic censorship.
“G!rl” – A reimagined form of “girl” to avoid detection.
“W0rld” – Substitution of “world” with a “0” to bypass content filters.
“Tr*mp” – Altered spelling to avoid suppression of political content related to Donald Trump.
“F*ckboi” – A variation of “fuckboy,” used to avoid bans related to explicit language.
“B1tch” – A variation of “bitch,” used commonly on social platforms to bypass censorship.
“M@therf*cker” – Substituting symbols to replace offensive words like “motherfucker”.
“D!ck” – A reworked version of the word “dick” used to dodge platform restrictions.
“C0ck” – A variation of “cock,” altered to avoid moderation tools.
“P*y”** – An obfuscated spelling of “pussy”.
“B1tchez” – A creative spelling variation of “bitches” to bypass algorithms.
“Sh!t” – A substitution for “shit,” frequently used in social media to avoid detection.
“D!ckhead” – A variation of “dickhead” used to evade algorithmic filtering.
“Fukcing” – A commonly used misspelling of “fucking”.
“C*nt” – A censored form of a highly offensive term.
“Bh”** – A shorter, obfuscated version of “bitch”.
“M!lfs” – A variation of “milfs,” often used in slang or adult content.
“S@xy” – An altered version of “sexy” to circumvent restrictions on adult content.
“B0y” – A variation of “boy” used to avoid censorship.
“Sh!tpost” – A form of posting that uses “shit” as part of its slang, altered to evade bans.
“Cl!t” – A modified spelling of “clit” used to bypass filters for explicit content.
“J3rk” – A less explicit version of “jerk” to avoid algorithms detecting rude language.
“P!ssed” – A censored variation of “pissed”.
“R3t@rd” – A misspelling of “retard,” frequently used in a derogatory context to avoid suppression.
“B4by” – A playful variation of “baby”.
“L3gends” – A reworking of “legends” to bypass content moderation.
“G0ddamn” – A variation of “goddamn,” adjusted to avoid suppression.
“F@ke” – A substitution for “fake,” used in conversations around authenticity.
“T@p” – An altered version of “tap,” often used in meme and viral content.
“L0ve” – A variation of “love” to avoid certain filters in romantic contexts.
“D4rkside” – A playful alteration of “dark side” to avoid potential political context censorship.
“B@by” – An altered version of “baby” often used in informal or meme-based language.
“P00p” – A reworked form of “poop” to bypass filters for content related to bodily functions.
“C@lm” – A re-spelling of “calm” to avoid automated content moderation systems.
“T@lking” – A variation of “talking” often used in memes and informal speech.
“B00ty” – A euphemistic spelling of “booty” for adult content.
“C!rcle” – A variation of “circle” used in meme formats.
“H@ck” – A reworking of “hack” to bypass censorship of topics around hacking.
“P!racy” – A variation of “piracy” used to avoid algorithms censoring illegal content discussions.
“S@lm” – A phonetic alteration of “salmon,” often used in memes.
“Sh0rts” – A re-spelling of “shorts” to avoid YouTube-specific algorithmic issues.
“Dr@gon” – A modified version of “dragon” used to evade content filtering.
“R@ts” – A reworked form of “rats,” used as part of slang or meme culture.
“S3llout” – An altered form of “sellout,” often used in criticisms of people perceived as compromising.
“M@ge” – A creative modification of “mage,” often used in gaming contexts.
“F@ce” – A modified version of “face” in slang and meme usage.
“M!shap” – A variation of “mishap,” used humorously in viral videos.
“G!t” – A playful variation of “git,” used as an insult in some online communities.
“P@ir” – A reworked spelling of “pair,” used in general conversations and memes.
“V!be” – A re-spelling of “vibe” used to describe moods or feelings.
“D!s” – A reworked form of “dis” to avoid automated content moderation.
“P!p3” – A stylized version of “pipe,” often used in gaming or tech-related slang.
“Fl!p” – A variation of “flip,” frequently used in meme culture.
“R3spond” – A variant of “respond,” commonly used in the context of social media interaction.
“B!tchass” – A slang term, reworked to avoid algorithmic filtering.
“Dr!ve” – A re-spelling of “drive” used in meme-based communication.
“L0vebug” – A playful variant of “lovebug,” used informally.
“S0cial” – A common reworking of “social” in memes or viral posts.
“Tr0ll” – A playful re-spelling of “troll,” widely used across platforms.
“C00l” – A commonly modified version of “cool” used in internet slang.
“B@lls” – A reworked form of “balls,” often in informal speech.
“T0x1c” – A modified version of “toxic,” frequently used in online discussions.
“W!sh” – A modification of “wish” often seen in online posts.
“Fl@sh” – A reworking of “flash” used in video gaming.
“D@rk” – A censored form of “dark” used in memes.
“B@byface” – A modified form of “babyface” used in slang.
“R3act” – A reworked form of “react” used in meme contexts.
“Gr@p3” – A variation of “grape,” used humorously in memes.
“R0ck” – A variation of “rock,” typically used in slang and gaming contexts.
“T1me” – A reworking of “time” used in various meme contexts.
“T1nker” – A playful rewording of “tinker,” used in tech discussions.
“Ch@ck” – A reworked version of “chick,” used in casual conversations.
“S!ck” – A stylized version of “sick,” often used in gaming communities.
“R3f” – A common re-spelling of “ref,” short for reference.
“H@ppy” – A modified spelling of “happy” in social media posts.
“M@ss” – A creative variation of “mass,” used in meme-based language.
“P@t” – A variation of “pat” used informally.
“K!ck” – A reworked version of “kick,” used in gaming slang.
“V!pe” – A variant of “vape,” used in online discussions.
“C@r” – A modified version of “car” used in memes.

These examples reflect the ongoing linguistic creativity driven by the algorithmic nature of social media platforms, where users constantly develop new terms to bypass content moderation tools.

Critical Analysis

The book offers a compelling argument about the impact of algorithms on modern communication. Aleksic convincingly demonstrates that the need to conform to algorithmic rules is reshaping not only what we say but also how we say it. The rapid spread of words like “unalive” highlights how social media can accelerate language change in ways that traditional media could not.

However, while the book does an excellent job of detailing the phenomenon of algospeak, one might argue that it could further explore the negative implications of this linguistic shift. As language becomes more commodified and designed to fit algorithmic patterns, there is a risk that it loses its richness and subtlety. The creativity and spontaneity that were once hallmarks of language seem constrained by the limits of algorithmic moderation.

While the book addresses this issue, a deeper investigation into the social consequences of these changes would provide a more comprehensive picture of the future of language.

In terms of writing style, Aleksic excels in making complex linguistic concepts accessible to a broad audience. He blends scholarly insight with humor and personal anecdotes, which helps make the book engaging and relatable. His clear explanations ensure that even readers without a background in linguistics can understand the intricacies of algospeak.

Strengths and Weaknesses

Algospeak shines in its ability to explain the rise of new linguistic practices in a digital world, providing readers with both a theoretical framework and real-world examples. Aleksic’s exploration of how social media shapes language is both timely and thought-provoking, making the book a valuable contribution to discussions on digital communication.

However, some readers may find the focus on social media platforms like TikTok and Instagram to be limiting. While these platforms are certainly influential, the broader societal implications of algospeak extend beyond social media. A more global perspective, looking at how these trends intersect with different cultures and languages, could enrich the book’s argument.

Reception/Criticism/Influence

Algospeak has been well-received for its insightful analysis and accessible writing style. Critics have praised Aleksic for tackling a complex and rapidly evolving subject with both academic rigor and personal flair. The book’s exploration of how social media influences language has sparked important conversations about the power of algorithms in shaping not just what we see online but also how we communicate with one another.

Quotations: Aleksic’s book is filled with thought-provoking quotes that encapsulate the core ideas of algospeak. For example, he writes:

“Unalive is the tip of a colossal iceberg. Beneath the icy water, there is a hulking mass of creative techniques, trends, memes, identities, echo chambers, and new ways to commoditize language that only could have existed in the new algorithmic context.”

This passage underscores the vast and often hidden impact of algorithms on language, suggesting that we are only beginning to understand the full extent of these changes.

Comparison with Similar Works

Aleksic’s work stands out in the field of linguistic studies because of its specific focus on the intersection of language and social media algorithms. While books like Because Internet by Gretchen McCulloch and Language and the Internet by David Crystal discuss internet-driven linguistic changes, Algospeak takes a more focused approach by zeroing in on the role of algorithms in shaping how we speak online.

Conclusion

In conclusion, Algospeak offers an engaging and insightful look at how social media algorithms are reshaping language. Aleksic effectively demonstrates how new words and linguistic trends emerge in response to content moderation systems, and how these changes are shaping online and offline communication.

While the book excels in explaining the rise of algospeak, a deeper examination of the social implications would make it an even more comprehensive study. This book is a must-read for anyone interested in the future of language in the digital age, particularly those in the fields of linguistics, communication, and social media studies.

Table of Contents