In Chapter 1, we set the scene by examining the dynamics of online offensive language. We examine offensive language across a spectrum, ranging from non-polite expressions to grossly offensive (potentially illegal) speech. We also explore the conceptual links between offensive language and related notions such as impoliteness, hate speech and language aggression. Importantly, this chapter focuses on why understanding offensive language is, above all, a concern best addressed by linguists. To achieve this, we discuss the similarities and differences between grossly offensive and (im)polite language. We specifically focus on pragmatic concepts such as locution, illocution and perlocution to explain how they operate at both ends of the spectrum. Finally, we address the challenges of detecting offensive language in computational approaches to combating online hate, emphasising the vital role of linguistic contributions.

In Chapter 4, we focus on the discourse of offensive language. Drawing on Foucault’s concept of discourse, we examine recurring patterns, structures and meanings that convey offensive implications in our corpus. We identify linguistic categories that are overused or underused in comparison to our reference corpus. The key features identified reveal that offensive language is often personal, opinionated and judgemental, and includes intrusive and critical expressions. In this chapter, we also explore the implications of these linguistic tendencies and their role in shaping the discourse of offence. Chapter 4 further demonstrates that the overuse of symbols, such as asterisks, serves to obscure offensive language, indicating both self-censorship and attempts to potentially normalise such language.

Chapter 3 explains our research methods, data collection and ethics. In this chapter, we focus on how we have addressed the typical challenges of interpreter bias in studying online offensive language. To mitigate these issues, we ground our study in naturally occurring data flagged as offensive by the targets themselves. We also introduce the reader to the world of social media content creators and discuss who the targets in our study are, and provide some demographic information about them. We discuss the use of Sketch Engine as a tool to address our primary objective of exploring the formal, lexical, semantic and discursive strategies involved in the construction of offensive language. We also discuss Wmatrix5, a corpus tool used to explore the semantic dimensions of offensive language. In addition, we explain how quantitative analysis was combined with thematic and linguistic-pragmatic approaches to examine how frequency and context shape offensive meanings. Chapter 3 further outlines our ethical considerations, including the responsible handling of data and the protection of participant anonymity, throughout the research process.

In Chapter 7 we focus on the shift from direct, explicit insults to the more indirect and implicit ones. We argue that explicitness exists on a continuum, making it difficult to draw a clear boundary between where implicitness ends and explicitness begins. We categorise our data into more explicit and less explicit language. Less explicit language includes offensive meanings which are expressed through hinting, insinuating, implying and suggesting. We compare our corpus of explicit language with a less explicit one to explore the differences between the two. Our analysis reveals that themes such as gender, racial and age biases are commonly used in the less explicit corpus. These biases are perpetuated through seemingly polite language, rhetorical questions and comments that indirectly and subtly attack the target’s identity. We examine how implicatures arise from specific word choices. We also discuss weak and strong implicatures, and how they can be used in a way that leaves room for potential deniability. Along the way, we also focus on what we call unmarked offensive implicatures.

Chapter 6 focuses on patterns of offensive language with a particular focus on specific words and multi-word units that characterise the discourse of offensive language. The chapter aims to enhance the classification of offensive words, refine models of offensive language, and deepen our understanding through keyword analysis. The findings reveal a wide range of explicit and taboo words, including racial slurs and derogatory terms, alongside emphatic markers, which intensify emotional statements. In our discussion of explicit language, we will critically examine the role of context in interpreting offensive language. We discuss the explicitly offensive language within the concept of ‘insults’, dividing them into two primary types: hard and soft. Although both types serve to denigrate, they differ in linguistic intensity and explicitness.

This introduction explores the growing presence of offensive language on social media platforms like TikTok, YouTube and Instagram, where anonymity often encourages more aggressive behaviour. It discusses the difficulty in distinguishing between what is ‘merely offensive’ and what crosses into illegal or grossly offensive territory, highlighting how this is a complex issue spanning multiple disciplines. The chapter highlights the importance of linguistic insights in understanding offensive language, especially given the limitations of automatic detection systems and the inherently subjective nature of offence. It also provides an overview of the chapters that follow.

Chapter 2 focuses on offensive language, positioned at the midpoint in the spectrum discussed in the first chapter. We situate offence and the acts of causing and taking offence in the theory of (im)politeness. The chapter reviews the development of (im)politeness theory through three waves and situates the current book within this theoretical progression. In this chapter, building on the previous literature, we also propose a model of offence which distinguishes between legal and moral (interactional) transgressions. To discuss the legal side, we focus on UK law, examining the challenges surrounding the concept of grossly offensive through a discussion of several high-profile cases. We also focus on moral-order transgressions which occur when interactional norms are breached. The chapter also argues that taking offence, whether face-to-face or online, could be a strategic social action used to, among other things, assert boundaries or influence social norms. As we argue, online offence may function as a tool for collective action, for raising awareness and for promoting social change.

This chapter summarises the key findings of the book on offensive language online, with particular emphasis on the perspectives of those targeted. It outlines the book’s multi-layered approach, which integrates corpus linguistics, discourse analysis and pragmatics. The chapter also explores future directions for research, including platform-specific variations, sociolinguistic changes and the value of interdisciplinary methodologies for understanding and addressing offensive language in digital spaces.

Chapter 5 focuses on the semantic domains of offensive language. The analysis of the semantic domains further confirms that offensive language is opinionated, intrusive and judgemental. Using the Wmatrix5 tools, we identify key areas of meaning that allow offenders to express, for example, criticism and negativity. Our analysis reveals a significant overrepresentation of terms related to, for example, dislike, foolishness and negative judgements about appearance, which overall point to a tendency towards personal attacks. By focusing on these domains, we aim to address further gaps in offensive language research, and predict alternative expressions of similar meanings.