I was interviewed recently by BBC World for a program on English and globalization. Here is the podcast, and my “mind-bending” remarks start around minute 12.
I was interviewed recently by BBC World for a program on English and globalization. Here is the podcast, and my “mind-bending” remarks start around minute 12.
Academics are travelers, and I have traveled a lot. There were, and are, good reasons for that: there is a host of crucial academic activities that involve traveling, and the most prominent of such events are conferences big and small, academic exchanges and visiting fellowships enabling close research collaboration with colleagues elsewhere. Since I considered this both a duty and a joy in my professional life, I had no hesitations booking flights to other continents where I would talk for about 45 minutes in front of a group of about 30 graduate students, and to do this at least five or six times per year.
The absurdity of such efforts took a while to sink in. Accumulated jetlags resulted in serious health issues, and a stern-faced cardiologist took time to explain to me in detail the disastrous effects of intensive and continuous air traveling on my body over an extended…
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Point of departure
The point of departure for what follows is this observation. Since the beginning of the 21st century, we live our social, cultural, political and economic lives in an online-offline nexus, in which both ‘zones’ – the online and the offline – can no longer be separated and must be seen as fused into a bewildering range of new online-offline practices of social interaction, knowledge exchange, learning, community formation and identity work. The so-called ‘digital revolution’ has already happened, it has become ‘historical’ according to Florian Cramer (2014), and we have entered a ‘post-digital’ era in which big-tech innovation is matched by grassroots searches for agency, DIY media creation and hybrid media systems.
This has profoundly affected the flows of information in societies such as ours, and we need to get our heads around these new ways in addressing their outcomes: messages, meanings and the social configurations within which they circulate. This evidently includes political messages and meanings. Note that such messages and meanings are almost without exception mediatized (and thus mediated) messages and meanings, reaching their audiences due to the mediating impact of media systems. For most people, political discourse is indirectly accessed through the specter of the media they are exposed to.
One can reformulate this general observation. Digital infrastructures have become part of what is conventionally described as ‘social structure’ – the deep, generic and often invisible drivers behind actual social conduct – and such infrastructures now demand much more attention in research on messages and meanings (cf. Arnaut, Karrebaek & Spotti 2017). Concretely: not just the content should be central to discourse-analytic research, but systems of communication and the way in which they shape new sociolinguistic conditions for production, circulation and uptake of discourses, new resources, new actors and new relations between actors (Maly 2018). Post-digital environments are new sociolinguistic environments and discourse analysis cannot avoid attention to the sociolinguistic conditions affecting contemporary discourses.
The point of departure has been sketched. I shall now offer three connected reflections on the analysis of political discourse within these post-digital conditions.
Revisiting propaganda models
Propaganda models are linear models of political mass communication, in which the messages and meanings of powerful actors – politicians in this case – are passed on to ‘the public’ by mass media owned or operated by actors sharing the same interests as those articulated by the powerful actors. Mass media, in such models, act as an intensifying and expansive conduit for the interests of the powerful, and their monopoly in the public sphere ensures propaganda effects on ‘public opinion’.
Various versions of propaganda models (the most widely known one is Herman & Chomsky 1988) have been predominant in critical discussions of mass media and politics throughout the 20th century, and they informed much early and influential work in Critical Discourse Analysis as well (e.g. Fairclough 1989). These models are grounded in a modernist imagination of ‘the public’ (hence the scare quotes I put around this term) and the public sphere, in which ‘the public’ is usually seen as ‘the masses’. The latter are amorphous and inert – therefore vulnerable to propaganda – and coinciding with the statistical notion of ‘population’, which allowed it to be investigated by means of notions such as ‘public opinion’ and to be structured into averages, majorities and minorities. As a political actor, ‘the public’ stood in a responsive relationship to politicians and state institutions on the one hand, and mass media on the other.
These often implicitly held images have been pervasive in spite of the fact that most serious sociologists (from Simmel and Dewey to Habermas, Bourdieu and Giddens) would frequently warn against the fallacies of such amorphous and homogenizing views of ‘the public’ and ‘the public sphere’. And attempts such as those of Dewey and Habermas to make citizens less responsive and inert, and more proactive and influential in the political process, often got no further than proposals for more structured, well-informed, rational debate in ‘the public sphere’.
We now realize that this public sphere is profoundly fragmented. I suppose it always was fragmented, but the mainstream sociological imagination privileged artificial homogenization over actual fragmentation. In the online-offline nexus, we definitively must abandon this construct of a single and unified public sphere made up of ‘the masses’ and manipulated by the ‘mass media’. In the new hybrid media system in which old and new media constantly interact, algorithms do not target ‘the masses’, they target a multitude of highly specific audiences (‘micro-populations’ in the terms of Maly & Varis 2016) in what has become known as ‘micromarketing’ or ‘niche marketing’. ‘Mass’ effects – think of the Brexit referendum and the election of Donald Trump as US president – are achieved by establishing loose, temporal and unstable coalitions between such micro-audiences. ‘Mass’ media in the 20th century sense of the term (currently called ‘mainstream media’ or MSM) now also operate on the logic of micromarketing algorithms and in close synergy with online platforms and social media. They are no longer hegemonic in the ‘public sphere’ in the ways that led, e.g., Lipmann and Dewey to their reflections on the role of media in a democracy. And manufacturing consent in the way Herman and Chomsky understood it now demands intense and coordinated activity on far more and more diverse media platforms, operating in a fragmented field of media content production and circulation.
I’m afraid that the public sphere – a phrase that has been used a zillion times in social and political analysis – has become practically meaningless. And the propaganda models that were so predominant in public discourse analysis also need to be fundamentally revisited, because two of their key elements have been dislodged: mass media in the 20th century sense, and the public sphere in the modernist sense outlined above. They have been replaced by complex systems of communication aimed at micromarketing.
As for rational debate within this public sphere – the duty of democratic citizens and the task of their mass media in the eyes of generations of social and political theorists – the same conclusion seems compelling. If propaganda models need to be replaced by micromarketing models of public communication, the features of marketing need to be taken serious. I shall now recite the commonplace features of such marketing practices: they are irrational, aestheticized and emotive. But let’s note with some emphasis that these features were already attributed to Nazi politics by Walter Benjamin in 1936. It is safe to assume that aesthetics has never been absent from the political sphere, and that it may even be one of its key features in retrospect. Let us equally note that these features, while not rational, are epistemic nonetheless: they organize modes of knowledge construction, of argumentation and persuasion just as effectively as rational, fact-based practices (cf. Blommaert 2018a; Prochazka & Blommaert 2019). Meaning is as much an effect of discursive shape as it is of discursive content, as Dell Hymes (1996) famously reminded us. Clickbait simply reaffirms this, as does the prominence of ‘fake news’ and ‘alternative facts’ (or outright lies) in contemporary political campaigns.
The implications of all of this are clear, and I will quickly sketch three major ones. All three are related to how we imagine the democratic system as an actually existing contemporary mode of organization of the political field.
First, we need to abandon the (cherished) idea of modern democracy as a rational system of decision-making, revolving around ‘the truth’ and with this ‘truth’ as the point around which consensus (and coalitions) can be formed. Few issues are presently as controversial as ‘the truth’, and commentators sometimes refer to our times as the ‘post-truth’ era. In actual practice, it is best to approach democratic decision-making as a ‘mixed method’ thing in which rational practices are just one element, and not always the prevailing one.
Second, we also need to distance ourselves from traditional views of contemporary democratic decision-making as carried along by relatively stable (and sociologically pre-defined) majorities engaged in rational debate with equally relatively stable minorities. And third, we need to distance ourselves from the idea of ‘public opinion’ as a reliable indicator of such majority-minority divisions.
Both elements – the majority-minority divisions and the notion of public opinion – too often operate as unchallenged a priori assumptions in analysis. In times of micromarketing and fragmented audiences, such assumptions need to be empirically demonstrated if we wish to get a precise view of the actual political process and the role of discursive action in that process. If we take these three implications on board, we are facing a more general one. An adequate understanding of the contemporary political system requires another sociological imagination (cf. Blommaert 2018b), for the one we tend to carry along in our analyses reflects a political process that might have been accurate in the 20th century, but no longer corresponds to the field that prevails today.
Revisiting models of communication
I can now turn to the second reflection. It is, obviously, connected to the previous one and can be seen as a more specific extension of it of particular immediacy for discourse analysts. Here, too, my remarks address deep and influential assumptions often implicitly articulated in analysis – assumptions about the model of communication underlying analysis.
I shall start from something which all of us learned during our first year of language studies: Saussure’s sender-receiver model of communication (Saussure 1960: 27). (See Figure 1)
Figure 1: Saussure’s model of communication
We see two (male) individual humans, A and B; A produces an utterance originating in his brain and transmits it through his mouth to the ears of B, who processes it in his brain and responds to it. Both A and B perform these acts synchronically (in a real moment of interaction) and symmetrically: the acts of A and B are identical in Saussure’s model. All of this is very well-known, but we should remind ourselves that this simply dyadic sender-receiver model is, to a large extent, still the default model for imagining communication at large, and thus serves as the backdrop for communication theorizing. Note: it is individual, human, spoken, linear, synchronic and direct within a clear sender-receiver relationship.
With this in mind, let us turn to the actual contemporary forms of communication in the post-digital era. Here is the main structure of communication on Twitter. (See figure 2)
Figure 2: Communication structure on Twitter
We see a very different and much more complex structure of communication here. The tweet, produced by someone (e.g. president Trump), is sent to an algorithm – a nonhuman ‘receiver’, if you wish – through which artificial intelligence operations forward it to numerous specific audiences (A 1, 2, …n in figure 3), whose responses are fed back, as data, to the algorithm and thence to the sender of the tweet in nonstop sequences of indirect, mediated interaction. Parts of these audiences can relay their own uptake of the tweet (via the Twitter algorithm) to secondary audiences (A 5, 6 … n in the scheme), who can do the same – and so on, enabling a tweet to reach audiences not initially accessible, both immediately after the moment of tweeting and much later. The audiences (also often called ‘bubbles’) are constructed by the algorithms out of users’ data-yielding profiles, and they are selected on the basis of a range of ‘data points’ including topic keywords, hashtags and histories of prior interactions. The audiences consist of individuals, sure; but in the case of Trump and many other high-profile accounts also of bots – computer programs behaving like ‘normal’ Twitter users and generating specific forms of response such as liking and retweeting and sometimes dramatically increasing the volume of traffic for tweets.
What we need to take along here is this:
(1) There is no linear, symmetrical and direct sender-receiver structure on Twitter, because the platform itself provides an algorithmic mediator for all and any interaction.
(2) The participants are, consequently, not all human, as very crucial parts of the communication structure are controlled by automated AI technologies.
(3) As an effect of these algorithmic mediations, there is not a single ‘audience’ (or ‘public’) in the structure of communication, but a fragmented complex of ‘niched’ audiences often with incompatible interests or political orientations.
(4) There is also not a single producer of discourse here: political discourse is produced and circulated by all actors within this model, humans as well as non-humans.
(5) The entire system is permanently in motion, with constant interactional conversions of actions performed by (human and nonhuman) participants into data further shaping and regulating the effects of the actions (cf. Maly 2018).
(6) These actions are indirect, i.e. mediated by technologies as well as by the uptake and feedback actions of (unknown and unintended) audiences.
(7) They are also not synchronic but spread over variable spans of time. Actions can be performed months or years after the original moment of tweeting, because of the archiving capacity of online platforms.
(8) Finally, we are observing scripted communication here, not spoken communication. We are in a field of literacy here; this field is extraordinarily diverse and involves, for instance, different kinds of platforms on which literacy practices are performed. The conversion of all actual online practices into data, to be used in AI and in micromarketing, must be included into this.
These are empirical observations, and specific ones. But even if we would prefer to minimalize their potential for extrapolation and generalization (something I would not encourage), these observations do not in any way fit into Saussure’s old model of communication, nor can they be made to fit into it. The model is simply irrelevant as a tool to generalize the actual modes of communication we face when looking at these types of examples.
Models of communication in the post-digital era need to be models in which the characteristics of the online-offline nexus are absorbed as a reality affecting the phenomenology of communication in the most profound sense. This is, I think, a matter of realism in scientific practice: the frameworks for generalization we use need to be grounded in empirical analytical insights reflecting the ‘is’ of communication, not its ‘ought’. More concretely, political discourse analysis needs to be re-footed on the basis of the new kinds of communicative economies (including resources, actors and relationships between actors) we observe and inhabit.
A polycentric world of communication
The latter remark takes us back to what was said earlier: political communication in post-digital environments involves a multitude of actors, some of whom are human and some non-human, and all of whom operate both as producers and receivers of political messages. The idea that political discourse is the discourse of professional politicians alone, or even primarily, is an anachronism. True, politicians often provide the ‘input’ for the complex communication processes outlined in the previous section; but they do not determine its effects, intensity or scale of circulation – things performed by the multiple audiences (including bots) in interaction with platform algorithms. Here, too, we can observe the limits and inadequacies of the older propaganda models: demonstrating that ‘the public’ is ‘influenced’ by politicians’ political messages – in which the politician (and his/her messages) is the key actor – nowadays requires a very intricate analysis of ‘who does what’. Outcomes of such analyses might suggest that parts of the public influence other parts of that public, or more precisely: they might suggest that not politicians, but specific audiences influence other audiences, and that this is achieved by means of a multitude of processes of re-entextualization (Silverstein 1996).
Entextualization refers to the process by means of which discourses are successively or simultaneously decontextualized and metadiscursively recontextualized, so that they become a new discourse associated to a new context and accompanied by a particular metadiscourse which provides a sort of ‘preferred reading’ for the discourse. This key concept helps us understand that ‘virality’ – the large-scale distribution of messages by means of online ‘copy’ practices such as reposts, retweets and so forth – is not, in fact, a series of repetitions of ‘the same’ message, but a series of re-entextualizations (cf Varis & Blommaert 2015). In such re-entextualizations, the message of a politician is taken by an audience member – it is appropriated, if you wish – and inserted into an entirely new act of communication involving a new producer (the audience member) and addressees (the audience member’s own network of online ‘friends’ or ‘followers’) in a new kind of interaction, with the algorithms mediating this new and more complicated process, the ‘data’ of which are fed back to the politicians’ original act of communication, even if the characteristics of the new act of communication diverge strongly from those of the original (‘input’) act.
Concretely, imagine that I retweet a tweet launched by president Trump. I am not one of Mr. Trump’s supporters; in fact, I’m highly critical of his presidency and I became a ‘follower’ of Mr. Trump’s Twitter account because it offers me plenty of powerful arguments to be critical. My retweet would reach a network of people broadly aligned with my views (my bubble), and it is likely that this specific audience of mine will understand my retweet as a critical comment on Mr. Trump, not as an act of support for him and his views. My retweet, in short, is a re-entextualization that conveys a negative message on Mr. Trump, not the positive one articulated in lots of other retweets (and preferred, one dares to venture, by Mr. Trump himself). But the Twitter algorithm will add my retweet to the total ‘virality’ of Mr. Trump’s original tweet, allowing him and his supporters to interpret my act as a form of popular support for (and possibly even agreement with) Mr. Trump’s message.
We observe polycentricity here: the circulation of political messages in the online-offline nexus does not, in any way, allow us to attach one single interpretation to that meaning. Sixty thousand retweets of Mr. Trump’s message cannot be read as sixty thousand acts of support and agreement – widely divergent interpretations will be included in what looks like simple repetitions of the same message. Observe (but I can only mention this in passing here) that new interpretations can be added much later, given the archival capacity of the Web: the tweets can be invoked as evidence in litigation, for example, or as evidence of contradictions or unconventional policy shifts by the president. Online messages inevitably end up in a system of communication in which the actually communicated meaning of such messages is open to very profound indexical re-orderings and, hence, of very different readings depending on the kinds of appropriations mentioned above.
Explanations for this can be found in the Twitter model of communication I sketched above: we are facing nonlinear, asymmetrical and non-synchronic acts of communication here, involving different ‘indexical centers’ (cf. Blommaert 2005). In the example I gave, I am such an indexical center for my own Twitter audience, and the indexical order I apply to Mr. Trump’s message will be very different from that attributed to it by supporters of the president, who represent another range of indexical centers. The algorithms, of course, are also very powerful indexical centers in the entire process. In each instance, entirely different sets of social, cultural and moral norms will be applied to the messages, and what such messages actually do in communication will depend on such widely divergent norms (cf. Blommaert 2019).
This feature of political (and other) communication in the post-digital era is yet another argument against simple propaganda models. Politicians quite often understand the numbers of retweets as well as the numbers of ‘followers’ or ‘friends’ of their social media accounts as evidence of the level of popular (often called ‘democratic’) support they command – an anachronistic reading grounded in the propaganda model and very much at odds with the actual facts of communication, uptake and effect of their messages. As said earlier, there is no way in which we can see online audiences as yet another embodiment of ‘the masses’ in the 20th century, modernist sense of that term.
Good and bad news for discourse analysts
The last reflection has a clear implication: politicians need to be aware of the widely divergent meanings that their messages allow, and need to spend a great deal of care for the actual forms of communication they engage in. Advanced big-data based micromarketing assists them in the process, but messages targeting specific audiences still have the capacity to spill over into unintended audiences and generate a powerful negative backlash that way. Remember that the ultimate aim is to construct (temporary and ephemeral, but real) coalitions of different audiences; negative backlash from unintended audiences can render the construction of such coalitions more difficult or impossible.
All of this is good news for political discourse analysts. It is also bad news. The good news is that the increased attention for actual forms of political communication creates a demand for nonstop, intensive and sophisticated discourse analysis. I did my PhD in 1989 on Swahili political discourse in Tanzania. In those days, our material consisted of a finite body of texts – speeches given and texts written by politicians, possibly complemented by mass-media reports of such speeches and texts. Political discourse analysis today is much more exciting, for accurate analysis now involves the capacity to change analytical strategies whenever the field and its constituent elements change – and this is now a permanent process.
This, of course, can also be seen as bad news. The toolkit with which I engaged with my Tanzanian texts in the 1980s was outstanding in its usefulness and clarity – we had standard ‘recipes’, so to speak, for doing the work of political discourse analysis. We no longer have the comfort of such clarity, for political discourse analysis, as just mentioned, now includes perpetual adjustment of perennially unfinished tools and tactics to adequately address a moving target. This challenge is theoretical, methodological, but also practical. Political discourse analysis is of crucial importance if we want to understand the complexities of the societies we inhabit. So there is not just a demand for such analysis but a need to continue providing it. The fact that this work becomes more difficult and more demanding should not deter us – the answer to it is a key scientific ambition called ‘innovation’.
 This essay is the written version of the opening statement of a Babylon webinar on this topic, held on 25 November 2019 and involving audiences from Brazil, Argentina and Australia. I am grateful to all participants for the very stimulating discussion we had during the webinar. A video version can be found here.
The debate between Lippman (1922) and Dewey (1927) can serve as an example. The debate structured two major lines of argument regarding the connection between politics, media as information providers, and the public, a pessimistic line and an optimistic one, respectively. These lines provide an accurate heuristics for following 20th century debates on the role and place of media in western democracies. Obviously, the views of e.g. Horkheimer & Adorno (1947) and Postman (1985) – to name just those influential voices – also fit into the same mold.
 The following paragraphs are adapted from Blommaert (2019).
Arnaut, Karel, Martha Karrebaek & Massimiliano Spotti (2017) Engaging superdiversity: The poesis-infrastructures nexus and language practices in combinatorial spaces. In Karel Arnaut, Jan Blommaert, Martha Karrebaek & Massimiliano Spotti (eds.) Engaging Superdiversity: Recombining Spaces, Times and Language Practices: 3-24. Bristol: Multilingual Matters.
Benjamin, Walter (1936 ) The work of art in the age of its technological reproducibility. In Walter Benjamin, Selected Essays, Volume 3: 1935-1938 (eds. Howard Eiland & Michael Jennings): 101-133. Cambridge MA: Belknapp Press of Harvard University Press.
Blommaert, Jan (2005) Discourse: A Critical Introduction. Cambridge: Cambridge University Press.
Blommaert, Jan (2018a) Trump’s tweetopoetics. Tilburg Papers in Culture Studies, paper 203. Downloaded from https://www.tilburguniversity.edu/research/institutes-and-research-groups/babylon/tpcs
Blommaert, Jan (2018b) Durkheim and the Internet: On Sociolinguistics and the Sociological Imagination. London: Bloomsbury.
Blommaert, Jan (2019) Sociolinguistic restratification in the online-offline nexus: Trump’s viral errors. Tilburg papers in Culture Studies, paper 234. Downloaded from https://www.tilburguniversity.edu/research/institutes-and-research-groups/babylon/tpcs
Cramer, Florian (2014) What is ‘post-digital’? A Peer-Reviewed Journal About Post-Digital Research 3/1: 10-24. https://monoskop.org/File:A_Peer-Reviewed_Journal_About_Post-Digital_Research_2014.pdf
Dewey, John (1927) The Public and Its Problems. New York: Holt.
Fairclough, Norman (1989) Language and Power. London: Longman.
Herman, Edward & Noam Chomsky (1988) Manufacturing Consent: The Political Economy of the Mass Media. New York: Pantheon.
Horkheimer, Max & Theodor Adorno (1947 ) Dialectic of Enlightenment. Stanford: Stanford University Press.
Hymes, Dell (1996) Ethnography, Linguistics, Narrative Inequality: Toward an Understanding of Voice> London: Taylor & Francis.
Lippman, Walter (1922) Public Opinion. New York: Harcourt.
Maly, Ico (2018) Populism as a mediatized communicative relation: The birth of algorithmic populism. Tilburg Papers in Culture Studies, paper 213. Downloaded from https://www.tilburguniversity.edu/research/institutes-and-research-groups/babylon/tpcs
Maly, Ico & Piia Varis (2016) The 21st century hipster: On micro-populations in times of superdiversity. European Journal of Cultural Studies 19/6: 637-653. https://doi.org/10.1177/1367549415597920
Postman, Neil (1985) Amusing Ourselves to Death: Public Discourse in the Age of Show Business. New York: Viking.
Prochzka, Ondrej & Jan Blommaert (2019) Ergoic framing in New Right online groups: Q, the MAGA kid, and the deep state theory. Tilburg Papers in Culture Studies, paper 224. Downloaded from https://www.tilburguniversity.edu/research/institutes-and-research-groups/babylon/tpcs
Saussure, Ferdinand de (1960) Cours de Linguistique Générale (eds. Charles Bally & Albert Sechehaye). Paris: Payot.
Silverstein, Michael (1996) The secret life of texts. In Michael Silverstein & Greg Urban (eds.) Natural Histories of Discourse: 81-105. Chicago: University of Chicago Press.
Varis, Piia & Jan Blommaert (2015) Conviviality and collectives on social media: Virality, memes, and new social structures. Multilingual Margins 2/1: 31-45
The written version of the talk can be found here.
It’s late November 2019 and I just returned from a two-week trip to Japan. I admit that on journeys such as these, the fieldworker in me tends to take over at times from the tourist or visitor, for Japan remains a stunningly interesting place for issues of language and globalization. I discussed a number of Japanese examples already in The Sociolinguistics of Globalization, now almost a decade ago, and my recent visit added new and rich linguistic landscape data to the voluminous collection I have built over the years.
Let me quickly reiterate the argument I developed earlier regarding the phenomenology of globalized languages such as English and French. I started from the observation that linguistically ‘incorrect’ forms of English and French account for a lot – perhaps most – of what we see of these languages in the world. It is too easy to dismiss such forms of language…
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Introduction: a perennial agenda
The discipline we now call sociolinguistics has throughout the 20th century systematically maintained and elaborated two connected issues.1 Note that ‘sociolinguistics’ as it is now called is an innovation of the 1960s, when scholars (mainly in the US) started using the label to distinguish themselves and their work from that of the Chomskyan paradigm in linguistics, and to emphasize continuity with an older paradigm incorporated in anthropology and exemplified in the tradition started by Franz Boas (Darnell 1998; Hymes 1992; Bauman & Briggs 2003). It is in this longer tradition that the two connected issues were given a definitive shape. The issues are:
Taken together, these issues define sociolinguistics as a discipline concerned with diversity, but in a particular way.
The first issue, unpacked, has to do with the observation that every language, when seen in its concrete social context, is ‘perfect’: its resources enable members of the community of usage to express all possible meanings and fulfill every social-communicative function. In Benjamin Lee Whorf’s (1956) famous view, every language incorporates, expresses and shapes the worldview of those who use it, and those so in its very structure (cf. also Silverstein 1979). The issue was clearly articulated in Boas’ seminal Introduction to the Handbook of American Indian Languages (1911, also Boas 1928) as well as in Sapir’s groundbreaking Language (1921). It became the epistemological, moral and political point of departure as well as the battle cry of generations of sociolinguists, and it defined the linguistic scope of the new discipline.
The second issue defined the battlefield of sociolinguistics. Given the in-principle equality of all languages, how come so many languages are factually considered inferior to others? Why are speakers of so many languages oppressed and marginalized, why do we make distinctions between ‘standard’ and ‘substandard’ varieties, why do we consider dialects features of backwardness and remnants of a pre-modern past? Why do we attach stigma to some accents in a language and prestige to others – when both are linguistically equivalent? And why are such distinctions codified in language policies and cast in even more robustly policed language ideologies enabling and sanctioning discriminations in which linguistic differences are turned into sociolinguistic inequalities?
This second issue, certainly from the 1960s onwards, defined the social scope of sociolinguistics, and it can be summarized in one word: stratification. And there were precursors: ‘salvage linguistics’ – the study of languages threatened with extinction – emerged out of an awareness that such languages would disappear not because of their intrinsic inferiority compared to, say, English or Spanish, but because of the fact that increasing marginalization of the users of such languages would ultimately eliminate the languages. And such forms of marginalization often included a strong stigma – a perceived, ideological inferiority – for the languages and language varieties as well. They were not qualified as ‘languages’ but as ‘dialects’, ‘speech’, ‘jargons’, ‘sabirs’ or simply ‘barbarian’ and ‘primitive’ (cf. Fabian 1986a, 1986b). Certainly when these language were not accompanied by an identifiable writing system, they were considered to be expressions of the innate and therefore general inferiority of their users.
As soon as a branch of scholarship emerged carrying the label of sociolinguistics, both issues merged into an agenda, expressed and developed in the work of the leading scholars of the first generation of sociolinguists. Forms of sociolinguistic diversity, ranging from AAVE in the US (Labov 1970), native-American stories (Hymes 1983), ‘nonnative’ Englishes in the US and the UK (Gumperz 1982) or working class accents in the UK (Bernstein 1971) and minority-majority multilingualism (Fishman 1971) were shown to be the object of intense discrimination, notably in education (the focus of e.g. Labov 1970; Bernstein 1971; Hymes 1980). Such forms of discrimination had social, not linguistic causes, and their analysis as linguistic phenomena needed to be set in a context that was at once structurally formed as well as synchronically enacted, often with predictable outcomes due to the pervasive and enduring influence of policies and language ideologies rationalizing (and rendering ‘natural’) the stratification of sociolinguistic regimes (cf. Kroskrity 2000; also Bourdieu 1991). Increasing diversity, for instance due to globalization processes, appeared to merely increase and complicate sociolinguistic inequalities (cf. Blommaert 2005, 2008, 2010; Arnaut et al 2016).
This very quick run through a century of sociolinguistic history takes me to the point of departure for this contribution. While we must take stratification as the basic engine behind the dynamics of sociolinguistic systems, the actual forms of stratification have become somewhat less predictable due to what we call the online-offline nexus: the fact that large parts of the world’s population now organize and live their social lives online as well as offline, with both zones of social life, so to speak, being mutually influencing (cf. Blommaert 2018). Offline practices are profoundly influenced and altered by online infrastructures and vice versa, creating different sociolinguistic economies – patterns of resource distribution, general formats for conducting communicative actions and forming communities – and repertoires adjusted to such changed economies.
A simple example can suffice to illustrate the changes: emojis have become part of the everyday repertoires of visual design of many millions of language users across the world and (while not ‘belonging’ to any language in particular) have rapidly acquired specific, conventionalized communicative functions and effects. Philip Seargeant (2019) perceived this development as nothing short of an ‘emoji revolution’. Now, emojis are not part of most language learning curricula – their usage is often explicitly proscribed in language classes – and their usage is ‘chronotopic’, confined to particular and situated timespace arrangements such as scripted online interaction, advertisements and popular culture (Kroon & Swanenberg 2019; cf. also Blommaert 2015). But within such chronotopes, they are, if you wish, features of ‘standard’ language with a tremendous, transnational and translinguistic scope of usage and variant productivity (e.g., when the fully-formed smiley emoji is not available, it can be realized by means of other typographic signs such as ‘:-)’).
Similar things can be observed with respect to hashtags – the ‘#’ sign – as well as with the global spread of the ‘@’ sign to denote time and place as well as addressees in a wide range of scripted messages. Both are widely used in complex functions, and such usages display strong degrees of normativity (Blommaert 2020). Observe that such signs do not remain online but can be transported to offline chronotopes as well. Hashtags, notably, are widely used in demonstration banners, posters and flyers as well as on clothing. Hashtags have become a near-global sign indexing ‘message’ in general. At a higher-scale level of communicative economies, we see how online social genres such as tweets or Instagram updates have become incorporated into domains of power and prestige – they have become firmly integrated into political campaigns, for instance, and now compete for prominence with older genres such as the politician’s public rally speech or the newspaper editor’s op-ed article.
Restratification in the online-offline nexus
All of this means that the normative world in which sociolinguistic resources get their place and value allocated needs to be reconsidered. The expansion of the infrastructures for communication have inevitably gone hand in hand with an expansion of the ‘centering institutions’ described by Michael Silverstein (1998: 404; also 1996) as the real or imagined sources of normative authority for social-communicative conduct to which people orient while communicating, and through which their conduct is appraised and ratified (cf. also Agha 2007). The result is a complex polycentric sociolinguistic system, i.e. an unstable, dynamic and open one in which gaps and overlaps, conflicts, contradictions and nonlinear outcomes are the rule rather than the exception (cf. Blommaert 2016).
Of course, this statement, as soon as it is formulated, appears pedestrian, almost truistic. Perhaps sociolinguistic systems were always complex ones (as prefigured by e.g. Bakhtin and Voloshinov when they emphasized dialogism and heteroglossia), and perhaps the only virtue of the online-offline nexus is that it takes this simple given into the spotlight and makes it inevitable. But even so there is a moment to be captured, for this insight forces us towards another imagination of the major vectors and patterns of stratification and restratification – away from simple top-down models of imposed and carefully engineered hegemony (as in early studies on language policy and language planning, e.g. Eastman 1983), from stable binaries of majority and minority languages at societal level with linear effects of linguicide looming (e.g. Phillipson 1992) and from studies of forms of language mixing as aberrations of a supposedly homogeneously monoglot norm (e.g. Myers-Scotton 1993). Theoretically as well as empirically, we need to see the normative valuation of sociolinguistic resources and of the modes of communication they shape, as well as the stratifying outcomes of such valuations, as sets of different effects spread over and caused by a range of actors and involving several very different types of activities, some of them involving high degrees of agency and others low degrees, some of them obviously revolving around human decision-making while others involve algorithmic technologies in crucial aspects of the process. Simply calling all of this ‘power’ may be comforting shorthand, but does not do justice to what actually goes on. The question is really: which specific forms of power generate stratifications and restratifications in online-offline situations.
I shall try to answer this question by means of an extended case analysis. I can offer a spoiler at this point. We shall see that the online language of the powerless can be appropriated by the powerful precisely because it is transgressive and evokes strong moral condemnation from powerful groups, and that such curious reversals of conventional sociolinguistic stratifications can algorithmically be turned into a partisan ‘majority’ norm in a fragmented public sphere. The case I have chosen involves the most powerful person on earth: the President of the United States of America. It involves English, the world’s most stratified language because it is the most globally distributed one. And it involves the sociolinguistic object most sensitive to normative judgment: orthography.
Trump on Twitter
There is a very strong cultural assumption in societies such as ours, in which the most powerful people are also the sociolinguistic elites: they are expected to command the most advanced and highly valued communicative resources. When they talk, they are fluent and eloquent in ‘standard’ varieties of the most prestigious languages; when they write they write elegant and elaborated texts in accordance to the strictest rules of grammar, genre and orthography. And in all of this we expect these people to be coherent, make sense and preferably sound intelligent. This assumption rests on robust sociological grounds, as the oeuvre of Pierre Bourdieu demonstrated: dominant groups in society are the guardians of norms in the field of culture as well as in the field of language, and when a variety of language is called ‘accentless’, we are actually facing the most prestigious accent – that of the elites (cf. Bourdieu 1987, 1991; Agha 2007). It is further undergirded by an army of professionals supporting the powerful in their communicative work – from speech writers to communication advisors and social media staff – and ensuring the best possible discursive products whenever one needs to talk or write.
There is no doubt that Donald Trump can draw on the services of an exceptionally large and exquisitely equipped army of such communication specialists. He could already do so before his election to the US presidency in 2016, and it is safe to assume that he could benefit from the services of the most outstanding members of the profession after he moved into the White House. Yet, since the very beginning of his electoral campaign, Trump’s discursive idiosyncrasies became the object of intense public discussion.
Of course, he had big shoes to fill as a communicator, being the successor to one of modern history’s most accomplished public orators, Barack Obama. But then, Trump was not the first US president to be targeted for public communication flaws. Obama succeeded George W. Bush, a president whose incoherence and inarticulateness in public speech had become the stuff of legends (see Silverstein 2003; Lempert & Silverstein 2012). Bush, with a Texas drawl, would fail to get the pronunciation of relatively simple words and names (such as ‘Europe’) right, he would produce incoherent ramblings in answers to reporters, would deliver contradictions in terms and so forth. Such communicative flaws were widely perceived to be deeply embarrassing for almost anyone associated with Bush, and as a sign of a character flaw called ‘questionable intelligence’ for Bush himself. But there still was the army of communication professionals, able to prevent the unfiltered and unedited presidential ramblings from becoming US policy, and able to turn incoherent statements into coherent (or coherently explained) ones, to rationalize the president’s inarticulateness as part of his ‘message’ as an ‘average American’ talking in a ‘demotic’ way. Trump was a lot worse.
Trump’s general tenor of communication was, to put it mildly, strange. In public debates, he was offensive bordering on obscene, bluntly insulting opponents (‘Crooked Hilary’, ‘the failing New York Times’) while using extravagant hyperboles in self-description and self-qualification – ‘great’, ‘the greatest’, ‘absolutely fabulous’, ‘beautiful’, ‘the best’, ‘the only one’ and so forth – and displaying a cavalier attitude towards facts as well as some of the defects earlier identified with George W. Bush (see figure 1).
Figure 1: Comment on Trump’s mispronunciation.
Trump’s public speech performances quickly became a favorite topic for late night show hosts such as Trevor Noah and Steven Colbert, and Trump imitators make a decent amount of money dissecting his usage of self-coined terms such as ‘bigly’, ‘stable genius’ and so forth and by poking fun at his obvious but stubbornly repeated gaffes (e.g. claiming that hurricane Dorian would strike Alabama, or announcing a border wall between Mexico and Colorado).
But Trump did not just talk: he also wrote a lot, and did so on Twitter. Trump’s campaign, as we know, was the first major algorithmic campaign in US history (Maly 2016), and Jordan Hollinger (2018) calls his victory the ‘first Twitter-based presidency’. His usage of Twitter is what makes his presidency entirely exceptional: he systematically used his private Twitter account as the channel for his messages, even after becoming president. The official Twitter account of the US president (@POTUS) often merely retweets messages launched by Trump on @realDonaldTrump. These tweets, consequently, fully maintain the character of ‘normal’, ‘authentic’, undoctored and unfltered tweets produced by an ‘ordinary’ Twitter user. Tweetbinder, an online repository on Trump’s tweets, claims that the president sent out about 10 tweets per day since his election, amounting to many thousands of tweets throughout his term in office. The same source also asserts that Trump writes and sends his tweets himself without the assistance (or censorship) of a communications team.2
The most amazing aspect of Trump’s usage of Twitter is the tension between his tenor as an ‘ordinary’ user of social media on the one hand, and the nature and content of his messages. Trump doesn’t just lambast his opponents or showcases his public success on Twitter, he also uses the medium to announce major (and often not otherwise announced or anticipated) policy decisions and initiatives – often causing confusion and déconfiture among his collaborators and political allies as well as drawing fierce criticism from his opponents. Twitter really is Trump’s most prominent channel of communication.
I need to pause here and turn to the general structure of communication on Twitter. And I shall start from something which all of us have absorbed during our first year of language studies: Saussure’s sender-receiver model of communication (Saussure 1960: 27). (See Figure 2)
Figure 2: Saussure’s model of communication
We see two (male) humans, A and B; A produces an utterance originating in his brain and transmits it through his mouth to the ears of B, who processes it in his brain and responds to it. All of this is very well-known, but we should remind ourselves that this simply dyadic sender-receiver model is, to a large extent, still the default model for imagining communication at large, and thus serves as the backdrop for communication theorizing. With this in mind, let us turn to the main structure of communication on Twitter. (See figure 3)
Figure 3: Communication structure on Twitter
We see a very different and much more complex structure of communication here. The tweet, produced by someone like Trump, is sent to an algorithm – a nonhuman ‘receiver’, if you wish – through which artificial intelligence operations forward it to numerous specific audiences (A 1, 2, …n in figure 3), whose responses are fed back, as data, to the algorithm and thence to the sender of the tweet in nonstop sequences of interaction. Parts of these audiences can relay their own uptake of the tweet (via the Twitter algorithm) to secondary audiences (A 5, 6 … n in the scheme), who can do the same – and so on, enabling a tweet to reach audiences not initially accessible. The audiences (also often called ‘bubbles’) are constructed out of users’ data yielding profiles, and they are selected on the basis of topic keywords, hashtags and histories of prior interactions.3 They consist of individuals, sure; but in the case of Trump and many other high-profile accounts also of bots – computer programs behaving like ‘normal’ Twitter users and generating specific forms of response such as liking and retweeting and sometimes dramatically increasing the volume of traffic for tweets.4
What we need to take along here is this:
(a) There is no linear sender-response structure on Twitter, because the platform itself provides an algorithmic mediator for all and any interaction;
(b) the participants are, consequently, not all human, as very crucial parts of the communication structure are controlled by automated AI technologies;
(c) as an effect of these algorithmic mediations, there is not a single ‘audience’ (or ‘public’) in the structure of communication, but a fragmented complex of ‘niched’ audiences often with incompatible interests or political orientations;5
(d) the entire system is permanently in motion, with constant interactional conversions of actions performed by (human and nonhuman) participants into data further shaping and regulating the effects of the actions (cf. Maly 2018).
We can now turn to Donald Trump’s tweets again.
Trump’s viral errors and sociolinguistic restratification
We saw how Trump’s speech idiosyncrasies were targeted by critics; his tweets have been an even more outspoken object of language-normative criticism. Given the ‘authentic’ nature of Trump’s tweets, peculiarities of writing habits can be noticed. One remarkable peculiarity is his unwarranted use of capitals – see ‘Endless Wars’ and ‘Walls’ in figure 4.
Figure 4: unwarranted capitals
The same ‘authentic’ nature of Trump’s tweets causes rather frequent typographic errors, and these are instantly singled out for condemnation. (See figure 5)
Figure 5: ‘honored’
We see indexicality in its purest form here: a typographic error leads to a judgment of the entire person: Trump doesn’t know what ‘honor’ is, hence he cannot write the word correctly. This form of sarcastic indexical interpretation is very frequent on Twitter. (See figure 6)
Figure 6: ‘passed, not past’
Those are moral condemnations of the person Donald Trump. But they are informed by something bigger: the strong cultural assumption mentioned earlier, in which we expect our social, cultural, intellectual and political elites to communicate in accordance with the most elevated standards of language – and in particular, of literate language (cf. Lillis 2013; Turner 2018). Thus, orthographic errors on Twitter are converted into judgments of Trump as president – since the president of the US is supposed to write correctly. (See figure 7)
Figure 7: ‘unpresidented’
It is because Trump is president that the indexical correctness issue is applied to his writing with such vigor and intensity. Interestingly, in such exposures, Trump’s Twitter literacy is generalized to include all of his literacy. Thus, when Trump wrote a widely publicized official letter to Turkey’s president Erdogan in October 2019, the awkward wording of the letter was caricatured by online artist El Elegante as a sequence of emojis (figure 8).
Figure 8: El Elegante’s caricature of Trump’s letter
Twitter is the main forum for such critical exposure of Trump’s typographical errors, but it is not the only one. Mainstream media comment on them, newspapers devote articles to them, and a wide range of analysts examine them. Blogger-analyst Ginny Hogan (2018) provides a short, sarcastic summary of the problem:
“Unfortunately, the data set doesn’t include all deleted tweets, although I would be honered to learn how some of Trump’s interesting spelling choices affect tweet popularity. To bad there’s not a lot of press covfefe on that — it’s really an unpresidented phenomenon #Denmakr.”
The reference to ‘covfeve’ here is interesting, because it’s probably Trump’s most iconic Twitter error. Trump posted it in May 2017, and the nonsense word is probably a botched attempt to write the term ‘coverage’ (see figure 9).
Figure 9: ‘covfeve’
The word became an instant hit among critics on Twitter and beyond, the more since the White House Press Secretary tried to explain it as meaningful: “I think the president and a small group of people know exactly what he meant”, Sean Spicer announced.6 ‘Covfeve’ became the stuff of memes and went viral in a wild stampede of (often hilarious) critical uptake.
So far so good: we see how orthographic errors by Donald Trump lead to relatively predictable – standard – indexical interpretations as transgressive and inadmissible features of communicative conduct displayed by the president of the United States. We can observe the dominant sociolinguistic stratification at work here: such errors in writing are wrong, certainly when performed by members of the elites, and they index moral disqualification of the person and question his membership of those elites. Someone who commits such errors should never be president of the US, is the line of interpretation we have observed so far. And this would be the end of the story in Saussure’s communication model: B (the audience) has disqualified what A (Trump) tried to communicate. But as we have seen, communication on Twitter is different.
Let us have a look at the people who posted the critical comments on Trump’s errors. All of them are public figures: Noga Tarnopolsky is a journalist, RC de Winter is a poet and digital artist, El Elegante is a digital artist, Randy Mayem Singer is a successful movie and TV series screenwriter, and J.K. Rowling is of course the author of the Harry Potter blockbusters. All of them are intellectuals and artists working with language, and in the worldview of Donald Trump and his supporters, they belong to the (‘liberal’) cultural ‘elites’. Within those ‘elites’ they form a subgroup notoriously critical of Trump and his politics, and Trump himself takes shots at such liberal intellectual and artist elite figures quite often on his Twitter account. (See figure 10)
Figure 10: Meryl Streep is over-rated.
These intellectual and artistic elites clearly form one (or several) of the niche audiences on Trump’s Twitter account – a hostile one. And they can be described, by the Trump camp, as the elites whom Trump wants to defy and defeat, for they are in opposition to ‘the people’. Many actors in Trump’s universe are ‘a threat/enemy to the people’ – mainstream media are, for instance, quite systematically qualified as such.7 Ridiculing Trump’s orthographic errors (or speech habits) can thus be represented as a predictable and stale anti-Trump reaction coming from one of the elite social groups he targets as opposed to the interests of ‘ordinary Americans’.
This is the point where we get sociolinguistic restratification. Trump’s orthographic errors are (very much like George W. Bushes discursive inarticulateness) indexically upgraded from ‘bad in the eyes of the elites’ to ‘good in the eyes of the people’ – they become indexically restratified as the demotic code that iconicizes the down-to-earthness of ordinary Americans. And this restratified sign goes viral among the other and more supportive audiences of his Twitter account. In figure 11, we see how a Trump supporter uses #covfeve (followed by two positive emojis) as an emblem of pride used against Trump critics. The meaning attributed to the word here is grounded in the interpretation of Trump’s initial ‘covfeve’ tweet, which attacked mainstream media. This intertext provides the function of the word here: covfeve has become (like ‘MAGA’) a term that can be used to talk back to Trump’s detractors.
Figure 11: pro-Trump Twitter account.
The term ‘covfeve’ was also adopted by a score of Twitter users in their user names. (see figure 12)
Figure 12: ‘covfeve’ accounts
Some of these accounts are obviously held by people who are critical of Trump, while others are held by Trump supporters. The indexical vectors of the term are opposites: for pro-Trump people, ‘covfeve’ indexes support for Trump and hostility towards his elite critics; for anti-Trump people, it indexes the fact that Trump is unfit for the presidency. And both indexical vectors are attached to an orthographic error made on a public forum such as Twitter. ‘Covfeve’ became a viral error, circulated within very different audiences and with very different meanings.
A lab of restratification
Let me summarize the case. Trump’s orthographic errors on Twitter got immense traction on Twitter (and beyond) and did so within very different audiences, some of whom applied the ‘standard’ sociolinguistic stratification in which orthographic correctness is mandatory for people at the top of the social ladder. Other audiences used an entirely different, ‘demotic’ understanding of these errors, presented there as emblematic of someone intent on defending the interests of ‘ordinary’ Americans. The virality of errors such as ‘covfeve’ implies at least two entirely opposite indexical vectors, one of which restratifies the conventions of the sociolinguistic domain of writing from elite-dominant to demotic-dominant.
There is, of course, irony in the fact that Donald Trump (like George W. Bush before him) can be presented at all as a non-elite, ‘ordinary’ person. He is a scion of a very wealthy family and proudly proclaims his wealth to all who want to listen, he was a mass media superstar, a bestselling author and an alumnus of the University of Pennsylvania’s prestigious Wharton School, and he is of course the president of the United States. From what is publicly known about his lifestyle, he really doesn’t live like ‘ordinary’ Americans.
His communication styles, however, offer the potential to turn this obvious misfit into a perfect fit: sarcasm about his speaking and writing errors can be presented as ‘elitist’ and magnified – generalized – as part of a pattern of elite domination of ‘ordinary’ Americans, the kind of elite domination Trump promised to abolish as president. In the process, the sociolinguistic norms of different audiences are played off against each other in Twitter discussions. It is on Twitter that the fragmented nature of audiences affords us a glimpse of the fragmentation of sociolinguistic stratification, with ‘standard’ (i.e. ‘elite’) norms competing with demotic ones. Within the latter, errors are not just normal or acceptable, they are prestigious and emblematic, as we could see in figure 11. The errors are there for a good reason: they iconicize the perceived ‘big’ divisions in US society and the perceived exclusion of ‘ordinary’ people from major public debates. Trump’s errors are icons of the voice of such ‘ordinary people.
We see a complex, polycentric sociolinguistic system here, in which specific norms can dominate specific segments of the public domain while they are being fundamentally challenged in other segments. Social media such as Twitter make this polycentricity and its restratifying features abundantly clear: they are a veritable lab for examining sociolinguistic normativity, debates and contests about normativity, and innovations in that field (cf. Blommaert 2018; Seargeant 2019).
For sociolinguistics as a science, this means that the supposed stability of stratified sociolinguistic systems – with minorities and majorities clearly demarcated by lines of objective power – needs to be critically revisited, empirically as well as theoretically. In the online-offline nexus, heteronormativity is not an exception, but a rule among segments of the users’ communities. These segments now have acquired public channels of communication, making previously invisible and disqualified demotic forms of language and literacy available for uptake, and turning them into prestige-carrying varieties demanding respect and public recognition. This new politics of language is expertly used by politicians such as Trump as well as by other powerful political and economic actors: the play of stratification and restratification is at the heart of several very large processes of social change, and requires a sociolinguistic analysis that does justice to its complexity.
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When it comes to the way she speaks, a woman’s place is in the wrong. It’s a point I’ve made frequently on this blog, and last week brought a reminder of how true it continues to be. On the same day I published a post inspired by criticisms of Greta Thunberg’s ‘strident’ speech to the UN Climate Action summit (‘strident’ being a code-word for women who express their views in an ‘excessively and unpleasantly forceful way’), the Times Education Supplement published a piece complaining that women don’t speak forcefully enough. It started like this:
“I’m sorry, I’m no expert on this but could we possibly…”
Have you ever heard yourself say something like this to your team?
I certainly have and I cringe to think how I must have come across.
Such phrases can make women appear weak or ineffective to colleagues, which in turn may affect whether they…
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