Corpus-based analysis of French and English neologisms in media discourse

The study of discourse is of significant interest to researchers. The main principles of the study of discourse are related to the French school, which combines historical, philosophical, and psychoanalytic aspects. The study of discourse allows researchers to learn the language as a means of transmitting a worldview in an analyzed social context. Media discourse plays an important role in creating public opinion, which is emphasized in M. Edelman’s lin-guopolistic concept, presuming that any language can shape social moods and that the choice of lexical units can have manipulative aspects. Therefore, the problem of choosing lexical means is still pertinent, and neologisms have recently become subjects of linguistic research [Edelman 1985; Edelman 2013]. I. A. Vorobyova studied the degree of influence of neologisms on sociopolitical changes [Vorob'yova 2019]. V. I. Zabotkina, J. Anderson and K. Malm-kjær explored the peculiarities of the terminology associated with neologisms [Zabotkina 1982; Anderson, Malmkjær 1995]. I. V. Skuratov established the typology of neologisms in modern French and analyzed them from the standpoint of sociolinguistics [Skuratov 2006]. Despite increased interest, the problem of methodology for studying neologisms remains relevant because of the variability of the language.

Linguistic corpora serve as a source of information regarding the number of occurrences of lexical units. It also provides the context in which words are used. The implementation of corpora helps in gaining access to the culture and ideology of the studied language. The corpus-based approach reveals the linguistic features of the text; it contains quantitative data on the grammatical, stylistic, and syntactic attributes of lexical units.

This article aims to study how a corpus-based approach can be applied to analyse neologisms in French and English media. Within the scope of this study, neologisms were analyzed in relation to the context and means of their formation. Another purpose of this research is to create a frequency list of common neologisms in the French and English media.

Literature Review

The term “discourse” is applied in several fields of modern science, such as philosophy, sociology, literature, and linguistics. Currently, there are several approaches to defining this term. In American linguistics, discourse is considered a connected seg- ment that is longer than a sentence [Anderson, Malmkjær 2006]. Discourse is closely related to the use of language in various social contexts as well as the interactions between participants of the speech act. Discourse is associated with the French School because it merges the historical, philosophical, and psychoanalytic aspects of this phenomenon [van Dijk 1998]. In linguistics, discourse describes the use of the language in its models and dynamics. The theory of discourse was developed by P. Serio and T. van Dijk [Serio 2002; van Dijk 1998]. T. van Dijk introduced cognitive discourse studies and mentioned that discourse is a communicative event, considered as a combination of linguistic form, cognitive structure, and speech act [van Dijk 1998]. In Russian linguistics, there is a similar definition of discourse; it is regarded as a complex communicative event that includes the text itself and extralin-guistic factors, such as the speakers’ intentions and points of views [Karaulov 1981].

Media discourse is connected to political discourse as it aims to report and comment on information about events that occur in society, including political aspects. Therefore, media discourse plays an important role in sharing public opinion and political situations [Filippovich, Prokhorov 2002]. M. S. Kardumyan suggests that media discourse and political discourse have several similar features; for example, they both target mass audiences and aim to describe cultural contexts. Another feature of political discourse is that it is situational and media discourse [Kardumyan 2010]. According to American politologist Murray Eidelman, political language is the “language of the political phenomena that take place in society” [Edelman 1985: 34]. At the same time, he believes that this term is not only a means of nomination and description of political actions but is also considered a part of them. Later, Russian researchers introduced a wider explanation of this term; for instance, T. V. Kisileva points out that political language is a special subsystem of the national language used in political communication, and the vocabulary of the language reflects socio-political processes [Kisileva 1997; Rozen 2009].

Ozhegov’s dictionary defines neologisms as “new words or expressions as well as the new meaning of an old word” [Ozhegov 2000: 487]. Russian and foreign researchers have provided similar definitions. For example, V. I. Zabotkina suggested that neologisms are lexical units that combine the novelty of form and content [Zabotkina 1982]. According to J. Anderson and K. Malmkjaer, neologisms have recently been introduced into language vocabulary. A lexical unit should be understood as any type of lexeme including single-word units, multiword expressions, and abbreviations [Anderson, Malmkjær 2006; Bragina 1973, Lopatin 1973].

Material and methods

Corpus linguistics is a branch of modern linguistics that has developed rapidly and continuously. This includes the implementation of corpora to analyze textual data. M. S. Kogan, V. P. Zakharov, N. V. Popova, N. I. Almazova study the impact of corpus linguistics in language teaching in Russia’s educational context [Kogan et al. 2020; Zakharov et al. 2020]. The authors considered corpora as part of the Data-Driven Learning (DDL) approach, which requires quantitative data to prove theories [Chujo et al. 2012; O'Halloran, 2010]. At the same time implementation of corpora can be divided in two different approaches: Corpus-Based Approach (CBA) and Corpus-Driven Approach (CDA). The corpusbased approach is deductive because it uses corpora to test the hypotheses. According to V. P. Zakharov, corpus linguistics is not just a methodology but also a distinct scientific field that is in the process of development. This can also illustrate its dual nature. On the one hand, corpus linguistics studies methods and approaches of implementation of corpora [Biber, Finegan 2014]. On the other hand, corpus linguistics develops a process for creating corpora [Kogan et al. 2020].

The study of neologisms can be challenging because these lexical units are not widely represented in general languages, and the implementation of corpora overcomes this challenge as it provides patterns and lexical units in context, which helps to analyze not only the word itself but also the context. J. Firth paid special attention to context and semantics; according to him, words should be studied in context [Firth 1949].

Néoveille was used to perform a quantitative analysis of the French neologisms. Néoveille is a platform that automatically detects neologisms in a dynamic corpora. This platform was introduced in 2015 as a collaboration between several universities, such as the COMUE Sorbonne Paris Cité and the University of Sao Paulo. Néoveille supports seven languages (French, Greek, Polish, Portugal, Czech, Chinese, and Russian) [Cartier 2017]. The main advantage of dynamic corpora is the possibility of retrieving the relevant information. The general architecture of Néoveille aims to reproduce language discourse flow. The platform collects text data from web sources and performs pre-processing.

WebCorp was used to retrieve data and information about the absolute frequency of lexical units presented in New Words by Cambridge dictionary. WebCorp was developed by the Research and Development Unit for English Studies at the University of Central England, Birmingham. This allows the users to obtain raw data from the web. WebCorp is a dynamic corpus that can process journalistic texts chronologically and provides a large amount of information about contemporary language, which allows the analysis of the frequency of occurrences of neologisms [Renouf, Kehoe, Banerjee 2007].

Results

Internet neologisms can be considered a new lexical unit; they affect the linguistic expression of objective reality and are constantly changing under the impact of a new means of communication – the Internet. During the study, the frequency of Internet neologisms was compiled and analyzed. This list includes lexical units that have appeared in the French media discourse over the last five years.

Table 1

Top 26 neologisms of 2022

Rank	Lexical unit	Frequency
1	personnes-années	2522
2	demies-journées	2207
3	grande-reporter	1709
4	tout-mots	799
5	voiture-parking	589
6	effet-prix	587
7	ateliers-conférences	484
8	personnels-résidents	136
9	vidéo-témoin	133
10	pair-impair	128
11	médecin-infectiologue	128
12	sous-reconnus	117
13	sous-blocs	101
14	quasi-membre	96
15	bar-boutique	80
16	tours-bus	78
17	pseudo-théories	37
18	pain-chocolatine	27
19	mi-pompe	27
20	débunkées	26
21	élèves-journalistes	25
22	squirts	23
23	couvert-bar	21
24	tchéco-russes	18
25	non-égalitaires	17
26	weezevent	16

Table 1 contains information about the 26 most frequent neologisms in the modern French media discourse in 2022. The most frequent neologisms are: personnes-années (2522), demies-journées (2207), grande-reporter (1709), tout-mots (799), voiture-parking (589), effet-prix (587), ateliers- conférences (484). The least frequent neologisms are: weezevent (16), non-égalitaires (17), tchéco-russes (18), couvert-bar (21), squirts (23). The most commonly used lexical unit is personnes-années (2522), it is found in Le Journal de Québec, Futura Sciences, Science et Avenir, Le Journal de Montréal, Sience et Santé, Le Monde, La Croix, Libération, Le Point, Midi Libre. This neologism is formed through compounding. Some examples of the lexical unit use are presented below:

• (1)    Cette différence est encore plus spectacu-laire dans la population âgée de plus de 80 ans : alors qu’il y a 420 décès pour 10 000 personnes-années chez les non-vaccinés, seulement 14 décès pour 10 000 personnes-années sont observés chez les doublements vaccinés, soit 30 fois moins [Bé-liveau 2021].

The neologism personnes-années is used to refer to people of older age, when analyzing the examples, it can be assumed this expression belongs to topic of science and medicine, this lexical unit can be considered politically correct. The lexical unit demies-journées refers to the theme of sport and it is found in media like Sportregions.fr, Le Journal de Saone et Loire Réinitialiser, Le Dauphiné Libéré Réinitialiser, Sud-Ouest Réinitialiser, La voix du nord. This neologism was also formed by composition. However, not only were French lexical units used in compound neologisms, but also borrowings from other languages. For example, the neologism voiture-parking is formed as a result of the compounding of the French noun la voiture and the English noun parking. This lexical unit appears in the following media resources: Le Dauphiné Libéré, L'Indépendant, La Dépêche de Kabylie, L'Express, Le Figaro, Le Télégramme, Midi Libre, Santé Magazine, L'Est Républicain.

It is presumed that the most common ways to form Internet neologisms in French media discourse are by compounding and borrowing. At the same time, the origin of borrowing lies not only in English. For example, the neologism liquamat originates in Greek, which is also found in Courrier International. An example of the use of this term is presented below:

• (2)    La lokma [aussi appelée luqaimat, ou loukoumas en Grèce], est généralement dégustée après l’iftar [la rupture du jeûne] et la prière de tarawih [Courrier International 2022].

Nevertheless, the most common are borrowings from English. For example, the lexical unit sciencefiction is formed as a result of the compounding of two English nouns, science and fiction .

• (3)    Ce mardi en avant-première dans "Sur vos écrans", le podcast ciné/séries de L'Indépendant, on vous conseille "Le visiteur du futur" la comédie de

  science-fiction du jeune réalisateur de 37 ans François Descraques qui rajeunit le cinéma français [Bonet 2022].

Table 2

Top 20 neologisms from 2016 to 2022

Rank	Lexical Unit	Frequency	Date
1	cookie	31797	18.03.2016 18:13
2	smartphone	26273	10.05.2017 15:37
3	qualif	16371	21.03.2016 06:27
4	adopters	16070	25.03.2016 16:35
5	coaching	13087	18.03.2016 18:12
6	loi-travail	12043	24.03.2016 16:29
7	appart	10626	18.03.2016 18:13
8	brexiters	10099	09.05.2016 12:21
9	reporting	9803	18.03.2016 18:13
10	composable	9081	06.06.2016 12:10
11	revendable	8055	06.07.2016 12:17
12	instagramable	7297	11.08.2016 06:19
13	provoc	4988	21.03.2016 00:43
14	sollicitable	4807	18.03.2016 18:13
15	covid	4683	02.03.2020 23:20
16	macroniste	4116	08.06.2016 18:38
17	cybersécurité	3444	25.06.2018 23:15
18	lobbying	3262	21.03.2016 20:30
19	macronistes	3234	22.04.2016 20:35
20	ex-chef	3032	10.05.2017 23:34

Table 2 presents a frequency list of French neologisms that appeared in media discourse from 2016 to 2022. The lexical units were sorted according to their absolute frequency. The most common neologisms appeared in the French media discourse in 2016. The column «Date» contains the date and the time of the first appearance of the neologism in the media, it can be assumed that the most common lexical units are: cookie (31797) , smartphone (26205) , qualif (16371) , adopters (16070) , coaching (13087) , loi-travail (12043) , appart (12043) . The least frequent words were vintagemania (1), sub-genre (1), straping (1), ultrarobuste (1), conseil-marathon (1) , and others. Probably, these lexical units can be considered the author’s occasionalisms since their absolute frequency equals one. The lexical units presented in Table 2 refer to both technology and politics. Neologisms cookie , smartphone , adopters , reporting , coaching , lobbying, and breaxiters appeared as a result of borrowing from English. Word macronistes is formed with the mean of suffixation, this neologism is used in relation to French president Emmanuel Macron, this lexical unit first appeared in media discourse in 2016 during the election.

The online resource of the Cambridge Dictionary New Words was used for the quantitative analysis of neologisms in the English language. This platform publishes daily information about lexical units that have recently appeared in the English language.

Table 3

Top 30 English neologisms in 2022

Rank	Lexical Unit	Frequency
1	liveaboard	1262
2	micromobility	1165
3	effective altruism	961
4	tomato flu	665
5	brown noise	562
6	spiritual bath	547
7	romantasy	401
8	hoverbike	383
9	barkitecture	364
10	superskinny	239
11	inactivist	238
12	motion pillow	218
13	nepo baby	178
14	wearapy	118
15	nap box	114
16	silver exodus	80
17	flying ferry	77
18	sidescraper	56
19	stealth help	49
20	thriftifarian	41
21	sibling novel	33
22	milestone anxiety	30
23	sea allotment	30
25	momtern	28
26	super-smeller	26
27	moth motorway	23
28	scream pot	18
29	disco nanny	2
30	luxury detective	1

Table 3 contains data on the number of occurrences of lexical units, which are sorted in descending order. The most frequent lexical units are: livea-board (1262) , micromobility (1165) , effective altruism (961) , tomato flu (665) , brown noise (562) , spiritual bath (547) . The least frequent neologisms are: luxury detective (1) , disco nanny (2) , scream pot (18) , moth motorway (23) , super-smeller (26) . The most common neologism is liveboat (1262), which appeared in the media in August 2022 and describes people who live permanently on a ship.

• (4)    The couple are currently in Greece, “a seagoing nation” they adore for its free mooring and the warm welcome extended to liveaboards . They dropped anchor on the small island of Meganisi when Covid struck but plan to cruise on towards Turkey. “Loads of liveaboards want to lap the world in five years or whatever,” Natalie says. “But we like to get to know new places rather than mindlessly circumnavigating the globe [Howard 2022].

Analysing the example (5), it can be presumed that the lexical unit liveboard has a positive connotation, epithets free mooring and warm welcome illustrate this, and verbs like adore also contribute to the formation of a positive connotation. The neologism liveboat is created by compounding the verb live and the noun board.

Another example is the neologism micromobility (1165) , which refers to the use of small vehicles for short-distance travel.

• (5)    Micromobility devices may be privately owned but are often shared-use vehicles that are maintained by a municipal government or private entity. Micromobility devices are particularly appealing to residents of densely populated areas, as they provide quick and convenient transportation to nearby destinations such as grocery stores, shops, or entertainment venues [Locke 2022].

The neologism micromobility is formed as a result of prefixation. Table 2 includes not only words but also collocations such as effective altruism. This lexical unit refers to an activist movement and study that aims to develop the best way to help people solve global problems.

• (6)    In the past few years, effective altruism has become the giving philosophy for many Silicon Valley programmers, hedge funders, and even tech billionaires. At its core, effective altruism is devoted to the question of how one can do as much good as possible with the money and time available to them [Kulish 2022].

The collocation tomato flu has also become common recently and describes a disease during which patients experience redness on the skin, which can be considered a metaphorical neologism since the meaning of colour is transferred.

• (7)    Ever since COVID-19 was declared a global pandemic, people have been more concerned than ever about potential disease threats. The newest of these is called « tomato flu », and has affected over 100 children in India, according to a recent correspondence in The Lancet. The authors report that tomato flu , likely a viral disease, was first identified in the Kollam district of Kerala, India on May 6, 2022 [Citroner 2022].

The neologism tomato flu is more often used in scientific discourse than in media discourse, which may be a consequence of the specifics of the topic, suitable for a certain target audience.

The lexical unit of romantasy is formed by compounding two nouns, romance and fantasy . Neologism denotes a genre of books that contains elements of fantasy and romance novels. The word ro-mantasy first appeared in The Book Seller magazine in August 2022.

• (8)    Rosie is a distinctively talented author, and this is a once-in-a-lifetime acquisition. Sixteen Souls is a swoony romantasy where Rosie has intricately plotted a stunning mystery with a fantastically diverse cast of characters. With Rosie’s TikTok platform and job as a bookseller, she has a masterful understand-

  ing of the YA market and is uniquely placed to reach a strikingly engaged readership [Bayley 2022].

The lexical unit romantasy is used in a positive connotation, as indicated by epithets swoony roman-tasy and the hyperbole stunning mystery with a fantastically diverse cast of characters .

The neologism inactivist is formed as a result of affixation using the prefix in- with a negative meaning and the noun activist. This lexical unit appeared in the Nesta magazine in January 2022. The time of its appearance coincided with the period of activity of the environmental movement, which was trying to draw public attention to the problem of the climate crisis. At the same time, the neologism inactivist can be used not only in relation to environmental activists but also to other political and social groups.

Discussion

The results indicated that French Internet neologisms were mostly formed as a result of borrowing and compounding. However, borrowings originate not only from English, but also from other languages. According to the results, lexical units can be borrowed from Greek and Japanese. French neologisms primarily refer to technology and politics. The results demonstrated that among the analyzed examples of English neologisms, there are not only words but also collocations; words are mostly formed with compounding and affixation, and they also refer to technology and politics. The findings provide evidence that the topics of neologisms are broadly comparable in French and English; similar topics are politics and technology. Neologisms extracted from the Néoville dynamic corpus from 2015 to 2022 indicate that the most common neologisms appeared in 2016 [Cartier 2017]. The majority of lexical units corresponding to the topic of technology and political neologisms are also represented.

The results agree well with the previous studies wherein E. Cartier, J. F. Sablayrolles, N. Boutmgha-rine, J. Humbley, M. Bertocci, C. Jacquet-Pfau, N. Kübler, G. Tallarico automatically detected neologisms in the corpus of contemporary French language, according to authors the most productive ways of forming neologisms are: prefixation, compounding, borrowing and suffixation [Cartier et al. 2018]. A similar conclusion was reached by A. Y. Golubeva, who discovered new politically correct lexical units [Golubeva 2019]. French Neologism personnes-années denotes people of older age. This illustrates the tendency to extend politically correct discourse. This correlates with Edelman’s linguopolitical concept. According to this concept, language is the center of social and political processes, as it influences people’s ways of thinking.

The results of this study can be applied to teaching French and English. Frequency lists consisting of neologisms and concordances extracted from media discourse can be used as authentic materials for developing intercultural competence [Galskova, Gez 2005; Nosonovich, Milrud 1999].

Although the corpus-based approach is widely accepted, it suffers from some limitations owing to the data-extraction process. In some cases, there are a certain number of inaccuracies in the linguistic descriptions of lexical units. This limitation can be overcome by manually reviewing data. Another limitation is associated with the architecture of WebCorp, which was used to perform a quantitative analysis of English neologisms [Renouf, Kehoe, Banerjee 2007]. WebCorp only provides users with linguistic data collected from the following search engines: Bing, Bing News, and The Guardian Open Platform, which leads to the compilation of the dynamic corpus with text from a limited quantity of sources. To overcome this limitation, the further development of dynamic corpora is required.

Conclusion

In modern linguistics, language is considered as a complex and constantly changing system, in which the processes of development and improvement do not stop. Changes occur most often in the language vocabulary. The need for change can be explained by the fact that lexis reflects objective reality; it also illustrates the socio-political situation in the country. The linguistic picture of the word demonstrates the changes taking place in society as well as the results of these changes. An analysis of the language development makes it possible to answer the questions about the means of new words formation and the needs of society.

An attempt was made to create frequency lists of the most common neologisms in French and English discourse. Despite these limitations, the corpusbased approach was effective for the quantitative analysis of neologisms. This allowed to obtain information on the absolute frequencies of lexical units and their contexts. Further research is needed on this topic along with the development of dynamic corpora. The current study could serve as a basis for a novel investigation into the implementation of corpus-based approaches in the study of neologisms in media discourse.