Semantic and lexical specifics of the emotives, nominating sadness in English

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Abstract

The article addresses a vital issue of nominations of human emotional state of sadness in English. As a part and parcel of daily life and communication, emotions are intrinsically connected to human linguistic behaviour. The research adheres to the anthropocentric paradigm that governs multiple research areas currently, thus making it relevant. Moreover, a combination of the methods used, namely, semantic, lexical, contextual, distributional analysis, combined with online tools and corpora, contributes to the research relevance. Given many triggers of the emotional state people face with on daily basis, the problem of nomination of emotions and finding reasons that lie behind them is a one of the ways to deal with it. The article aims at revealing the semantic and lexical peculiarities of the emotives, nominating sadness in English with reference to their contexts. 40 linguistic units, nominating sadness in English were collected from the dictionaries. About 1000 example sentences were elicited from corpora. The research was implemented in four stages. The structural classification reveled prevalence of verbal emotives with preposition of KV+prep+A type. Further, we focused on the combinatorial features of the emotives based on the British National Corpus texts and Google NGram viewer tool. The verbs ‘be’, ‘feel’, ‘get’ are more common to collocate with the emotives under study. The semantics of the emotives is extended by the introduction of the semes ‘increase’, ‘decrease’ and ‘absence’ of a wide range of sadness’ triggers. Google NGram newspaper texts tend to resort to the emotives for the nomination of economic and political bodies rather than individuals.

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Introduction

The nominations of emotions, i.e. emotives, have been studied in numerous research works within various branches of linguistics [Apresyan 1995; Pennenbaker 1997; Grondelaers, Stefan, Geeraerts 1998; Wierzbicka 2009; Stange 2016; Ulrike 2016 Volkova, Panchenko 2018; Zhabotynska, Slyvka 2020]. We follow the theories of Shakhovsky and define emotives as ‘linguistic units with an emotive component in their meaning’ [Shakhovsky 2009]. Emotiveness is regarded as a linguistic equivalent of emotionality [Andreeva 2020].

Emotions may be nominated directly and indirectly, i.e. descriptively [Apresyan 1995; Shakhovsky 2009]. Some researchers claim that direct nominations of emotions are not regarded as emotive as they nominate an emotion itself, but not a person in a state of emotion [Apresyan 1995]. Babenko argues that, descriptive or metaphoric emotives are units that describe personal state of emotions [Babenko 1989]. People encounter multiple triggers of sadness daily. Thus the problem of verbalizing the emotional state is of great value and significance. The study of lexical and semantic features of the emotives nominating sadness in English (hereinafter ENSE) may shed the light on the nature of this emotion.

Authors view context as a tool to research and uncover the peculiarities of emotives’ semantics [Uchida 1997; Naciscioine 2010; Sternin, Salomatina 2011; Nemcova 2013]. A contextual study of ENSE may be regarded as a research niche.

The anthropocentric linguistic paradigm which currently predetermines large number of research works makes present study relevant due to the nominated personal emotional state of sadness. The research novelty comprises the application of multiple methods and approaches, namely, lexicographic, semantic, contextual to find semantic, lexical and contextual feature of the ENSE [Andreeva 2015; Andreeva 2019].

The research aims at revealing the semantic and lexical specifics of the ENSE based on their contexts in the texts of the BNC and Google NGram viewer.

The aim sets the following research tasks: 1) to elicit ENSE from the dictionaries; 2) to perform structural classification of the ENSE distinguishing one-word emotives and word combinations; 3) to find contexts of the ENSE in the BNC and register them; 4) to analyze the word combinations with the ENSE in the revealed BNC texts; 5) to determine additional meanings of the ENSE based on their syntactic contexts registered; 6) to analyze the distribution of the ENSE in the sources and, in particular, in newspapers uploaded into Google NGram viewer tool; 7) to compare the semantics of the ENSE.

The last decades are marked with the increased interest of the research in the anthropocentric notions, namely nominations of emotions and emotive metaphors [Barchard, Grob, Roe 2017; Marmolejo-Ramos 2017; Smirnova, Cumming, Sloeva, Kuvshinova, Romanov, Nosachev 2018]. Barchard et al. suggest that figurative means are helpful because ‘it is often the easiest way to explain abstract concepts such as emotions’ [Barchard, Grob, Roe 2017]. Their experimental data proves that metaphorically sadness is compared to something being ‘down, dark, blue, and empty’ (e. g. I feel down, He is down in the dumps; my spirits sank) [Barchard, Grob, Roe 2017]. Kövecses et al. performed the experiment analyzing the lexical components and collocations with the emotive metaphors and determined the patterns, namely, fear is associated with cold (have cold feet, cold shiver) [Kövecses 2013]. The descriptor of the emotional state was also researched by the questionnaires. Waggoner surveyed the Americans about their ‘emotion-temperature’ correspondence [Waggoner 2010].

The correlation of the literal and figurative meanings was highlighted by both Russian and foreign researchers [Lakoff, Johnson 1980; Uchida 1997; Hanks 2004; McGlona 2007; Amosova 2013; Baeva 2021]. The authors highlight that the lexical form and meaning of an emotive metaphor correlate with the extralinguistic information used to coin it [Dobrovol’skij, Piirainen 2010]. The indicated correlation corresponds to the terms of the ‘source domain’ and the ‘target domain’, introduced by Lakoff and Johnson [Lakoff, Johnson 1980].

To study word semantics researchers traditionally resort to the structural approach [Espinal, Mateu 2010; Naciscioune 2010]. In the paper we follow theories of Sternin and reveal core, peripheral and potential semes in the structure of an emotive. By a seme we understand ‘a minimal component of the meaning’ [Naciscione 2010]. The core seme aids differentiating word’s semantic fields. The peripheral semes reveal differences in the meaning of emotives [Novikov 2021]. The potential semes of the emotives are found in the contextual study.

 Amosova described the syntactic context in the following way ‘a semantic implementation of a word, regardless of the lexical meanings of the words included in this construction’ [Amosova 2013]. Researchers highlight the significance of the context when analyzing metaphors, namely due to the meaning extension [Andreeva 2020].

Moreover, contextual information is a reliable tool to uncover the collocations with ENSE. The structural approach introduced by Arakin [Arakin 2005] implies that a word combination contains a core word (hereinafter K (Kernel)) and an adjunct (hereinafter A). The two may be represented by a wide range of parts of speech, namely, n (noun), v (verb), d (adverb), a (adjective), and prep (preposition).

The research comprised 4 stages, accorded with the following research questions (RQ):

RQ1: What are the structural types / patterns of the ENSE?

RQ2: What are possible collocations with the ENSE?

RQ3: What additional meanings are found in the contextual study of the emotives?

RQ4: What is the distribution of ENSE in the mass media texts?

Materials and methods

The research material comprises 40 emotives elicited from the dictionaries (Slang dictionary; Rebrina 2017; MIL). Moreover, to study contextual specifics of the emotives, we resorted to the political, sociological, cultural and media texts registered in the British National Corpus (BNC). All the texts obtained were codified by the authors. In total we registered approximately 1000 texts.

The BNC was compiled by Oxford University press in the 1980s – early 1990s, registers about 100 million of text from various genres (namely, fiction, spoken, newspapers, magazines, and academic). All the example sentences were obtained from the British National Corpora.

Google NGram Viewer online tool was used to determine the frequency of the collocations with the emotives under study. The online tool rests on the Google books and shows the frequency of word usage both graphically and contextually.

The research rested on the following methods: description, elements of statistical analysis, lexicographic, semantic and distributional analysis.

 

Results and Discussion

At the preliminary stage of the research 40 ENSE were elicited from the dictionaries (Slang dictionary; Rebrina 2017; MIL).

At Stage 1 we grouped the emotives according to their structural type and distinguished between one-word emotives and emotive word combinations. There are eight one-word ENSE. E.g. arsey, sad, gloomy, gutted, disappointed, mardy, a person, who gets disappointed easily. The revealed emotive word combinations were accorded with the structural theory of Arakin [Arakin 2005]. For example, the emotive ‘be miffed’ is marked as Kv + Ad (see Table 1).

Table 1

The structural types of word combinations

Таблица 1

Структурные типы сочетаний

 

Structural type

Number of emotives

Verbal word combinations

Kv + prep + A

12

Kv + A

11

Nominal word combinations

A + Kn

4

Kn / a + A

3

A + prep + Kn

1

 

 

As Table 1 suggests, the prevailing number of word combinations belong to the verbal type (23)[1] of the structural pattern with preposition ‘Kv + prep + A’ (12). E.g. to be in the doldrums, to be in bad mood, sad; to be in low water, to be sad and depressed; to be under water, to be disappointed, wrecked, sad; to be down in the dumps, to be sad.

Revealed verbal combinations also represent pattern ‘Kv + A’ (11) and may be exemplified by the following emotives: fret oneself to fiddle strings, to torture oneself, to make oneself sad; to have a scrubbed hammock face, to have very sad, dismal face; to be high and dry, to be left in trouble, in sad state.

Nominal word combinations (8) fall into two structural types: ‘A + Kn’ (4) – wet blanket, a sad person, who does not want to be entertained; dull fish, a sad person; stormy petrel, a person, who causes sad things to occur; and ‘Kn / a + A’ (3) – wet as a shag, a sad person, who looks miserable; rock happy, a person, who is sad due to long stay away from home; face as long as fiddle, a sad face.

At Stage 2 the collocations with the ENSE were determined based on the texts of the BNC.

The emotive down in the dumps, sad person is found in 18 contexts in the BNC. The emotive, primarily, is preceded by the verbs be (9), feel (4), have, press modifiers a bit (3), really (2), constantly, positively, pretty, right, so. E.g. ES1[2] ‘<…> so, he said that she's feeling a bit down in the dumps and quite moody’ (BNC), ES4 ‘<…> they lose it's makes you feel right down in the dumps’ (BNC) (see Fig. 1).

The emotive wet blanket, a sad person, who doesn’t want to entertain functions in 17 texts in the BNC. It collocates with verbs be (4), imagine as, resemble, modifiers such as real (3), middle aged (2). E.g. ES8 ‘<…> a proposal so bizarre that it should be accounted for by a motive, not to have at dinner a famously silent person, imagined as a wet blanket’ (BNC), ES12 ‘Most of the older boys agreed with Jack and believed that Piggy was a middle-aged wet blanket because he always thought he knew best about everything’ (BNC).

The emotive in the doldrums, sad and depressed is used in 59 texts in the BNC. The emotive is preceded by verbs be (18), remain (4), seem (2), nouns season, period, decade, months, country, industry, economy, discipline, markets, prices, music, policy. E.g. ES4 ‘The mortgage market has been in the doldrums for three years and lending is shrinking steadily’ (BNC), ES10 ‘The Petroleum sub-sector began the decade in the doldrums, having lost much of its traffic due to reduced demand and surrendered further flows to long-distance pipelines’ (BNC).

The emotive high and dry, abandoned in trouble and sad is used in 51 texts in the BNC. The emotive is preceded by verbs leave (28), be (3), catch, expose, pronouns (6). E.g. ES20 ‘If he hadn't rattled her so much the other day, leaving her high and dry to sneak off and join his girlfriend’ (BNC), ES25 ‘We were caught , high and dry’ (BNC).

At Stage 3 we focused on the semantics extended due to contextual specifics of the emotives under study. We shall exemplify the implemented procedure by three emotives given their frequency in the BNC texts.

 

Additional meanings revealed for the emotive ‘high and dry’

The meaning of the emotive high and dry is explained in 51 contexts of the BNC belonging to commerce, fiction, sport, science and media genres. In particular, in ES7 emotive is objectified reasoned by the cessation of services. E.g. ES1 ‘And for the thousands of chatline users who will be left high and dry when their service shuts down in April, Dr Derek Milne predicts a further search for support’ (BNC).

A person is described as high and dry as he / she has no money left. E.g. ES10 ‘The money, however, always disappears leaving the professional high and dry and minus a considerable sum of money’ (BNC).

The emotive is used in the meaning of ‘no chance of competing’ due to achievements of other people in ES40 ‘Darren Gawley claims he was left high and dry and unable to compete in yesterday's British Championship because of Robert Dunlop's win in the 125cc class’ (BNC).

 In ES43 the emotive is implemented in the meaning ‘lack of variation’. E.g., ES45 ‘There is a real danger in only doing the classical things you're OK with it for a time, but then you're left high and dry when fashion moves on’ (BNC).

 

Additional meanings revealed for the emotive ‘down in the dumps’

The emotive down in the dumps functions in 18 texts in the BNC, namely in fiction, prose, tabloids, and newspapers genres.

In ES5 the woman is down in the dumps as she is scared of staying at a certain place on a festive occasion. ES5 ‘She supposed she was feeling a bit down in the dumps, apprehensive too about celebrating Christmas Day at the Danbys’ (BNC).

The aging process triggers sadness in a 40-years-old person in ES7‘I'm 40 years old and feel really down in the dumps’ (BNC).

In ES10 a man is sad as he has no or little achievements at his work thus resulting in no professional growth. ES10 ‘At times he was really down in the dumps. He'd complain that all the work he was doing didn't seem to be making him any bigger’ (BNC).

High prices make person feel sad in ES13 ‘If you are constantly down in the dumps over the price of fleecewear then this may be the answer to your prayers’ (BNC).

 

Additional meanings revealed for the emotive ‘in the doldrums’

The emotive in the doldrums is used in political, economical, fiction, sciences texts in the BNC. In ES4 the emotive is used to describe a person who is sad due to lack of equipment. ES4 ‘<…> modern well-equipped schools are for science, while arts schools struggle along in the doldrums, where neither teachers nor pupils will want to be’ (BNC).

The meaning ‘poor sport achievements’ is objectified in ES11 ‘Scotland has been in the doldrums of international competition for years, only able to raise its game in occasional moments of glorious defeat as in the last European Championship’ (BNC)].

In the ES15 the company is high and dry as it is poorly capable of keeping up with the competitors. ‘Unilever was still in the doldrums over fears that some of its brands will suffer in price wars’ (BNC). Semantic structure of the ENSE was expanded by additional meanings revealed in the BNC texts (see Table 2).

At Stage 4 we studied the collocations and frequency with three most frequent ENSE (see Stage 3) in the sources registered in Google NGram Viewer (see Figure 2). We resorted to the books, magazines, media texts and video titles.

Interestingly, the vast majority of the collocations revealed in the BNC texts for ENSE were also functioning in the Google NGram texts. However, surprisingly, there is the wide range of newspapers and magazines headlines and titles of the songs, pop bands which contain the ENSE under study. In particular, the emotive high and dry, which is the most frequent on the graph (Fig. 2) is used to name songs, music groups, books by Guy Pearse (2007), Sarah Skilton (2014), Sasmit Powale (2019) and many others.

In the texts of newspapers the emotive down in the dumps refers to person and is used with the verbs be (20), get (14), feel (10). E.g. ‘A Winnipeg anthropologist is down in the dumps these days, searching for clues to Canada's past’ (Google NGram).

NGram viewer texts containing the emotive in the doldrums often refer to the economical, commercial and industrial contexts rather than describing single person. E.g. ‘<…> the increase in NPLs was due to the economy being in the doldrums’ (Google NGram), ‘The labor market, which had been stuck in the doldrums over the last three years, has been showing strong signs recently that it is getting back in the groove’ (Google NGram).

Conclusion

According to the obtained results the most frequent structural patterns of the ENSE are verbal word combinations with preposition. One-word emotives are, primarily, participles, nominating sad person.

The research revealed that emotives are preceded, mostly, by verbs both in the BNC texts and the newspapers registered in the Google NGram viewer tool. The latter, however, provides more diverse application areas, encompassing book titles, newspaper headlines, songs and music groups. According to NGram search, the emotive in the doldrums is more frequent for the description of industrial and economical entities than people.

The significant number of additional meanings of the emotive high and dry contain potential seme ‘absence’, in particular, absence of services, money, competition, variation. The semes ‘increase’ and ‘decrease’ are added to the emotives down in the dumps and in the doldrums. Based on the BNC texts, the former is triggered by decreased achievements, increased fear, age and prices. The latter nominates the person who is sad due to decreased achievements, competitiveness, and absence of equipment.

The research perspective comprises the extension of the research material. In particular, the developed algorithm may be applied to the study of emotives nominating both positive (joy) and negative emotions (fear, anger). Furthermore, corpora study may be limited to a specific sub-corpus, i.e. science, fiction, media. Cross linguistic studies may also contribute to the topic.

 

 

[1] Hereinafter the numbers in brackets indicate the frequency of ENSE in the given group. Frequency rate 1 remains  unmarked.

 

[2]  The contexts elicited from the BNC were registered and coded. The code consists of letters ES, which stand for ‘example sentence’ and a number.

 

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About the authors

M. I. Andreeva

Kazan State Medical University

Author for correspondence.
Email: lafruta@mail.ru
ORCID iD: 0000-0002-5760-0934

Candidate of Philological Sciences, associate professor of the Department of Foreign Languages

Russian Federation, 49, Butlerov Street, Kazan, 420012, Russian Federation.

D. Z. Gaynutdinova

Institute of International Relations, Kazan – Volga Region Federal University

Email: key691@yandex.ru
ORCID iD: 0000-0003-4684-6063

Candidate of Philological Sciences, associate professor of the Department of European Languages and Cultures

Russian Federation, 18, Kremlevskaya Street, Kazan, 420008, Russian Federation.

A. T. Galiakhmetova

Kazan State Power Engineering University

Email: albinagal2601@mail.ru
ORCID iD: 0000-0003-1477-9038

Candidate of Pedagogical Sciences, associate professor of the Department of Foreign Languages

Russian Federation, 51, Krasnoselskaya Street, Kazan, 420066, Russian Federation.

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