International Open Access Journal Platform

1 Introduction

With the continuous improvement of China’s comprehensive national strength and international status, the cooperation between China and the international community has been progressively deepened, drawing exponentially increasing global attention to China’s development. Therefore, how to precisely construct and efficiently disseminate the national image has become a key issue that urgently needs to be solved. The Report on the Work of the Government is a concentrated embodiment of the annual policy program of the Chinese government, covering all-around policy measures and development achievements in economy, politics, culture, society, ecology, etc. It has extremely high authority and representativeness. Its English translation, as a pivotal text for the international community to understand China’s national conditions and development strategies, occupies a core position in international communication and provides a vital platform for China to shape its own image.

The development of corpus-based critical translation studies has brought new opportunities and methods to the research of English translations (Hu, 2017). Therefore, by means of corpus analysis tools, research on the English translation of the Report on the Work of the Government (2023-2024) can deeply explore the lexical and semantic features of its text, and the national image behind the text can be clearly presented.

2 Literature Review

2.1 Research on National Image

An image serves as a discourse construct shaped by the specific social, historical, and cultural context (Leerssen, 2000). The national image, as a pivotal component of a nation’s soft power, functions not only as a strategic resource in international political dynamics but also as a central theme in cross-cultural communication research. It generally comprises two dimensions: self-construction (self-shaping) from an autochthonous perspective and other-cognition (other-shaping) from an external perspective (Chen & Zheng, 2024).

In 1959, the renowned American political scientist Boulding (Boulding, 1959) was the first to propose the concept of “national image,” defining it as the combination of a country’s perception of itself and that of other bodies in the international system. Since then, the conceptual perspective of national image has expanded from the political field to multiple fields, such as psychology, communication studies, economics, etc. Galtung and Ruge (1965) proposed from the perspective of communication studies that the national image should include the media image, and the news media are an important force in shaping the international image. Baloglu and McCleary (1999) deemed that the national image is the sum of evaluations of a particular country based on existing cognition and individual feelings, which further enriches the connotation of the concept of national image from the perspective of epistemology. Chew Ⅲ and William (2006) emphasized that the national image should be analyzed within the historical context, integrating it into a three-dimensional image model encompassing geographical, social, and historical dimensions.

Whether based on the self-shaping perspective or the other-shaping perspective, overseas study focused on the media content on international official discourse and international social platforms. Gong and Firdaus (2024) argued that the keywords described by China Daily regarding the epidemic have changed from the initial “disaster” to “potential opportunity,” highlighting China’s optimistic and positive image. Whyke et al.(Whyke, Chen & Lopez-Mugica, 2022) deemed that the short videos about rural life in China created by Li Ziqi presented the image of diligent, filial and independent Eastern women, which indirectly reflects the mainstream values of China’s pursuit of hard work, dedication and kindness, providing a new perspective for the construction of China’s image. Kimaiyo (2024) found that China has carried out effective soft power output on African media platforms and shaped a positive image of
China.

2.2 Research on China’s national and self-shaping image

Domestic scholars pay more attention to exploring the definition of “national image” from the perspective of social connections, emphasizing that national image should include the evaluation and understanding of multiple subjects. Sun (2002) once pointed out that a country’s image is the understanding and evaluation of its political, economic, social, cultural and geographical conditions by both the internal and external public of a country. A country’s image fundamentally depends on its comprehensive national strength, but it cannot be simply equated with the actual situation of the country. There is often a marked divergence between a nation’s domestic image and its international image. Duan (2007) also emphasized that a country’s image is the overall, relatively stable evaluation and perception of the country itself. The actions and various activities by both the external and internal public of a country reflect a country’s cultural soft power and comprehensive national strength. Li (2006) elaborated specifically on the definitions of internal image and external image, believing that a country’s image is usually composed of internal image and external image. The country itself constructs the internal image to gain attention and support worldwide, while other countries shape the external image, which is usually different from the internal image. The former is the self-perception within a country based on its own positioning in the international community and self-presentation within the international community, while the latter is the comprehensive evaluation and view of a specific country by the governments, institutions or people of other countries.

In recent years, research has gradually touched upon the image of China shaped in the media from other regions. Gao and Zhang (2021) held that the report on China’s anti-epidemic assistance in the New York Times has shaped an aggressive image of China, indicating that the image of China being shaped by others has deviations and misinterpretations in China. Yan (2024) found that the national image of China in Singapore’s diplomatic discourse is mainly reflected as an enterprising and booming economic power. Liu and Mao (2020) adopted the corpus-assisted method and reached the research conclusion that in the content of mainstream African newspaper media, China has multiple image labels such as “powerful China,” “friend or partner-like China” and “worrying China.”

From the perspective of self-shaping, researchers mostly take the official discourse of the Chinese state, works, and the content of the country’s mainstream media as corpora to explore the national image. Xu and Gao (2023), employing an eco-discourse analysis method grounded in systemic functional linguistics, revealed through their research that the discourse on ecological civilization in President Xi’s speeches delivered on major international platforms has effectively shaped a positive Chinese ecological image characterized by responsibility, accountability, and action-oriented commitments. Xie and Wang (2018), pointed out that China’s self-shaping international image needs to be achieved through translation. From the perspective of the attributes of translation itself, its practical process inevitably involves the power relations in discourse practice, thereby reflecting the ideological structure in the broader national economic, political, policy and cultural contexts (Fawcett, 1995). At present, some scholars have combined the corpus research method to explore the self-shaping image of the Chinese state in the translated texts. Hu and Tian (2018a) adopted the corpus method to conduct a comparative analysis of the linguistic features of the English translation of Chinese diplomatic discourse and that of American diplomatic discourse from the perspectives of high-frequency words, key words, the application of modal verbs and the collocation of “we.” This study found that Chinese diplomatic discourse has constructed a diplomatic image of China that is down-to-earth, proactive, and peace-loving. Fan et al.(2024), employing corpus analysis tools to collect and analyze diplomatic addresses from the English translation of The Governance of China, discovered that the English translation systematically constructs four predominant image categories. Song and Lü (2025), through the construction of a parallel corpus of Mo Yan’s novels in Chinese and English, found that the female and peasant images representing the positive image of China in the original text were presented as backward and corrupt images in the translation, which had a negative impact on the dissemination of the image of China.

Previous studies have significantly contributed to the understanding of national image, especially China’s national image. However, there is a lack of in-depth exploration of official government documents, such as the English translation of the Report on the Work of the Government. These documents, as important carriers of a country’s policies and development directions, can provide rich information for analyzing China’s self-shaping image.

3 Research design

3.1 Research subject and questions

This thesis takes the English translation of the Report on the Work of the Government (2023-2024) (referred to as RWG) and the English translation of the Presidential Address to the Federal Assembly (2023-2024) (referred to as PAFA) as the corpus and builds the self-constructed corpora as the research subject. All the texts involved in this research are obtained from official and authoritative channels. The English translation of RWG is obtained from the official website of the State Council of the People’s Republic of China: http://www.gov.cn/, and the English translation of PAFA is obtained from the official website of the President of Russia: http://www.kremlin.ru. The basic details are shown in Table 1.

Table 1 The basic information of the self-constructed corpora

Corpus	Time Span	Tokens	Total
English Translation of RWG	2023-2024	29627	61798
English Translation of PAFA	2023-2024	32171

RWG is the annual work report delivered by the Premier of the State Council of China to the National People’s Congress, and PAFA is the annual report delivered by the President of Russia to the Federal Assembly. The contents of both reports focus on analyzing the current situation of the country, policy directions and plans. They have the same themes, the same time spans, and similar tokens. Therefore, they are relatively comparable as a whole.

This thesis seeks to address the following two research questions:

(1) In comparison with the English translation of Russia’s PAFA, what lexical characteristics are exhibited in the English translation of China’s RWG?

(2) What self-shaping image of China is reflected in the English translation of RWG?

3.2 Research instruments

TreeTagger (3.0) is a professional-level annotation software developed by Helmut Schmid. This study mainly applies two functions. They are the POS tagging function and the Lemmatization function.

AntConc (4.3.1) is a text analysis software developed by Laurence Anthony and is capable of handling large-scale text data, and helps to deeply analyze the patterns and trends of language usage. This study mainly adopts three core functions in AntConc. The first one is Keyword in Context, which can accurately locate keywords in large-scale texts and fully present their context. The second one is Word List. It generates a list of all the words in the loaded corpus. The third one is Keyword List. It identifies words that exhibit unusual frequency (or infrequency) in the given corpus when contrasted with a reference corpus.

3.3 Research methods

Firstly, this study will collect research corpora from the official website to construct two corpora. They are the English translations of RWG and PAFA. Then the text uses TreeTagger to perform part-of-speech tagging and word form restoration on the corpus text. And after that, AntConc is used to conduct specific retrieval and analysis on the corpus texts that have undergone part-of-speech tagging and word form restoration. Lastly, comparative analysis is conducted between RWG and PAFA to reveal the prominent linguistic features of RWG.

4 Results and discussion

Lexis serves as a fundamental constituent for constructing the semantic information within texts. High-frequency notional words can reflect the work or issues that the speaker is concerned about, describe the measures that the speaker often takes, and involve the speaker’s thoughts, ideas, words, and deeds. They can be directly applied to the shaping of the speaker’s image (Hu and Tian, 2018b). High-frequency nouns involve the issues or topics that the speaker is concerned about or interested in, while high-frequency verbs describe the frequent actions or measures taken by the speaker. Keywords refer to words that occur much more frequently than usual compared to the reference corpus. Positive keywords refer to the keywords with a significantly higher frequency in the target corpus, which reflect the thoughts and feelings of the speaker and shape the image of the speaker (Scott & Tribble, 2006).

4.1 China’s self-shaping image through high-frequency nouns

To obtain the high-frequency nouns lists of RWG and PAFA, respectively, the Word List function of AntConc is used with the Regex “_\bN.” The top 25 high-frequency nouns are selected for comparative analysis. The basic information is shown in Table 2.

Table 2 Top 25 high-frequency nouns in the English translation of RWG and PAFA

English Translation of RWG				English Translation of PAFA
Rank	Headword	Number of Occurrences	Norm Frequency	Headword	Number of Occurrences	Norm Frequency
1	development	253	8539.508	year	120	3730.067
2	people	142	4792.925	Russia	117	3636.816
3	policy	142	4792.925	people	111	3450.312
4	government	121	4084.112	country	94	2921.886
5	China	120	4050.359	region	87	2704.299
6	system	107	3611.571	ruble	73	2362.376
7	effort	92	3105.276	percent	72	2269.124
8	percent	83	2801.499	project	66	2238.040
9	service	83	2801.499	government	65	2051.537
10	area	81	2733.993	family	63	2020.453
11	reform	70	2362.71	programme	63	1958.285
12	year	69	2328.957	business	53	1958.285
13	growth	63	2126.439	economy	52	1647.446
14	sector	59	1991.427	development	51	1616.363
15	investment	58	1957.674	time	50	1585.279
16	market	58	1957.674	child	49	1554.195
17	enterprise	49	1653.897	system	48	1523.111
18	Party	48	1620.144	school	43	1492.027
19	economy	48	1620.144	life	40	1336.608
20	support	48	1620.144	state	36	1243.356
21	employment	47	1586.391	area	35	1119.020
22	work	46	1552.638	company	35	1087.936
23	innovation	45	1518.885	today	33	1087.936
24	project	45	1518.885	issue	32	1025.769
25	trade	45	1518.885	fact	31	994.685

According to the above table, RWG and PAFA share some common high-frequency nouns, such as “people,” “government,” “percent,” and their respective country names (“China,” “Russia”). From the perspective of discourse attributes, RWG and PAFA both belong to political discourse texts and have distinct official discourse features. Their discourse subjects, discourse objects and social functions show a high degree of consistency at the macro level. However, texts also show certain differences in the high-frequency nouns list. The noun “development” appears in both, but its usage frequency in RWG is five times as high as that in the PAFA. More crucially, words such as “reform,” “investment,” “employment,” “enterprise,” and “innovation” that frequently appear in the RWG all belong to the core words under the economic theme, but these words are not high-frequency nouns in the PAFA. This strongly highlights that the Chinese government has adhered to taking economic construction as the center and showcases the national image of China that keeps pace with the times and continuously promotes reform and innovation.

It should also be pointed out that words with similar frequency still have certain differences in the semantics expressed in the text. The core noun “people” shares similar frequency in RWG and PAFA. Then this word is used for further retrieval by AntConc. There is a close correlation between semantics and lexical collocation. Collocations are the co-occurrence of two or more words within short distances in a text. The standard span in collocational analysis, defined as a four-word span surrounding the node word, determines the operational range for detecting statistically significant lexical partnerships. The collocations of words mainly fall into two categories: some collocations are eye-catching or interesting because they are unexpected, while others are of great significance in the structure of language vocabulary due to frequent repetition (Pu, 2021). Therefore, with the span set to L4-R4, the Collocate function is adopted to conduct a systematic investigation of the lexical collocation network of “people.” To enhance the visual representation of the research, the word cloud technology is simultaneously used to generate the collocation network cloud Figure 1 and Figure 2 of the RWG and PAFA corpora. Among them, the vocabulary sizes are positively correlated with the Mutual information (MI) value. MI value is a commonly used measurement method in the field of information science. It is now employed in the study of word collocation to measure the collocation strength between words. The MI value calculates the probability information about the occurrence of another word that can be provided by the frequency of one word’s appearance in the corpus. The difference in MI values indicates the different intensities of word collocation. The higher the MI value, the higher the collocation intensity of the word with the search term (Wei, 2002).

Figure 1 The collocation network cloud of “people” in the English translation of RWG

Figure 2 The collocation network cloud of “people” in the English translation of PAFA

Based on Figure 1, the English translation of RWG has constructed a multi-dimensional “people” semantic network. In the dimension of people’s livelihood, the collocation words “wellbeing,” “life,” “need,” “basic,” and “meet” form a continuous semantic chain, highlighting the Chinese government’s emphasis on the institutional guarantee construction for the basic needs of the people. In the dimension of social groups, the collocation “young” points to the youth development policy, and the collocation “disability” points to the social assistance system for the vulnerable, demonstrating the key attention of the Chinese government to the young and special groups. In the dimension of national defense and security, the collocation words “armed” and “force” reflect the investment of the Chinese government in the modernization of the armed forces of the people’s army, showing China’s emphasis on the construction of national defense forces. The multi-dimensional “people” semantic network collectively shapes China’s image, which is characterized by safeguarding basic livelihoods, supporting vulnerable groups, empowering youth development, and prioritizing national defense and security. In contrast, based on Figure 2, the English translation of PAFA forms a single semantic collocation with “young,” and its combination with the network presents a significant one-dimensional feature, focusing more on the power of young people.

4.2 China’s self-shaping image through high-frequency verbs

In order to obtain the high-frequency verb lists of RWG and PAFA, respectively, the Word List function of AntConc is used with the Regex “_VV.” The top 25 high-frequency verbs are selected for comparative analysis. The specific situation is as shown in Table 3.

Table 3 Top 25 high-frequency verbs in the English translation of RWG and PAFA

English Translation of RWG				English Translation of PAFA
Rank	Headword	Number of Occurrences	Norm Frequency	Headword	Number of Occurrences	Norm Frequency
1	improve	171	5771.762	do	95	2952.970
2	promote	140	4725.419	like	81	2517.796
3	ensure	115	3881.594	include	70	2175.873
4	make	112	3780.336	make	67	2082.621
5	increase	75	2531.475	need	56	1740.698
6	develop	72	2430.216	say	64	1678.530
7	implement	68	2295.204	build	47	1460.943
8	build	65	2193.945	take	45	1398.775
9	continue	62	2092.686	use	42	1305.524
10	take	61	2058.933	create	41	1274.440
11	support	57	1923.921	know	41	1274.440
12	work	56	1890.168	work	41	1274.440
13	strengthen	55	1856.415	support	39	1212.272
14	provide	49	1653.897	increase	38	1181.188
15	expand	47	1586.391	continue	37	1150.104
16	keep	47	1586.391	ask	32	994.685
17	enhance	46	1552.638	expand	31	963.601
18	advance	45	1518.885	go	30	932.517
19	boost	38	1282.614	let	29	901.433
20	launch	38	1282.614	ensure	28	870.349
21	see	38	1282.614	launch	27	839.265
22	adopt	34	1147.602	develop	26	808.181
23	meet	34	1147.602	give	26	808.181
24	pursue	33	1113.849	see	26	808.181
25	remain	33	1113.849	start	25	777.097

As can be seen from the above table, in the English translation of RWG and PAFA, some high-frequency verbs are the same, such as “develop,” “increase,” “continue,” etc. However, the frequency of these same high-frequency verbs in RWG is much higher than those in PAFA. In addition, among the high-frequency verbs in PAFA, there are also many delexicalized verbs with rather general meanings, such as “do,” “say,” “go,” “let,” etc. Delexicalized verbs, also referred to as light verbs, are characterized by their broad collocational ranges and adaptability across diverse contexts. These verbs are polysemic, acquiring context-specific meanings through combinations with varying lexical items. The meanings of these verbs themselves become semantically weakened, making them challenging to be interpreted precisely. To convey the clear meaning, these verbs rely heavily on the surrounding words they are combined with. This dependency on context is why they are labeled “non-lexicalized verbs”(Hu & Liu, 2016). And such delexicalized verbs are rarer in the RWG corpus.

RWG also includes high-frequency verbs such as “promote,” “strengthen,” and “enhance.” These verbs have the following two main characteristics compared with the delexicalized verbs: (1) The semantic implications of these verbs involve critical evaluation and judgement of existing conditions, reflecting that there are still deficiencies for improvement in the current situation, and further pointing to the positive role of the measures corresponding to these verbs in improving the current situation; (2) The concrete tasks associated with these verbs are typically characterized by long-term objectives, requiring consistent and dedicated efforts to achieve sustainable outcomes. To further understand the semantics expressed by these verbs, the high-frequency verbs “promote,” “strengthen” and “enhance” are used as search terms, and the Keyword in Context function is used to randomly extract the relevant index lines in the RWG corpus. The details are shown in Table 4.

Table 4 Relevant index lines of “promote,” “strengthen,” “enhance” in the RWG corpus.

Left Context	Hit	Right Context
tutoring. We will enhance public-interest preschool education and	promote	the development of regular county high schools.
systematic planning of major scientific and technological infrastructure and	promote	the development of generic technology platforms and pilot-scale
wind and photovoltaic power bases and transmission routes and	promote	the development and use of distributed energy sources
Taiwan independence and promote reunification. We should	promote	the peaceful development of cross-Strait relations and advance
Global Development Initiative and the Global Security Initiative and	promote	the shared values of humanity. Let us
fiscal policy and a prudent monetary policy, and	strengthen	coordination between policy instruments while developing new ones
the functions of industrial investment funds. We will	strengthen	coordination, planning, and investment guidance for
adapt themselves to our socialist society. We will	strengthen	and improve our work related to overseas Chinese
such as cross-border flows of data. We will	strengthen	services for foreign investors and make China a
Across all localities, new approaches were developed to	strengthen	services for promoting foreign investment, and greater
and fostering new capabilities, so as to	enhance	the resilience and competitiveness of industrial and supply
strengths, and research priorities, so as to	enhance	our capacity for original innovation. To meet
mitigation, and relief efforts in local communities and	enhance	our capacity for guarding against risks, responding
of strategic emerging industries. We will consolidate and	enhance	our leading position in industries such as intelligent
a digital government and promote one-stop government services to	enhance	our service levels. We will firmly tackle

According to Table 4, “promote” is often collocated with “development,” “strengthen” with “coordination” and “service,” and “enhance” with “capacity.” By analyzing the index lines listed in the above table, it can be inferred that, in terms of primary education, China will continue to promote the development of high schools in rural areas and strive to enhance the educational level of the whole nation (“promote the development of regular county high schools”). In terms of technological development, China constantly pursues technological innovation and actively explores the path of green and sustainable development (“promote the development of generic technology platforms and pilot-scale,” “promote the development and use of distributed energy sources, enhance the resilience and competitiveness of industrial and supply,” and “enhance our capacity for original innovation”). In terms of national sovereignty, China is firmly committed to advancing the reunification of the nation and deepening cross-strait relations. (“promote the peaceful development of cross-Strait relations and advance”).

The index lines and characteristics of these verbs indicate that the high-frequency verbs in RWG have positive meanings. They not only show that the Chinese government has a clear and profound understanding of the problems, but also emphasize that the Chinese government focuses on improving its own capabilities and is committed to adopting effective measures to solve the problems, thereby shaping an image of China that is proactive, realistic and pragmatic.

4.3 China’s self-shaping image through keywords

The Keyword function of Antconc is utilized to generate the keyword list of the RWG corpus and PAFA corpus, respectively, by using each other as reference corpora. The top 25 keywords ranked by keyness values are selected for comparative analysis. The specific details are shown in Table 5.

Table 5 Top 25 keywords in English translation of RWG and PAFA

English Translation of RWG				English Translation of PAFA
Rank	Keyword	Number of Occurrences	Keyness (Likelihood)	Keyword	Number of Occurrences	Keyness (Likelihood)
1	and	1945	300.316	I	295	324.210
2	policy	142	166.735	this	377	273.525
3	China	120	166.416	be	976	171.844
4	development	253	164.328	they	209	160.438
5	improve	171	163.491	it	224	158.377
6	promote	140	149.942	Russia	117	152.961
7	we	760	123.56	have	307	111.862
8	reform	78	105.373	our	317	98.042
9	Chinese	52	76.507	like	100	97.843
10	basic	67	73.026	ruble	73	95.389
11	Party	48	70.618	would	94	95.305
12	ensure	115	64.354	but	88	87.972
13	advance	57	63.958	programme	66	86.235
14	rural	83	60.333	their	225	81.078
15	enhance	46	53.655	that	316	79.861
16	trade	45	52.269	Russian	56	73.161
17	boost	40	50.745	not	100	72.047
18	stable	47	50.362	say	54	70.546
19	employment	47	50.362	about	76	69.118
20	strengthen	55	49.528	you	58	56.258
21	innovation	45	47.671	family	63	53.931
22	yuan	32	47.07	know	41	53.555
23	step	71	46.678	who	71	46.908
24	effort	92	46.602	next	41	45.573
25	urban	46	45.014	do	95	45.262

It can be known from Table 5 that, apart from the high-frequency nouns and high-frequency verbs that have been discussed earlier, the most significant difference in the keyword list between the RWG corpus and the PAFA corpus lies in the use of personal pronouns. RWG mostly uses the plural pronoun “we,” while PAFA mostly uses the singular pronoun “I.” According to the content of the translation, “we” and “I” respectively refer to the speaking subjects in RWG and PAFA. Personal pronouns are confined to the analysis of referents at the syntactic level in traditional grammar, while functional grammar extends them to the functional realization of interpersonal and contextual meanings. Beyond referring to specific objects in context, personal pronouns also serve to establish power dynamics and solidarity relations (Liu, 2016). To further compare the semantics of “we” in RWG and “I” in PAFA, the Cluster function in AntConc is used to retrieve the word “we” in the RWG corpus and “I” in the PAFA corpus, respectively, generating the following clusters in Table 6.

Table 6 The clusters of “we” and “I” in the English translation of RWG and PAFA

English Translation of RWG			English Translation of PAFA
Rank	Clusters	Number of Occurrences	Clusters	Number of Occurrences
1	we will	306	I would	81
2	we should	100	I am	32
3	we have	19	I will	21
4	we made	17	I have	19
5	we must	15	I propose	18

According to Table 6, it can be known that the words with a high collocational strength with “we” in the RWG corpus and the words with a high collocational strength with “I” in the PAFA corpus all involve modal verbs. Modal verbs express interpersonal meanings and reflect the speaker’s emotional attitudes and positions. In systemic functional linguistics, modality is one of the means to reflect interpersonal functions, aiming to establish, mediate and maintain interpersonal roles and social relationships. According to the values of modality (Halliday, 2000), modal verbs are usually classified into low-value modal verbs such as “can,” “could,” “may” and “might,” medium-value modal verbs such as “will,” “would,” “shall” and “should,” and high-value modal verbs such as “must,” “ought to,” “need” and “have to,” etc. High-value modal verbs often reflect the speaker’s strong subjective will and firm determination and are commonly used to express mandatory instructions or attitudes. Low-value modal verbs are expressed in a relatively gentle and euphemistic tone, effectively creating a warm and friendly communication atmosphere, thereby shortening the psychological distance between the communicating parties. Medium-value modal verbs are between the two. They can play a moderate guiding role for the audience without making the speech seem overly forceful. While achieving the purpose of communication, they maintain a relatively friendly language style. The data in the above table shows that compared with PAFA, RWG takes medium-value modal verbs such as “will” and “should” more frequently, with a total frequency as high as 406 times. The frequent occurrence of these two modal verbs reflects the planning and vision of the Chinese government for national development, which demonstrates that the government expresses the demands in a humble tone. Taking the medium-value modal verbs narrows the distance between the speaker and the audience in an approachable manner, thereby embodying China’s peaceful, modest and far-sighted image. In addition, RWG repeatedly takes the high-value modal verb “must,” strongly expressing the strong determination of the Chinese government to take concrete measures and conveying the government’s high sense of responsibility and execution ability in promoting economic and social development.

5 Conclusion

Research findings show that, compared with the English translation of PAFA, the English translation of RWG has the following language features: The high-frequency nouns are highly related to economic development; The collocation of the high-frequency core noun “people” constructs multi-dimensional semantics of “basic livelihood-social groups-national defense forces.” What is more, the high-frequency verbs imply reflections on the current situation and continuous improvements in the future. From the perspective of keywords, the English version of RWG mostly uses the plural form of the first-person pronoun “we,” and “we” is often used in combination with the medium-value modal verbs “will” and “should.”

There are certain deficiencies in this thesis. Firstly, the corpus constructed in this thesis is relatively small. Although the English version of RWG selected for the research has the advantage of presenting the latest image, the two-year texts are difficult to fully present the diachronic characteristics of the construction of China’s image. Secondly, this thesis mainly focuses on the statistical analysis of high-frequency nouns, high-frequency verbs and keywords, which cannot fully showcase the textual characteristics of this English version. Future research can be advanced from three dimensions. Firstly, the capacity of the corpus can be appropriately expanded to construct a diachronic composite corpus. Secondly, research on China’s self-shaping image can be conducted from other language features such as sentence structure, rhetorical devices, and text structure. Thirdly, dynamic tracking and multi-dimensional data collection methods can be introduced to quantitatively analyze the dissemination scope, audience’s feedback and public opinions of the English version of RWG in different cultural contexts, and to deeply explore the differences in understanding and cognitive changes of the translation content among different groups.

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