Declining Chinese Nationalism: Evidence Based on Internet Search Query Data

Abstract

While many scholars have done research on Chinese nationalism, more rigorously collected time-series data are needed to measure its nationwide change. Based on Google Trends and Baidu search results from January 2011 to December 2023, this study creatively created high-frequency monthly times series data to measure Chinese nationalism. By employing the Hodrick-Prescott filter, this study finds that the trend of Chinese nationalism has generally declined since 2018 or even earlier. The implication is that even if Chinese nationalism rises, it is primarily driven by short-term factors. At the same time, starting from late 2020, when China faced increased isolation from the global community, individuals outside of China may unintentionally amplify the scope of Chinese nationalism. While this study makes significant and original contributions to studies on Chinese nationalism, it also serves as a starting point for more quantitative (time-series) research in the future.

Introduction

Research on Chinese nationalism holds significant social relevance. A prominent case in point is China’s wolf warrior diplomacy, which has captured global attention among policymakers and China observers since early 2020. Huang 1 highlighted the transition in Chinese foreign policy rhetoric from a soft, defensive, and conciliatory tone to an increasingly assertive, offensive, and confrontational one, underscored by a surge in nationalist sentiment. Sullivan and Wang 2 went on to assert that the integration of cyber-nationalism into formal diplomatic discourse marks a notable evolution. Chen 3 further contextualizes the interplay between top-down directives and grassroots nationalist sentiments within this framework.

China’s nationalism was argued to be at the heart of the post-pandemic debate on global order due to rising anti-Chinese sentiments globally and its influence on foreign policy. 4 Previous studies on Chinese nationalism either adopted a conceptual approach, event analyses, or survey-data-based cross-sectional statistical models. To the best of the author’s knowledge, Johnston 5 is the only one who looked at the development of Chinese nationalism based on a long-time time series dataset. However, low-frequency data like yearly data may smooth out the causal relations among variables. Furthermore, Johnston 6 only examined data from Beijing. Unlike previous studies, this study creatively created monthly time series datasets based on Baidu search and Google Trends data from January 2011 to December 2023 to measure Chinese nationalism. Time series modeling was employed with these datasets to scrutinize the trajectory of Chinese nationalism, with the primary goal of addressing the question: is Chinese nationalism on the rise? In this context, “rising nationalism” predominantly pertains to popular nationalism and is defined as “external manifestations of underlying tensions” (refer to the literature review section for further discussions).

There are several advantages to utilizing time series data. Firstly, it enables a comprehensive understanding of the trend of Chinese nationalism. In contrast, event studies or cross-sectional analyses can only assess Chinese nationalism at specific time points or in relation to particular events within short durations. Secondly, time series data allows for the identification of underlying causes of Chinese nationalism over time. Consequently, this approach potentially facilitates forecasting of Chinese nationalism in the future, enabling predictions of its implications on foreign policy dynamics (such as China’s wolf warrior diplomacy) and sentiments regarding potential conflicts (such as those across the Taiwan Straits).

The structure of this paper is as follows. “Literature review” reviews relevant literature on Chinese nationalism, focusing on its definition, development, political use, and expression. “Data sources” introduces the data sources, i.e., Google Trends and Baidu search. “Rising Chinese nationalism?” looks at the trend of Chinese nationalism based on Google Trends and Baidu search data using the Hodrick–Prescott filter. “Concluding remarks” concludes this paper.

Literature review

Prior studies on Chinese nationalism have explored various facets. While this study uniquely contributes to academia by introducing high-frequency time-series data for measuring Chinese nationalism, the review in this section focuses on broader literature on Chinese nationalism, including definitions and types, political use, development, and expression. The aim is to offer a brief review of Chinese nationalism, positioning this study within the broader scope of research on the evolution of Chinese nationalism over time. To achieve this goal, the study assesses the form of nationalist expression as a metric for analysis.

First, there are various definitions of Chinese nationalism. Guang 7 argued that there are different viewpoints regarding the definition of Chinese nationalism. For example, Pye 8 believed that modern Chinese nationalism is “confused,” “contentless,” and “incoherent.” Johnston 9 concluded that most Chinese nationalism experts are well-versed in the intricate substance and evolution of modern Chinese nationalism. Duan 10 reviewed relevant literature and concluded that Chinese nationalism can be categorized into different types according to different standards. A specific form of nationalism, digital nationalism, has garnered recent attention. For instance, Sullivan and Wang 11 scrutinized the impact of Chinese digital nationalism on shaping China’s wolf warrior diplomacy. Chen 12 delved into China’s nationalist narrative within the digital realm of Chinese social media platform Weibo. Additionally, Schneider 13 illustrated how the CCP utilized the digital platform Bilibili during the COVID-19 crisis to amplify nationalist sentiments. Zhao 14 concluded that “these labels can only show one or a few dimensions of Chinese nationalism of a specific period and unable to cover the complexity of Chinese nationalism,” and that “the characteristics of Chinese nationalism have not been dealt with in depth.”

Second, regarding the political use of Chinese nationalism, the Chinese governments have purposely fueled nationalism to bolster domestic support, legitimize authority, and assert its global influence. 15 At the same time, while Chinese nationalism has traditionally been perceived as a tool wielded by the government to influence and mobilize the populace, research indicates that its construction can occur through both top-down directives and bottom-up initiatives. For instance, drawing from a limited sample of teachers in Hong Kong, Leung 16 concluded that top-down nationalistic education tends to prioritize indoctrination over fostering critical thinking skills. Examining the phenomenon of “Little Pink,” Fang and Repnikova 17 shed light on non-state expressions of cyber-nationalism. Additionally, employing the Network Agenda Setting approach, Chen et al. 18 revealed that the formation of Chinese nationalism online operates in a dual-directional manner.

Third, the development of Chinese nationalism has been examined by many scholars. According to Guang, 19 the debate on Chinese nationalism in the 1950s and 1960s was focused on the nature of the Chinese revolution, but this debate receded from the late 1960s to the 1970s. Regarding contemporary Chinese nationalism, Guang 20 argued that there are a few widely-held assumptions, i.e., its anti-Western orientation, its statist character, its cultural-historical ambitions, and it is built on powerful sentiments generated by the “century of shame and humiliation.” Modongal 21 delineated Chinese nationalism into four distinct stages: Mao-centric state-controlled nationalism spanning from 1949 to 1976, pro-Western liberal nationalism from 1976 to 1989, anti-West pragmatic nationalism from 1989 to 2008, and cyber-nationalism emerging since 2008.

The question of whether contemporary Chinese nationalism is rising is a major focus of research. According to Johnston, 22 “in general, the discourse about rising nationalism, particularly in the media and among pundits, tends to refer more to the intensity of popular nationalism,” and rising nationalism refers to “the intensity or degree of nationalism expressed by ordinary citizens.” This expression can take various forms, manifesting in cultural, political, and social domains. Carrico 23 provided a conflict-based conceptualization of China’s rising nationalism, i.e., “external manifestations of underlying tensions.” The term “Chinese dream” (see “Key phrase: Chinese dream” for details) can be interpreted from both collective and individual perspectives. It encompasses the ideals of “national rejuvenation, improvement of people’s livelihoods, prosperity, construction of a better society, and military strengthening” as the shared aspiration of the Chinese people, deemed most achievable under one-party, Socialist rule. 24 On the collective front, it mirrors the tensions surrounding China’s pursuit to reclaim its rightful great power status within the existing global order. From an individual standpoint, the term introduces conflicts with the well-known concept of the “American dream.” 25 Furthermore, another term “China’s rise” (as well as “great rejuvenation”) (see “Key phrase: China’s rise” for details) can be viewed as the collective dimension of the broader “Chinese dream.”

Previous studies have examined China’s rising nationalism driven by specific events such as the bombing of the Chinese embassy in Belgrade by the United States in May 1999, the EP3 incident in April 2001, the condemnation of the Japanese Prime Minister’s trips to the Yasukuni Shrine in 2005 26 and anti-Japanese demonstration in 2012, 27 a series of nationalist movements in 2008, the boycott of South Korean products in 2017, and the rising nationalism during the Covid-19 pandemic. 28 As argued by Zhao, 29 this approach focuses on the “moments of madness” and thus lacks representativeness. Some studies examined online platforms such as Weibo, 30 Zhihu, 31 and Bilibili. 32 However, the problem is that they cannot reflect “unstained” opinions. Some studies adopted a survey-data-based cross-sectional approach, 33 which explanatory power, however, was restricted by some serious inadequacies, including small sample size, overreliance on questionnaires, and a repetitive set of inquiries. 34 Several limited studies examined the time series development of Chinese nationalism. For example, Johnston 35 conducted a yearly time-series survey from 2000 to 2015 and found that there had not been a continuously rising level of nationalism among the survey respondents. However, similar to other survey-data-based studies, it also has a representativeness issue. Also, yearly data may have quite likely smoothed out many causal relations. As a result, serious multivariate regression becomes difficult. Zhao 36 conducted an everyday discourse analysis of Chinese nationalism between 20 January and 25 May 2020. The limitation is that it only covers a very short period and is event-driven (Covid-19). Some scholars turned to discourse analysis of Chinese nationalism, such as the Chinese dream. 37 As argued by Zhao, 38 the problem with this approach is that it ignored the voice of the masses. In a word, as argued by Duan, 39 there is still very little systematic research on Chinese nationalism, and the lack of cross-time (and cross-country) benchmarks is a crucial oversight in the existing research.

This study fills in the gap by employing Google Trends and Baidu search data to measure Chinese nationalism. As argued by Wang and Tao, 40 nationalist discourse on social media is closer to reality than information collected through surveys and experiments. At the same time, internet search activities, which suffer less censorship than social media, are assumed to be much closer to reality than a discourse on social media. From this point of view, internet search activities are more accurate in measuring nationalism. Furthermore, internet search activity data are as frequent as monthly or weekly (or even daily). As a result, serious time series modeling becomes feasible.

Data sources

First, the two data sources based on search engine queries, i.e., Google Trends and Baidu Index, are introduced. Second, studies on these search engine-based data, in particular Google Trends, including their nature, are reviewed. Based on the nature of search queries, this study concludes that they can be used to measure concepts related to Chinese nationalism.

Notably, Google Trends, being more globally utilized and researched than Baidu, takes precedence in the following discussion, with Baidu introduced subsequently. However, in “Rising Chinese nationalism?,” the analysis begins by examining results derived from Baidu. This approach is adopted because Baidu outcomes offer insights into the internal dynamics of Chinese nationalism, potentially yielding a more accurate depiction than external viewpoints. The divergence between these internal and external perspectives is addressed at the end of “Rising Chinese nationalism?”

Search engine queries

Google Trends⁴¹ is an insightful website provided by Google that analyzes the popularity of top search queries in Google Search across different regions and languages. Google Trends normalizes search results based on the time and location of a query. This normalization enables meaningful comparisons across different dates, countries, or cities. In essence, the numbers displayed in Google Trends represent the level of search interest relative to the highest point on the chart for the specified area and time. For a more in-depth introduction, please refer to Liu.⁴²

The Baidu Index⁴³ serves as an additional source for analyzing search trends. Baidu, the largest search engine in China and the second largest globally, holds a market share ranging from 51 percent to approximately 80 percent between January 2011 and December 2023 in China.⁴⁴ It is important to note that Baidu search data is not scaled by default. To ensure comparability between Baidu search and Google Trends data, the original Baidu search data is scaled by the author on a scale of 0 to 100. Additionally, the original Baidu search results are transformed into weekly and monthly data by summing the observations. The start date for Baidu search data is 1 January 2011. Although Google Trends data is available from as early as 2004, the start date for the data sets in this study is set as January 2011 to maintain consistency and comparability. Furthermore, it should be noted that, unlike Google Trends, Baidu search might censor certain sensitive key phrases. In this study, the examined key phrases are not expected to be part of the sensitive list. Consequently, any potential biases in Baidu search results, if present, are presumed to be insignificant.

Studies on search engine queries

As both Google Trends and Baidu Index are essentially very similar in terms of search engines, the conclusion drawn based on Google Trends can also be applied to Baidu Index.

Liu 45 conducted an exhaustive examination of studies on Google Trends, encompassing its application in measuring the public agenda and agenda-setting effects, its connections with media coverage, and its diverse applications across various fields, along with pertinent practical considerations. Essentially, Liu 46 concludes that Google Trends (and Baidu Index) can be interpreted as indicators of the public’s perception regarding the most significant topics, influenced by policy matters, media coverage, and individual attention to specific issues. Furthermore, as outlined in the media system dependency theory, 47 the media serves as a crucial conduit for non-specialists to acquire knowledge about international affairs. Consequently, our understanding of Chinese nationalism, particularly within the English-speaking world, is predominantly shaped by media coverage. Increased intensity of Chinese nationalism leads to heightened reporting and analysis on the subject, subsequently prompting greater search activity on the internet. This rationale underscores the use of Google search data, employing the key phrase “China nationalism,” as a metric for gauging Chinese nationalism (detailed in “Google Trends indicator”). Consequently, Baidu search results utilizing phrases such as “China rise” or “Chinese dream” (detailed in “Baidu search indicators”) can be employed to gauge the Chinese public’s perspective and measure Chinese nationalism from this standpoint.

Rising Chinese nationalism?

This section looks at the development of Chinese nationalism during 2011–2023, aiming to answer such a question: is China’s nationalism rising? Following Johnston, 48 rising nationalism is defined as the intensity or degree of nationalism expressed by ordinary citizens. In “Baidu search indicators,” the Baidu data are used as a proxy variable to measure Chinese nationalism. In “Google Trends indicator,” the Google Trends data are used as the other proxy variable. The Hodrick–Prescott filter (or Hodrick–Prescott decomposition) tool is used to obtain the trend data.

The Hodrick–Prescott (HP) filter is a mathematical method primarily used in macroeconomics for removing the cyclical component of a time series from raw data. It is used to create a smoothed-curve representation of a time series that is more sensitive to long-term variations than short-term ones. The sensitivity of the trend to short-term variations can be adjusted in EViews by changing a multiplier (lambda) that is chosen automatically for varied frequencies of data. The lambda value for monthly data in this study is 14,400. Hamilton 49 criticized the HP filter for various technical issues. As a response, Hodrick 50 concluded that for time series data that have distinct growth and cyclical components, the HP filter works better. Future studies can choose different filter tools for alternative tests.

Baidu search indicators

In this part, a few alternative variables are proposed to measure Chinese nationalism. Unlike Google Trends, “China nationalism (‘中国民族主义’ in Chinese)” or “nationalism (‘民族主义’ in Chinese)” are not good key phrases. The reason is that Chinese media coverage of Chinese nationalism may suffer from heavy censorship. The search results are not able to accurately reflect the (normalized) volume of Chinese nationalism. Furthermore, using “(China) nationalism” as a key phrase is an indirect measurement. A better way is to look at the key phrases that can directly reflect Chinese nationalism. In this part, three key phrases are used, i.e., Chinese dream (中国梦), China’s Rise (中国崛起), and the great rejuvenation of the Chinese nation (中国民族伟大复兴). All the data are monthly.

Key phrase: Chinese dream

According to Sørensen, 51 the “Chinese dream” as a concept was rarely mentioned before Chinese President Xi took it up in November 2012. The dominant interpretation is that the “Chinese dream” is a nationalistic concept, aimed at reclaiming China’s rightful great power position, dignity, and respect, using military force if necessary. Wang 52 also argued that the Chinese Dream is part of the context of nationalism. Baidu search raw data (see Appendix 2) show that the Chinese dream search index reached its peak in middle 2013. The issue is that this peak value is such an extreme outlier that it is even very difficult to analyze the pattern of the after-decomposition data. As a result, the HP filter is only applied to data sets after 2015. Figure 1 shows the HP Filter results of China’s nationalism measured with the key phrase “Chinese dream (中国梦)” Baidu search.

Figure 1. Baidu Search: Using “中国梦 (Chinese Dream)” as the key phrase during January 2015–December 2023: HP Filter.

First, the cycle data show clear cyclical components. The peak time of cyclical components happened in May and November in 2015, in May and October of 2016, 2017, 2018 and 2019, in June and September in 2020, in May and October in 2021 and 2022, and in May, September, and October 2023. The basic pattern is that the peak time happened around May and October. In May, there is a major public holiday in China named Labour Day (1 May). Chinese leaders usually issue medals to Model Workers and Advanced Workers, accompanied by a speech. For example, on 28 April 2015, Chinese President called for the working class to support the Chinese dream through work. 53 He also mentioned the Chinese dream during his 2016 Labour Day speech⁵⁴, 2017 Labour Day speech, 55 and 2021 Labour Day message. 56 Besides, various Chinese media outlets also especially connect this day with the Chinese dream. In October, there is another major public holiday in China, i.e., the National Day (1 October). There are national celebrations around this day including the Wreath-laying ceremony at the Monument to the People’s Heroes, the Publication of the National Day Honors List, the National flag-raising ceremony, and the National civil-military parade. It is no wonder that the Chinese dream gains its momentum around this day.

Second and most importantly, Figure 1 shows that the trend data of the Chinese dream has been declining since early 2018. The implication is that even if we see or hear something about rising Chinese nationalism (proxied with the Chinese dream), it is primarily driven by short-term factors.

Moreover, based on data from Hupu.com, a sports media website boasting over 70 million registered users and 160 million daily visits,⁵⁷ the assessment of life by Chinese netizens witnessed a significant decline since 2018 (refer to Appendix 4). It is important to note that the user demographic on this website is predominantly male, introducing a potential sample bias that could impact the validity of these findings. Additionally, sentiments regarding personal life are linked to national pride but may not be universally shared in the same manner.

Key phrase: China’s rise

According to Itzkowitz Shifrinson and Beckley, 58 “China’s rise” is a relative term, suggesting an increase in the ratio of economic and military capabilities between China and the US/the world. While China initially avoided using such a narrative, it has recently fully embraced it. From the viewpoint of Chinese nationalists, China is rising and the West is declining. 59 Figure 2 shows the HP Filter results of China’s nationalism measured with the key phrase “China’s Rise” (“中国崛起”) Baidu search.

Figure 2. Baidu Search: Using “中国崛起 (China’s Rise)” as the key phrase from January 2011 to December 2023: HP Filter.

First, the cycle data show some cyclical components. The peak time of cyclical components happened in June and October 2011, in May and October 2012, in May and December 2013, in May and November 2014, in April, June, and December 2015, in July and December 2016, in June and October 2017, in April, October and December 2018, in May and October 2019, in March and December 2020, in March 2021, in March and October 2022, and in April and September 2023. Although less consistent than that of the “Chinese dream” as shown in Figure 1, the basic pattern is that the peak time happened around May and October. As discussed in “Key phrase: Chinese dream,” the reason for the surge in search activities is two major public holidays, i.e., Labour Day and National Day, and more intensive political campaigns and media coverage around them than usual.

Second and most importantly, Figure 2 shows that the trend data for China’s rise has been declining since early 2016. This is generally consistent with the results using another key phrase, “Chinese dream.” The suggestion here is that any observations we make or information we hear regarding the increase in Chinese nationalism (represented by China’s rise) are predominantly influenced by short-term considerations.

Furthermore, Johnston 60 argued that another term, “great rejuvenation,” may also be related to Chinese nationalism. HP Filter results (see Appendix 3) show a rising trend before 2022 but a decline in 2023. The peak time of cyclical components also happened around May and October, suggesting a cyclical feature. According to Wang, 61 while the “Chinese dream” is a new phrase and signature ideology of the Chinese Communist Party (CCP), the core concept of national rejuvenation is not new. In fact, the concept of rejuvenating the country has been used as a political platform by generations of modern Chinese political leaders. The narrative has been used by political leaders to strengthen their own legitimacy, promote their own interests, instill a sense of nationalism, and rally public support for social change. In the post-Tiananmen and post-Cold War era, the legitimacy-challenged CCP has utilized the narrative, in particular, to glorify the Party, consolidate national identity, and defend the CCP's one-party rule. While this term has complicated meanings, and is far more than simply reflecting Chinese nationalism, the rising trend data primarily show that the CCP has especially strengthened its efforts before 2022. The CCP’s main target is the 100th anniversary of the CCP on 1 July 2021, which is argued to be the biggest moment for China. 62 National rejuvenation would be the key theme of the Anniversary. 63 In fact, it is, 64 and it reached its peak on 1 July 2021, as indicated by daily data (unreported but available upon request. Notably, Appendix 3 utilizes monthly data, employing the monthly average to mitigate fluctuations and provide a more stabilized perspective). Excluding the outlier in July 2021, and focusing solely on datasets from August 2021 to December 2023, reveals a distinct declining trend (unreported but accessible upon request).

Google Trends indicator

Raw data

The key phrase “China nationalism” is used (if using “Chinese nationalism” as the key phrase, the search results are much fewer. Also, “China nationalism” is more popular than “Chinese nationalism” except in the United Kingdom. See Appendix 1 for more information). Figure 3 shows the search results, which are used as a proxy variable measuring Chinese nationalism. Compared with Baidu indicators (see “Baidu search indicators”), Google Trends data are from the viewpoint of the English-speaking world, thus an indirect measurement.

Figure 3. Search results for “China nationalism,” Google Trends monthly data, January 2011–December 2023, worldwide.

Figure 3 shows that the largest peak of search interest occurred in April 2022, driven by various factors. Firstly, the response of Chinese social media to the Russia-Ukraine war raised concerns about Chinese nationalism. Repnikova and Zhou 65 highlighted those online comments predominantly favored Moscow and criticized U.S. influence. Liu 66 further noted that these posts were marked by nationalism and aggressive “wolf warrior” narratives. Additionally, Jung 67 emphasized the impact of “The Great Translation Movement,” aiming to globally spotlight the perception that individuals in China are of arrogance, nationalism, cruelty, and a lack of sympathy. Secondly, issues surrounding Chinese nationalism were amplified by the response of Chinese leaders during the EU-China summit. President Xi’s statement, asserting that former colonizers should not pass judgment on China regarding human rights issues, 68 sparked considerable debate. Thirdly, reports emerged that English language elements were removed from certain station placards and maps in China, aligning with President Xi’s call for increased “cultural confidence.” 69 These incidents collectively fueled the surge in search interest during this period.

Decomposition

Figure 4 shows the HP Filter results of China’s nationalism measured with data retrieved from Google Trends.

Figure 4. China’s Nationalism from January 2011 to December 2023 based on Google Trends: HP Filter.

First, the cycle data show clear cyclical components. The peak time of cyclical components happened either in January (2014), February (2012, 2013, 2016, and 2017), March (2011, 2021, and 2023), or April (2015, 2018, 2019, 2020, and 2022). They are generally around March of each year. In China, March is most often the time of China’s Lianghui (or “Two Sessions”), except for 2020, when it was delayed to May because of the outbreak of Covid-19. The Lianghui refers to the annual plenary sessions of the national or local People’s Congress and the national or local committee of the Chinese People’s Political Consultative Conference. Around Lianghui, it is expected that Lianghui representatives will be interviewed by the media and express their viewpoints on various areas such as foreign policy, domestic politics, society, culture, and the economy. Also, Chinese leaders will deliver their speeches to the Lianghui, signaling to the outside about China’s various policies. As a result, March is a very special time characterized by a high intensity of media coverage of viewpoints and policy announcements. The consequence is that China’s nationalism draws special attention around March, and forms the cyclical component.

Second and most importantly, Figure 4 shows that although the trend data of China’s nationalism were gradually rising during 2011–2017, they started declining in January 2018 until June 2020. Significantly, the fervor of nationalist expression within China, observed through Baidu, and the external interest in Chinese nationalism, gauged via Google, closely align in their overarching trajectory.

However, a divergence between internal observations and external perspectives began to surface from late 2020 (until 2023). During this timeframe, external assessments notably exceeded the actual levels of nationalist expression within China. The primary contributing factor was the stringent zero-covid policy adopted by China from 2020 to 2022 during the Covid-19 pandemic, leading to frequent lockdowns in affected areas and a substantial reduction in connections between China and the outside world. Although the zero-covid policy was abolished in December 2022, China’s increased emphasis on national security led to a greater degree of control. Foreign diplomats faced increasing challenges in meeting with Chinese officials, academics, and think tank members. 70 In 2022, the number of foreign tourists visiting China constituted only 10 percent of the figures recorded in 2019. In 2023, this percentage was projected to reach a range of 15 to 20 percent compared to the levels observed in 2019. 71 Consequently, individuals outside China are prone to overinterpretation of specific events or comments, inadvertently exaggerating the perceived extent of Chinese nationalism.

Concluding remarks

As discussed at the beginning of this paper, China’s nationalism was argued to be at the heart of the post-pandemic debate on the global order. Various scholars have done much research on Chinese nationalism. However, as argued by Johnston, 72 “scholars of Chinese nationalism need more rigorously collected time-series data that measure nationwide change in various indicators of nationalism.” Based on Baidu search and Google Trends results, this study creatively created high-frequency monthly times series data to measure Chinese nationalism. Utilizing this metric, the study empirically investigated the trajectory of Chinese nationalism, aiming to answer the question: is Chinese nationalism experiencing an upward trend?

Based on monthly Google Trends and Baidu search data from January 2011 to December 2023 and employing the HP filter, this study finds that the trend of Chinese nationalism is generally declining from 2018 or even earlier. The implication is that even if Chinese nationalism rises, it is primarily driven by short-term factors. At the same time, a divergence emerged between internal observations, as indicated by Baidu results, and external perspectives reflected by Google Trends, from late 2020. This discrepancy is primarily attributed to China’s heightened isolation from the global community, a consequence of the zero-covid policy and a heightened focus on national security. Consequently, individuals outside of China may inadvertently exaggerate the extent of Chinese nationalism.

This study also serves as a starting point for more quantitative (time-series) studies of Chinese nationalism in the future. For example, different key phrases can be further tested to measure different types of nationalism. Future studies can also identify independent variables that could potentially cause Chinese nationalism and test their significance by employing time series statistical models. Future studies can also conduct comparative analysis both within the region and globally. This comparative approach can shed light on the unique features and drivers of Chinese nationalism. As argued by Liu, 73 measurement errors stemming from random sampling and Google’s algorithm updates pose limitations for Google Trends in forecasting, particularly in business, economics, and healthcare. However, if the emphasis lies on coefficient signs rather than magnitudes, or simply general trends as in this study, such errors may have very limited if any impact.

Additionally, time series modeling can be conducted to test the implications of Chinese nationalism for foreign policy and war. These studies hold significant implications for policymakers worldwide. For instance, in terms of foreign policy, as elucidated in the introduction and literature review sections, Chinese nationalism has been instrumental in shaping China’s wolf warrior diplomacy. Assuming that multiple factors have contributed to the emergence of wolf warrior diplomacy and other variables remain constant (though, notably, Chinese strength has been somewhat diminished due to its zero COVID policy), a waning Chinese nationalism implies a more subdued or restrained foreign policy stance. Indeed, the reality reflects a gradual quietening of China’s wolf warrior diplomacy, evidenced by the reassignment of its prominent figure, Zhao Lijian, in January 2023. Furthermore, with regard to war sentiment, a decline in Chinese nationalism suggests a diminished fervor for conflict among the Chinese populace. This insight carries weighty implications for policymakers globally, particularly concerning sensitive issues such as the Taiwan Straits and the South China Sea.

From the viewpoint of academia, this study contributes by expanding the applications of Google Trends (and Baidu Index) data in political studies. As concluded by Mellon⁷⁴, many political scientists have started utilizing Google Trends as a metric for gauging issue salience or attention. This tool has been applied to various issues, ranging from constituent responses to WTO trade disputes to the dynamics of the Occupy movement. This study defines Internet search query data as a time series variable measuring agenda-setting effect. It means that time series modeling based on high-frequency time series data can be more applied in political studies.

Acknowledgements

The author would like to express gratitude to the editors of the Journal of Nationalism and Ethnic Politics, as well as two anonymous referees, for their valuable comments on an earlier version of this paper. Any errors remain the sole responsibility of the author.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Notes on contributors

Kerry Liu

Kerry Liu is an independent scholar in Australia.

Notes

1 Zhao Alexandre Huang, “‘Wolf Warrior’ and China’s Digital Public Diplomacy during the COVID-19 Crisis,” Place Branding and Public Diplomacy 18, no. 1 (2022): 37–40.

2 Jonathan Sullivan and Weixiang Wang, “China’s ‘Wolf Warrior Diplomacy’: The Interaction of Formal Diplomacy and Cyber-Nationalism,” Journal of Current Chinese Affairs 52, no. 1 (2023): 68–88.

3 Keyu Alexander Chen, “Digital Nationalism: How Do the Chinese Diplomats and Digital Public View ‘Wolf Warrior’ Diplomacy?,” Global Media and China 8, no. 2 (2023): 138–54.

4 Zhenyu Wang and Yuzhou Tao, “Many Nationalisms, One Disaster: Categories, Attitudes and Evolution of Chinese Nationalism on Social Media during the COVID-19 Pandemic,” Journal of Chinese Political Science 26, no. 3 (2021): 525–48.

5 Alastair Iain Johnston, “Is Chinese Nationalism Rising? Evidence from Beijing,” International Security 41, no. 3 (2016): 7–43.

6 Johnston, “Is Chinese Nationalism Rising?”

7 Lei Guang, “Realpolitik Nationalism: International Sources of Chinese Nationalism,” Modern China 31, no. 4 (2005): 487–514.

8 Lucian W. Pye, “China: Not Your Typical Superpower,” Problems of Post-Communism 43, no. 4 (1996): 3–15.

9 Johnston, “Is Chinese Nationalism Rising?”

10 Xiaolin Duan, “Unanswered Questions: Why We May Be Wrong about Chinese Nationalism and Its Foreign Policy Implications,” Journal of Contemporary China 26, no. 108 (2017): 886–900.

11 Sullivan and Wang, “China’s ‘Wolf Warrior Diplomacy’.”

12 Chen, “Digital Nationalism.”

13 Florian Schneider, “China’s Viral Villages: Digital Nationalism and the COVID-19 Crisis on Online Video-Sharing Platform Bilibili,” Communication and the Public 6, no. 1–4 (2021): 48–66.

14 Xiaoyu Zhao, “A Discourse Analysis of Quotidian Expressions of Nationalism during the COVID-19 Pandemic in Chinese Cyberspace,” Journal of Chinese Political Science 26, no. 2 (2021): 277–93.

15 Jian Zhang, “Chinese Nationalism and Its Foreign Policy Implications,” Asia-Pacific Security 108 (2003); Duan, “Unanswered Questions.”

16 Yan Wing Leung, “Nationalistic Education and Indoctrination,” Citizenship, Social and Economics Education 6, no. 2 (2004): 116–30.

17 Kecheng Fang and Maria Repnikova, “Demystifying "Little Pink": The Creation and Evolution of a Gendered Label for Nationalistic Activists in China,” New Media & Society 20, no. 6 (2018): 2162–85.

18 Zhuo Chen, Chris Chao Su, and Anfan Chen, “Top-Down or Bottom-Up? A Network Agenda-Setting Study of Chinese Nationalism on Social Media,” Journal of Broadcasting & Electronic Media 63, no. 3 (2019): 512–33.

19 Guang, “Realpolitik Nationalism.”

20 Ibid.

21 Shameer Modongal, “Development of Nationalism in China,” Cogent Social Sciences 2, no. 1 (2016): 1235749.

22 Johnston, “Is Chinese Nationalism Rising?,” 8.

23 Kevin Carrico, “National Identity Deconstruction: Revisiting the Debate on Chinese Nationalism via Hong Kong Nationalism,” Nations and Nationalism 29, no. 2 (2023): 768–83.

24 Evan Osnos, “Can China Deliver the China Dream(s)?,” New Yorker, 26 (2013). http://www.wheretherebedragons.com/wp-content/uploads/2013/06/Can-China-Deliver-the-China-Dreams.pdf.

25 Sujian Guo and Baogang Guo, eds. Greater China in an Era of Globalization (Rowman & Littlefield, 2010).

26 Jean-Pierre Cabestan, “The Many Facets of Chinese Nationalism,” China Perspectives 2005, no. 3 (2005): 59.

27 Christopher Cairns, and Allen Carlson, “Real-World Islands in a Social Media Sea: Nationalism and Censorship on Weibo during the 2012 Diaoyu/Senkaku Crisis,” The China Quarterly 225 (2016): 23–49.

28 Zhao, “A Discourse Analysis of Quotidian Expressions”; Wang and Tao, “Many Nationalisms, One Disaster.”

29 Zhao, “A Discourse Analysis of Quotidian Expressions.”

30 Yinxian Zhang, Jiajun Liu, and Ji-Rong Wen, “Nationalism on Weibo: Towards a Multifaceted Understanding of Chinese Nationalism,” The China Quarterly 235 (2018): 758–83.

31 Zhao, “A Discourse Analysis of Quotidian Expressions.”

32 Schneider, “China’s Viral Villages.”

33 Robert Hoffmann and Jeremy Larner, “The Demography of Chinese Nationalism: A Field-Experimental Approach,” The China Quarterly 213 (2013): 189–204; Z. Wei, “China’s Little Pinks: Nationalism among Elite University Students in Hangzhou?,” Asian Survey 59, no. 5 (2019): 822–43.

34 Zhao, “A Discourse Analysis of Quotidian Expressions.”

35 Johnston, “Is Chinese Nationalism Rising?”

36 Zhao, “A Discourse Analysis of Quotidian Expressions.”

37 Jiayu Wang, “Representing Chinese Nationalism/Patriotism through President Xi Jinping’s “Chinese Dream” Discourse,” Journal of Language and Politics 16, no. 6 (2017): 830–48; William A. Callahan, “Dreaming as a Critical Discourse of National Belonging: China Dream, American Dream and World Dream,” Nations and Nationalism 23, no. 2 (2017): 248–70.

38 Zhao, “A Discourse Analysis of Quotidian Expressions.”

39 Duan, “Unanswered Questions.”

40 Wang and Tao, “Many Nationalisms, One Disaster.”

41 See https://trends.google.com/trends/.

42 See Kerry Liu, “America’s Decoupling from China Narrative: Development, Determinants, and Policy Implications,” Journal of Information Technology & Politics (2023): 1–17. https://doi.org/10.1080/19331681.2023.2208105

43 See https://index.baidu.com/v2/index.html#/.

44 See https://gs.statcounter.com/search-engine-market-share/all/china.

45 Liu, “America’s Decoupling from China Narrative.”

46 Ibid.

47 Sandra J. Ball-Rokeach and Melvin L. DeFleur, “A Dependency Model of Mass-Media Effects,” Communication Research 3, no. 1 (1976): 3–21.

48 Johnston, “Is Chinese Nationalism Rising?”

49 James D. Hamilton, “Why You Should Never Use the Hodrick-Prescott Filter,” Review of Economics and Statistics 100, no. 5 (2018): 831–43.

50 Robert J. Hodrick, “An Exploration of Trend-Cycle Decomposition Methodologies in Simulated Data” (No. w26750, National Bureau of Economic Research, 2020).

51 Camilla T. N. Sørensen, “The Significance of Xi Jinping’s “Chinese Dream” for Chinese Foreign Policy: From “Tao Guang Yang Hui” to “Fen Fa You Wei”,” Journal of China and International Relations 3, no. 1 (2015).

52 Zheng Wang, “The Chinese Dream: Concept and Context,” Journal of Chinese Political Science 19, no. 1 (2014): 1–13.

53 Xinhua News, “习近平在庆祝"五一"国际劳动节大会上的讲话 Xi Jinping’s Speech at the Celebration of "May 1st" International Labor Day,” April 28, 2015. http://www.xinhuanet.com//politics/2015-04/28/c_1115120734.htm.

54 Sina News. 2016. 这些年习近平怎样过劳动节 How did Xi Jinping celebrate Labor Day these years. 2 May. Retrieved from http://news.sina.com.cn/c/nd/2016-05-02/doc-ifxrtztc3144970.shtml.

55 Jingrui Li and Jing Wu, “习近平号召“以劳动为荣”: 激励劳动者, 托举中国梦 Xi Jinping Calls for "Proud of Labor": Inspiring Laborers and Supporting the Chinese Dream,” April 28, 2017. http://politics.people.com.cn/n1/2017/0428/c1001-29243574.html.

56 Qiushi, “总书记的“劳动节”寄语 Message from the General Secretary on "Labor Day”,” May 1, 2021. http://www.qstheory.cn/zhuanqu/2021-05/01/c_1127400625.htm (in Chinese).

57 See https://www.thepaper.cn/newsDetail_forward_13476424 (in Chinese).

58 Joshua R. Itzkowitz Shifrinson and Michael Beckley, “Debating China’s Rise and US Decline,” International Security 37, no. 3 (2013): 172–81.

59 C. Buckley, “China’s Combative Nationalists See a World Turning Their Way,” New York Times, December 14, 2020. https://cn.nytimes.com/china/20201214/china-nationalists-covid/dual/.

60 Johnston, “Is Chinese Nationalism Rising?”

61 Wang, “The Chinese Dream.”

62 Kerry Brown, “Can China’s Great Show of Unity Last?,” The Diplomat, March 28, 2018. https://thediplomat.com/2018/03/can-chinas-great-show-of-unity-last/.

63 Brown, “Can China’s Great Show of Unity Last?”

64 Jinping Xi, “习近平: 在庆祝中国共产党成立100周年大会上的讲话. Xi Jinping: Speech at the Celebration of the 100th Anniversary of the Founding of the Communist Party of China,” Xinhua News, July 15, 2021. http://www.xinhuanet.com/politics/leaders/2021-07/15/c_1127658385.htm (in Chinese).

65 Maria Repnikova and Wendy Zhou, “What China’s Social Media Is Saying about Ukraine,” The Atlantic, March 2022. https://www.theatlantic.com/ideas/archive/2022/03/china-xi-ukraine-war-america/627028/.

66 Yimei Liu, “The Unintended Consequences of China’s Stance on Ukraine,” The Diplomat, March 19, 2022. https://thediplomat.com/2022/03/the-unintended-consequences-of-chinas-stance-on-ukraine/.

67 Chauncey Jung, “The Great Translation Movement Shines a Spotlight on China’s Propaganda,” The Diplomat, April 5, 2022. https://thediplomat.com/2022/04/the-great-translation-movement-shines-a-spotlight-on-chinas-propaganda/.

68 The Economist, “China Goes on the Offensive over Human Rights,” April 13, 2022. https://www.economist.com/china/2022/04/13/china-goes-on-the-offensive-over-human-rights.

69 The Economist, “Why China Is Turning away from English,” April 13, 2022. https://www.economist.com/china/2022/04/13/why-china-is-turning-away-from-english.

70 Finbarr Bermingham, “EU Envoy Slams China’s ‘Obsession with National Security’, Questions Economic Rebound,” South China Morning Post, January 17, 2024. https://www.scmp.com/news/china/diplomacy/article/3248814/eu-envoy-slams-chinas-obsession-national-security-questions-economic-rebound.

71 Jiemian News, “外籍游客在华存在诸多不便 入境游难题如何破解 Foreign Tourists Face Many Inconveniences in China. How to Solve the Problems of Inbound Tourism?,” December 15, 2024. http://travel.china.com.cn/txt/2023-12/15/content_116881463.shtml#:∼:text=%E4%BC%97%E4%BF%A1%E6%97%85%E6%B8%B8%E9%9B%86%E5%9B%A2%E5%89%AF,%E5%B9%B4%E7%9A%8415%2D20%25%E3%80%82 (in Chinese).

72 Johnston, “Is Chinese Nationalism Rising?,” 42.

73 See Liu, “America’s Decoupling from China Narrative.”

74 Mellon, Jonathan. “Internet Search Data and Issue Salience: The Properties of Google Trends as a Measure of Issue Salience.” Journal of Elections, Public Opinion & Parties 24, no. 1 (2014): 45–72.

Appendix 1.

Google Trends comparison between search results using different keywords

Appendix 2.

Baidu search: 中国梦 (Chinese dream) raw data

Note:

• In the left-up corner is “Baidu Search Index – Chinese Dream (搜索指数 – 中国梦)”

• The period is from 1 January 2011 to 31 December 2023

Appendix 3.

Results of the HP filter: Baidu search using 中华民族伟大复兴(great rejuvenation) as the key phrase during 2011–2023

Appendix 4.

Ratings (0 being the lowest and 10 being the highest) from Hupu.com from 2004 to 2023

Source: https://twitter.com/whyyoutouzhele/status/1731277331472200095.

Note: This Twitter account stands as the largest Chinese account on X. It served as the primary platform for disseminating information about protests in China against the zero-COVID policy (refer to https://www.technologyreview.com/2022/12/02/1064075/teacher-li-twitter-china-protests/). Furthermore, it consistently shared submissions from its followers addressing various social issues in China (refer to https://en.wikipedia.org/wiki/Teacher_Li_Is_Not_Your_Teacher).