Introduction The development of information technology facilities an instantaneous and borderless global communication, which strengthen the influence of ideas on global events. The public diplomacy, therefore, become a vital tool for statecraft, especially for emerging powers, such as the People’s Republic of China. A year ago, China had limited numbers of diplomatic presence on Twitter. A handful of accounts, posting holiday greetings and Chinese sceneries, operated in the absence of central coordination and direction. Recent years, the number of accounts increases to over 150, which attracts Western scholars and medias with their provocative attitude and inflammatory content. While academics and press increasingly emphasize Chinese diplomats’ Twitter activities and coin them as “wolf warrior diplomacy”, they have concentrated in agitating and emotional characteristics of the tweets. This study endeavors to address the lacuna by employing text analysis to examine Chinese Twitter diplomacy: what is the actual content of the tweets. The research assesses and evaluate Chinese wolf warrior diplomacy via Twitter with regard to four characteristics, in particular—clickbait’s content, leveraging the influence networks, divert criticism by using positive content, and trolling the U.S on race. Research Question Recent stories around the “wolf warrior” diplomacy have placed attention to particular accounts, such as Zhao Lijian and Hua Chunying. By exploring and examining the tweets, this study hopes to determine whether Chinese Twitter diplomacy exhibited a coherent communication strategy or a more ad-hoc and individualistic practice. In addition, the research also focuses on the frequencies of words across tweets, and topics of tweets, suggesting a relative propaganda strategy pattern. Literature Review Digital diplomacy, which is a sub-category of public diplomacy, has evolved from a marginal diplomatic technique to a crucial component of state diplomacy. As described by Burson-Marstellers in 2017, the twitter diplomacy “has gone from being an afterthought to being the very first though of world leaders and governments across the globe, as audience flock to their Twitter newsfeeds from the latest news and statements.” As such, a growing body of research examines how Twitter serve as an efficient mechanism in the digital diplomacy. However, studies tend to focus on whether Twitter fosters a two-way exchange of ideas with foreign publics (Comor & Bean, 2012; Harris, 2013; Hayden et al.C,2013; Kampf et al., 2015; Manor, 2016). China is one of the many countries that develops and deploys communication strategy through social networking sites (Leight et al., 2011; Harris, 2013; Cull, 2010; Hocking & Melissen, 2015; Kampf et al., 2015). Even since the slogan “Going out, going global”(走出去) advocated by the central government, Beijing has pushed medias to construct a peaceful national image. The most notable example is the three state-owned media—Xinhua News Agency, People’s Daily, and China Center Television—created Twitter accounts to propagate positive image of China (Thussu, 2016). In 2013, Xi Jinping, the Chairman of the Chinese Communist Party, stipulated that the concept of external propaganda (外宣) needed to be in cooperated with “new concepts, new categories, and new expression that could be accepted by both China and foreign states”. To achieve this target, China incorporates “positive psychology” into Twitter posts to cultivate “positive emotion, engagement, relationship, meaning and accomplishment” with foreign audience (Zhang & Matingwina, 2016). Through this practices, Chinese diplomats and state-owned medias construct positive image by shaping narratives for the soft use of public diplomacy on Twitter. However, recently, as indicated by Brandt and Schafer Chinese digital diplomacy has shifted from promoting positive image to disseminating ani-Western content through its increasingly assertive tactics. Chinese diplomat’s Twitter accounts “propagate conflicting conspiracy theories, covert trolling campaigns and amplify false theories” (Brandt & Schafer, 2020). Data In order to assess the content and strategy of Chinese digital diplomacy on Twitter, the researcher employ data compiled from captured Twitter activities originating from a list of 56 ambassadors’ accounts, 97 embassies’ accounts and 7 spokespeople’s accounts. We rely on tweets published by these accounts, retweets and other metadata. The names of the accounts are included on the “Chinese Diplomats List” at the Appendix. The research collected Twitter data for five months (December 10, 2020 to April 13, 2021), using the Brandwatch service. Although the researcher has collected as many as tweets from Chinese diplomats’ Twitter accounts, the list is by no mean an exhaustive one. As a result, the corpus may suffer from selection bias. The Chinese diplomats accounts are selected from followers of Hua Chunying and Zhao Lijian, two most active Twitter users among the Chinese diplomats. The list is cross-referenced with Wikipedia, which records virtually all names of Chinese diplomats. However, even though the number of Chinese diplomats’ Twitter accounts has increased drastically, only less than half of all ambassadors, embassies, and spokespersons have Twitter accounts. Therefore, the corpus may not represent a comprehensive population. The corpus may also experience incentive bias. Although Twitter's application programming interface allows the researcher to acquire tweets from Chinese diplomats, only the existing tweets are included in the corpus. In other words, tweets that are deleted are not included in the corpus. Chinese diplomats or embassies may be voluntarily or be forced to delete or hide provoking tweets that could cast them in a negative light. This may produce a biased result towards one of our research questions: whether Twitter diplomacy exhibited a coherent communication strategy, or a more ad-hoc and individualistic practice, as ad-hoc tweets may not be included in the corpus. The third bias is a medium bias, in which the study only focuses on text. Twitter allows users to post texts, pictures, videos, and links. In this study, only texts are analyzed. Moreover, as restricted by the word limit and platform policies, Twitter's content may be tailored for Twitter. Chinese diplomats may have different experiences and incentives when using other platforms, which may lead to a different research result. Also, with the retweet function, some tweets are duplicated. This will increase the frequency of words, which may lead to a biased research outcome. The final bias is a retrieval bias. To construct the corpus, this study adopts user selection to identify the available Chinese diplomats' Twitter accounts and acquires all tweets from those accounts. The data retrieval is facilitated by Brandwatch, which returns all tweets of particular users within the recent ten years. However, although most of the Chinese diplomats' Twitter accounts are created around 2019, some diplomats, such as Zhao Lijian, created his account in 2010. This may lead to a non-exhaustive list of tweets. Hand-coding A complete dataset (n=38,077) contains all tweets and retweets collected during the time period. From which, we coded a random sample of 100 tweets. Coding of the random sample occurred in three phases. First, the researcher identified categories of wolf warrior tweets based on the article published in Brookings Institute and categories on People’s Daily(Brandt & Schafer, 2020). In the second phase, the researcher refines coding categories and made minor adjustments based on discussion with classmates. At the end of this phase, the researcher formulates a codebook which includes 4 primary substantive characteristics of wolf warrior diplomacy, multiple sub-categories, and examples for specificity which is presented in the Appendix. Finally, the coding of tweets in the sample is performed by two individuals independently and then consolidated. The intercoder reliability records 0.91 in Krippendorff’s alpha, which is a fairly high score. When there are disagreements between the coders about the categories of a code in tweet, the results are set according to the researcher’s result. Result Distinctive Words Algorithm: Fightin’ Words The Chinese application of digital diplomacy on Twitter display a coherent communication strategy, which indicates a judicious selection of words and emphasis of tweet topics. The words used in tweets are almost universal. Additionally, for many words, the data supported a direct linkage between individual diplomats and embassy over the usage of words. As shown in the following example, the tweets posted in China and tweets posted in the U.S. are highly overlapped. The most distinctive 10 words for the China category are: "farm" "today" "ceremoni" "part" "area" "take" "autonom" "peopl" "region" "major" The most distinctive 10 words for the U.S. category are: "major" "farm" "autonom” “part" "region" "area" "today" "ceremoni" "take" "peopl" To further validate the result, I re-employ the fightin’ words approach on the “Account Type” field of metadata. This field represents a user type on whether the account is an individual account or an organizational account. If an ambassador owns the account, that is an individual account. If an embassy owns the account, that is an organizational account. The most distinctive 10 words for the Individual category are: "take" "farm" "part" "area" "major" "autonom" "peopl" "today" "ceremoni" "region" The most distinctive 10 words for the Organization category are: "part" "major" "today" "ceremoni" "autonom" "farm" "peopl" "area" "region" "take" The result resonates with the “China-US” categories which present similar distinctive words. Topic models of tweets As indicated in the graph, tweets relating “Xinjiang” is most prevalent (Topic 3), represented in almost 20% of all tweets. These tweets generally response to the international condemnation of China’s repression of Uyghurs in Xinjiang and endeavors to change the negative conversation to positive. For example, in one tweet, China retweet BeltandRoadDesk that “Out of millions of Uyghurs whom western MLM claimed are in “detention camp” in Xinjiang, yet they can only find ONE woman who has been “systematically tortured “. Western MLM repeatedly used her to demonise China.” At nearly 15% of messages, “Holiday tweets” (Topic 2) received the second-most amount of tweets. “Poverty eradication program” (Topic 4) is tied for a close-third. “Hong Kong issues” (Topic 8) represents 13% of tweets. “COVID-19” (Topic 7) log in at 12% of Twitter diplomacy content. “Chinese economic performance” (Topic 1) constitutes 11% of tweets. “Meeting with foreign leaders” (Topic 5) and “Chinese scenery”(Topic 6) represents 10% and 9% of the tweets respectively. “High-speed railroad” (Topic 9) constates nearly 8% of the tweets. The result of hand-coding Although the fightin’ words and structural topic model uncover the tweets posted by Chinese diplomats exhibit a coherent communication, they are hard to distinguish from topics discovered from other countries’ digital diplomacy, such as improving bilateral relations, multilateralism, terrorism and development. In other words, by only adopting the above methods, we do not understand why the tweets are called “wolf warrior” tweets. Since text is multidimensional, tweets contain more aspects than just topic message. To further investigate the latent message that wolf warrior tweets have, I decide to hand-code a training set that randomly includes 100 tweets. The hand-coding employs two coders, one is the researcher, another one is Brydon Brancart. The wolf warrior tweets are labeled as 1, 0 the otherwise. Given the content of wolf warrior tweets not just constitute text but also videos, pictures, hyperlinks and retweets, I define the “wolf warrior” tweets are those that propagate conflicting conspiracy theories that designed to sow chaos and deflect blame, sprawl state media apparatus, convert trolling campaigns, amplify false theories, and flood conversations about China’s human rights record with positive content. By employing Naïve Bayes, the model receives over 90% in precision and 83% in recall. To perform cross-validation with Lasso, the predicted tweets by using the model correspond with the characteristics in the codebook. The examples of predicted non-wolf warrior tweets are presented as follow: 1. RT @XHNews Chinese space science satellite Insight detects fast radio burst signal from a magnetar in the Milky Way, marking a milestone in understanding the nature of mysterious signal emanating from the universe. 2. #WangYi: After 30 years of cooperation, China&ASEAN have established a shared belief in solidarity, equality & mutual assistance, developed a sense of a shared future & a partnership through thick and thin. 3. The two sides also stood firm for #multilateralism and took on global challenges together. #China-#CEEC cooperation is part and parcel of China-#EU relations, whose good progress means new opportunities for China-CEEC cooperation. 4. RT @SpokespersonCHN #UN Secretary-General congratulates #China on the successful efforts in the fight against extreme poverty. 5. Beijing Winter Olympics: Main venue for ice hockey features new technology, sustainability. https://t.co/ab6CMyPcZy 通过 @cgtnofficial The identified non-wolf warrior tweets generally promote and strengthen Sino-foreign relations using Twitter diplomacy and transfer positive emotions to target the public. However, the tweets are by no means “depoliticized.” The tweets are not only used to interpret and endorse Sino-Foreign relations but also politically endowed to promoted, implicitly, China’s policies. In other words, the non-provocative content is an essential resource for Beijing’s digital diplomacy to convey political information in a subtle manner. The machine also able to identify wolf warrior tweets, as shown below: 1. RT @MahuiChina @CaoYi_MFA Most Muslim countries in the world support China on Xinjiang. Look at the governments/politicians/thinktankers/individuals who are attacking China and think why so. 2. If forcing Christian Mestre to resign represents mainstream view of France, it only proves the despicable & disgusting media platform conspired to assault decency. They'd rather stay in dark corner to paste fakes than face simple facts & ground situations. 3. RT @ChinaDaily A new exhibition in Beijing showcases picturesque natural scenery, cultural diversity and poverty alleviation efforts in Northwest China's Xinjiang Uygur autonomous region. #Xinjiang 4. RT @CaoYi_MFA We believe the vast majority of countries in the world are sharp-eyed as they have an objective and fair assessment of Xinjiang's development and the Chinese government's policy on making Xinjiang a stable and prosperous place. 5. RT @SpokespersonCHN They chose to dance with the few anti-China elements in their clumsy dramas, instead of acknowledging the progress in #Xinjiang. The identified wolf warrior tweets correspond to the characteristics described in the codebook. The first, third, fourth and final tweets in the example shows how China responds to international condemnation of its repression of Uyghurs in Xinjiang and its endeavors to change the negative conversation to positive by promoting propaganda images of “happy” Uyghurs, rosy pictures of life in the province. The tweets also normally employ hashtags of Xinjiang. The second tweets in the example shows how China’s diplomats frame foreign government’s responses over controversial domestic issues as hypocritical. Implication This research employs text analysis in order to deduce patterns in the China’s use of Twitter as a tool of foreign policy. More specifically, the data analysis has provided insights into aspects related to China’s digital diplomacy. First, the research endeavors to determine if the China’s application of digital diplomacy is a coherent strategy. On this question, this research finds that while there is difference in ranking of the use of word, the China’s digital diplomacy largely displayed a deliberate, disciplined and coherent communication strategy. This finding helps to fill in the gap of the degree of coherence in China’s digital diplomacy. Despite the highly overlapped use of word in China’s application of digital diplomacy, the research does find a striking deviation from the conventional wisdom of wolf warrior diplomacy that tweets tend to propagate conspiracy theories and design to sow chaos and deflect blame. The topics of tweets are not purely aggressive content, although China’s responses on Xinjiang issue is identified as the top tweeting priority. Topics also include relatively neutral messages such as Chinese economic performance, and poverty eradication program. Although several fine studies on Chinese digital diplomacy aimed at single issues have been published, this study makes an important contribution to the limited current knowledge about the content of digital diplomacy, by identifying the broad range of topics which are highlighted in Chinese diplomats’ posts. Lastly, a hand-coding analysis of tweets is employed herein to offer empirical insights into what content of tweets are categorized as wolf warrior tweets. The research finds that a large majority of the wolf warrior tweets can be identified by machine learning which employs the hand-coding data as the training set. Still, some of the tweets which are with short content, and mainly with images and videos are difficult to be pinpointed. One confounding factor is the influence of heat global events, such as Hong Kong protests, human right issue in Xinjiang, on digital diplomacy. Major events are known to generate significant social media activities, which can skew the results (Kampf et al. 2015). Meanwhile, controversial global events can motivate Chinese diplomats to generate coordinated response on a heat topic, which give the Chinese propaganda agencies a platform for spreading their messages
Reference:
Brandt, J., & Schafer, B. (2020, October 28). How China's 'wolf warrior' diplomats use and abuse Twitter. Brookings. https://www.brookings.edu/techstream/how-chinas-wolf-warrior-diplomats-use-and-abuse-twitter/.
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Cull, N. J. (2010). Public diplomacy: Seven lessons for its future from its past. Place Branding and Public Diplomacy, 6(1), 11–17. https://doi.org/10.1057/pb.2010.4
Harris, B. (2013). Diplomacy 2.0: The future of social media in nation branding. The Journal of Public Diplomacy, 4(1).
Hayden, C., Waisanen, D., & Osipova, Y. (2013). Facilitating the Conversation. American Behavioral Scientist, 57(11), 1623–1642. https://doi.org/10.1177/0002764213505365
Hocking, B., & Melissen, J. (2015). Diplomacy in the digital age. Clingendael, Netherlands Institute of International Relations.
Kampf, R., Manor, I., & Segev, E. (2015). Digital Diplomacy 2.0? A Cross-national Comparison of Public Engagement in Facebook and Twitter. The Hague Journal of Diplomacy, 10(4), 331–362. https://doi.org/10.1163/1871191x-12341318
Leight, N., Walton, S. B., Ananian, T., Cruz-Enriquez, M., & Jarwaharlal, K. (2011). PDiN Quarterly – Trends in Public Diplomacy: January, February and March 2011. Place Branding and Public Diplomacy, 7(2), 136–149. https://doi.org/10.1057/pb.2011.8
Manor, I. (2016). Are we there yet have MFAs realized the potential of digital diplomacy ?: results from a cross-national comparison. Brill.
Thussu, D. K. (2016). The Scramble for Asian Soft Power in Africa. China’s Media and Soft Power in Africa, 33–45. https://doi.org/10.1057/9781137539670_3
Zhang, Y., & Matingwina, S. (2016). Constructive Journalism: A New Journalistic Paradigm of Chinese Media in Africa. China’s Media and Soft Power in Africa, 93–105. https://doi.org/10.1057/9781137539670_7
Appendix
Chinese Diplomats List
CountryAmbassadorScreen_name AfghanistanWANG Yu (王愚)@ChinaEmbKabul AlbaniaZHOU Ding (周鼎)@ChinaembassyT AngolaGONG Tao (龚韬)@ChinaEmbAngola Antigua and BarbudaSUN Ang (孙昂)@ChinaEmbAntigua ArgentinaZOU Xiaoli (邹肖力)@ChinaEmbArg AustraliaCHENG Jingye (成竞业)@chengjiny Australia — SyndeyZHOU Limin (周立民)@ChinaConSydney AustriaLI Xiaosi (李晓驷)_@li_xiaosi_@chinaembaustria BarbadosYAN Xiusheng (延秀生)_@Yxiusheng BelarusXIE Xiaoyong (谢小用)@ZhongBai2020 BelgiumCAO Zhongming (曹忠明)@ChinaAmbBelgium BotswanaZHAO Yanbo (赵彦博)@DrZhaoYanbo BrazilYANG Wanming (杨万明)_@WanmingYang_@EmbaixadaChina Brazil — Rio de JaneiroLI Yang (李杨)_@CGChinaLiYang_@ConsulChinaRJ BulgariaDong Xiaojun (董晓军)@AmbDongXiaojun BurundiLI Changlin (李昌林)@AmbChineBurundi CameroonWANG Yingwu (王英武)@AmbChineCmr CanadaCONG Peiwu (丛培武)@ChinaEmbOttawa Canada — CalgaryLU Xu (陆旭)@ChinaCGCalgary Cape VerdeDU Xiaocong (杜小丛) ChadLI Jinjin (李津津)@ambchinetchad ColombiaLAN Hu (蓝虎)@china_embajada Democratic Republic of the CongoZHU Jing(朱京)_@Amb_ZhuJing_@AmbCHINEenRDC Republic of the CongoMA Fulin (马福林)@chinaembcongobz CroatiaXU Erwen (许尔文)@ErwenXu CubaCHEN Xi (陈曦)@EmbChinaCuba CyprusLIU Yantao (刘彦涛)@AmbassadorLiu DenmarkFENG Tie (冯铁)@ChinaInDenmark DjiboutiZHUI Ruisheng (卓瑞生)@ChineAmbDjibout Dominican RepublicZHANG Run (张润)_@EmbZhangRun_@ChinaEmbajadaRD EcuadorCHEN Guoyou (陈国友)@EmbajadaChinaEc EgyptLIAO Liqiang (廖力强)_@AmbLiaoLiqiang_@CHN_EGY El SalvadorOU Jianhong (欧箭虹)_@oujianhong_@EmbajadaChinaSV EthiopiaZHAO Zhiyuan (赵志远)@ChinaEmbAddis FijiQIAN Bo (钱波)@ChineseEmb_FJ FinlandCHEN Li (陈立)@ChinaEmbFinland France[6]LU Shaye(卢沙野)@AmbassadeChine France — StarsbourgLING Jun (凌军)@consulat_de GermanyWU Ken (吴恳)@ChinaEmbGermany Germany — HamburgDU Xiaohui (杜晓晖)@GeneralkonsulDu GhanaLU Kun (卢坤)@ChinaEmbinGH GreeceZHANG Qiyue (章启月)@Chinaemb_Hellas GrenadaZHAO Yongchen_@ChinaEmbGrenada_@DrZhaoyongchen GuineaHUANG Wei (黄巍)@chine_guinee HungaryQI Dayu (齐大愚)@ChineseEmbinHU IndiaSUN Weidong (孙卫东)_@China_Amb_India_@ChinaSpox_India India — KolkataZHA Liyou (查立友)@ZhaLiyou IranCHANG Hua (常华)@AmbChangHua IraqZHANG Tao (张涛)@ChinaIraq IrelandHE Xiangdong (何向东)@ChinaEmbIreland Italy[7]LI Junhua (李军华)@AmbCina JapanKONG Xuanyou (孔铉佑)@ChnEmbassy_jp Japan — NagoyaLIU Xiaojun (刘晓军)@ChnConsulateNgo Japan — NiigataSUN Dagang （孙大刚）@ChnConsulateNgt
Japan — OsakaHE Zhenliang (何振良)@ChnConsul_osaka Japan — FukuokaLV Guijun (律桂军)@ChnConsulateFuk JordanCHEN Chuandong (陈传东)@ChineseembassyJ KazakhstanZHANG Xiao (张霄)@ChinaEmbKazakh KenyaZHOU Pingjian (周平剑)@ChineseEmbKenya KiribatiTANG Songgen (唐松根)@TSonggen Nrth KoreaLiu Xiaoming（刘晓明)@AmbLiuXiaoMing South KoreaXING Haiming (邢海明)suspended South Korea — JejuWANG Luxin@jejuZLG KuwaitLI Minggang (李名刚)@ChinaEmbKuwait KyrgyzstanDU Dewen (杜德文) LebanonWANG Kejian (王克俭)_@ChinainLebanon_@CaoYi_MFA LesothoLEI Kezhong (雷克中)_@AmbassadorLei_@ChinaEmbLesotho LiberiaREN Yisheng (任义生)@ChineseLiberia Liechtenstein[9]ZHAO Qinghua (Consul General)@Dr_ZhaoQinghua LithuaniaSHEN Zhifei (申知非)@ZhifeiShen MalawiLIU Hongyang (刘洪洋)_@LiuHongyang4_@ChinaEmbassy_MW MaldivesZHANG Lizhong (张利忠)don't exist MaliZHU Liying (朱立英)_@LiyingZHU1_@Chine_au_Mali MaltaYU Dunhai (于敦海)_@Ydunhai_@ChinaEmbMalta MauritaniaVacant@ChinaEmbinMR MontenegroLIU Jin (刘晋)@ChineseEmbinMNE NamibiaZHANG Yiming (张益明)@Amb_Yiming NepalHOU Yanqi (侯艳琪)@PRCAmbNepal Netherlands[10]TAN Jian (谈践)@ChinaEmbNL NigeriaVacant@china_emb_ng OmanLI Lingbing (李凌冰)@ChinaEmbOman PakistanNonG Rong (农融)_@AmbNong_@CathayPak PanamaWEI Qiang (魏强)@weiasecas Papua New GuineaXUE Bing (薛冰)@ChineseEmb_PNG PeruLIANG Yu (梁宇)@ChinaEmbPeru PhilippinesHUANG Xilian (黄溪连)@Chinaembmanila PolandLIU Guangyuan (刘光源)_@ChinaEmbPoland_@AmbLiuGuangYuan QatarZHOU Jian (周剑)@AmbZhouJian RussiaZHANG Hanhui (张汉晖)@ChineseEmbinRus SamoaCHAO Xiaoliang (巢小良)@chinaandsamoa Saudi ArabiaCHEN Weiqing (陈伟庆)_@AmbChenWeiqing_@ChinaEmbKSA SenegalXIAO Han (肖晗)@ChineAmbassade SerbiaCHEN Bo (陈波)_@AmbChenBo_@EmbChina_RS SlovakiaSUN Lijie (孙立杰)@ChinaEmbSVK SloveniaWANG Shunqing (王顺卿)@ChinaEmSlovenia SomaliaQIN Jian (覃俭)_@AmbSomQinJian_@ChineseSomalia South AfricaCHEN Xiaodong (陈晓东)@AmbCHENXiaodong South Africa — Cape TownLIN Jing (林静)@CGCHINA_CPT TANG Zhongdong@ChnConsulateJhb Spain[11]WU Haitao (吴海涛)@ChinaEmbEsp Spain -- BarcelonaLIN Nan (林楠）@ConsulChinaBcn Sri LankaQI Zhenhong (戚振宏)@ChinaEmbSL SurinameLIU Quan (刘全)_@AmbLiuQuan_@CHNEmbSuriname SyriaFENG Biao (冯飚)@AmbFengBiao TanzaniaWANG Ke (王克)@ChineseEmbTZ TongaCAO Xiaolin(曹小林)@embassy_chinese Trinidad and TobagoFANG Qiu (方遒)@AmbFangQiu TurkeyLIU Shaobin (刘少宾)@ChinaEmbTurkey Turkey — IstanbulCUI Wei (崔巍)@chinaconsulist UgandaZHENG Zhuqiang (郑竹强)_@ChinaAmbUganda_@ChineseEmb_Uga UkraineFAN Xianrong (范先荣)@China_Ukraine_ United Arab EmiratesNI Jian (倪坚) United Arab Emirates — DubaiLI Xuhang (李旭航)@CGPRCinDubai United KingdomZheng Zeguang (郑泽光) (incoming)@ChineseEmbinUK United Kingdom — BelfastZHANG Meifang (张美芳)_@CGMeifangZhang_@CCGBelfast United Kingdom — EdinburghMA Qiang (马强)@chinacgedi United StatesCUI Tiankai (崔天凯)_@AmbCuiTiankai_@ChineseEmbinUS United States — San FranciscoWANG Donghua (王东华)_@Wdonghua_@ConsulateSan United States — ChicagoZHAO Jian (赵建)@ChinaConsulate United States — Los AngelesZHANG Ping (张平)@CGZhangPingLA VenezuelaLI Baorong (李宝荣)_@Li_Baorong_@Emb_ChinaVen YemenKANG Yong (康勇)@ChineseEmbtoYEM ZimbabweGUO Shaochun (郭少春)_@China_Amb_Zim_@ChineseZimbabwe Association of Southeast Asian NationsDeng Xijun (邓锡军)@China2ASEAN African UnionLIU Yuxi (刘豫锡)@Ambassador_Liu European UnionZHANG Ming (张明)@ChinaEUMission United NationsZHANG Jun (张军)_@ChinaAmbUN_@Chinamission2un_@CHN_UN_NYUnited Nations Office in GenevaCHEN Xu (陈旭)_@Amb_ChenXu_@ChinaMissionGvaUnited Nations Office in ViennaWANG Qun (王群)@ChinaMissionVieOrganisation for the Prohibition of Chemical Weapons[10]TAN Jian (谈践)@China_OPCW
Codebook
Four Characteristics of wolf warrior tweets
Mixing Beijing-friendly messaging with clickbait’s content
1. Viral memes (https://twitter.com/SpokespersonCHN/status/1313853846695735304)
2. Panda videos (https://twitter.com/China2ASEAN/status/1299979978642087938)
3. Confrontation content (https://twitter.com/SpokespersonCHN/status/1246665952139198464)
4. Conspiratorial content (https://twitter.com/zlj517/status/1280131459429232645 )
Leveraging the influence networks of other autocrats by amplify content from alt-media outlets, journalists, pseudo-academics, activists, conspiracy theorists
1. Xinjiang
Example: It seems that some US officials enjoy smearing China around the clock & around the world. What they say about Xinjiang is the LIE of the CENTURY. LYING and CHEATING won't make you nobler and greater. Why not come to Xinjiang and see with your own eyes?
2. Hong Kong National Security
Example: The National Security Law helps Hong Kong restore peace and stability.
3. Technology
Example: TikTok to SUE Trump over ‘unconstitutional’ ban as Twitter joins battle for its US assets & users – reports
4. COVID-19
Example: What did they know, exactly? US intel warned of ‘cataclysmic’ coronavirus pandemic in NOVEMBER 2019
5. Protests in Hong Kong
Example: THUGS & HEROES HYPOCRISY
6. Chinese sanction on foreign officials
Example: China sanction 11 US individuals over Hong Kong affairs. Here is the list #China #US #HongKong @MFC_China @zlj517 @Chinamission2un @BBCWorld @CNN @XHNews @CGTNOfficial @PDChina @globaltimesnews @ChinaDaily @RT_com @NHKWORLD_News @ChineseEmbinUS @ChineseembinUK @ChinaEUmission
Using ‘positive’ content to drown out criticism
1. Propaganda images of happy life in Xinjiang
Example: Welcome to Urumqi, the capital of Xinjiang, China.
2. Retweets from the following accounts
Example: Discover Xinjiang (@DXinjiang), Xinjiang Channel (@Xinjiangchannel)
3. Hashtags
Example: #AmazingXinjiang, #AmazingChina
Trolling the U.S on Race
China’s diplomats frame the U.S. government’s heavy-handed responses over domestic protests as hypocritical:
1. Hashtags
Example: #BlackLivesMatter #GeorgeFloyd #IcantBreathe
2. Accusing U.S. applies double standards
Example: US double standards on domestic riots and Hong Kong turmoil mocked on Chinese internet
3. Applying “whataboutism” to deflect criticism of its own actions
Example: "I can't breathe."
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