Keywords

Often considered as a central dynamic in political movement and activism, emotions—such as anger, fear, pride, and disgust—accompany, condition, and coordinate every stage of movement and activism (e.g., Aminzade & McAdam, 2002, p. 140; Goodwin & Jasper, 2004; Goodwin et al., 2009; Herzog & Golden, 2009; Jasper, 2011, 2018). Meanwhile, as “human capacities for emotion evolved to increase moral commitments to others, social structures and culture,” as Turner and Stets (2006, p. 544) explicated, human emotions “are ultimately connected to morality.” Activists and movement organizations utilize moral judgment to motivate political action as emotionally laden conscientious objection (e.g., Horberg et al., 2011), evoke moral shock and outrage to spur movement participation even in the absence of a network of contacts (e.g., Goodwin et al., 2000), and maneuver moral appeal and rhetoric to heighten positive emotions for mobilization and involvement (e.g., Jung, 2020; Lipsitz, 2018).

Yet studies concerning emotions in online activism—let alone emotions and morality—have remained “marginal” (Ahmed et al., 2017, p. 447), even though the Internet, especially social media, is increasingly becoming a relevant sphere for the expression, activation, and contagion of emotions when people engage in political behavior (e.g., Ahmed et al., 2017; Jones et al., 2013; Knudsen & Stage, 2012). So far, scholarship in this vein has paid less attention to the complexity between emotions and different political participation behaviors in online activism. As Wahl-Jorgensen (2012) explained, a presumption that considers emotion as the opposite of reason and rationality fundamentally leads to such a lacuna in interrogating mediated political participation. Furthermore, among studies that have explored emotions and political participation, most have considered cases in democratic contexts (e.g., Lee & Kwak, 2014; Valentino et al., 2011), leaving fewer looking at cases in a nondemocratic context, where a repressive or high-risk sociopolitical context may lead to distinctive patterns of emotional expression (e.g., Dal & Nisbet, 2020; Yang & Jiang, 2015).

To fill in the lacuna, this chapter analyzes emotional expressions and corresponding moral dimensions in messages posted on the Chinese social media Weibo, and the participation character of public responses online, modeling their emergence and trajectories, and explaining the conditions that are necessary for them to evolve. The Quangang “carbon nine leak incident,” representing online environmental activism in 2018, is used as the case, with the investigation of emotional expressions in social media posts and different types of political participation online, both quantitatively and qualitatively. Our emotion-rich findings offer the following insights and implications for the understudied complexity of emotions and political participation in an authoritarian context. For one thing, the relationship between different emotional expressions and online participation remains complicated and thus cannot be grouped together without regard for the specific event and its context. For another, a deliberative appropriation and management of moral dimensions in a repressive context have shaped emotional expressions into different roles than those in a democratic context. Particularly, this study reveals how the management and performance of moral emotions like anger and disgust by activists succeeded in attracting attention and encouraging online political participation in an authoritarian context. Besides, as basic human moral principles and foundations, empathy and sympathy—moral experiences in short—also facilitated the generation and expression of activists’ emotions. By doing so, we advocate that a contextualized understanding of both emotions and morality in social movements should drive scholarly inquiry.

In the sections below, we first present a review of scholarship concerning emotions, morality, and (online) political activism, to illustrate the bourgeoning research into emotions and online activism. With an acknowledgment of their contributions, we pinpoint two gaps that our study fills: the lack of understanding of the complexity of emotions, morality, and online participation behaviors, and the less-studied dimension of emotions and online activism in a nondemocratic context. Then, we draw on theories of emotion and online political participation behaviors as a basis for our theoretical reasoning, and we propose our research questions. Third, we lay out our methodological strategy, including case selection, data collection, and analytical approaches. Fourth, we present our findings and discussions with plausible explanations, limitations, and reflections on our conclusion.

Emotions in Political Participation

Discussion of the role of emotions in political participation has experienced a process of being central, abolished, and resurgent (Goodwin et al., 2000; Jasper, 1998, 2011). Until the 1960s, emotions occupied a core role in crowds’ political behavior outside normal institutions (e.g., Le Bon, 1897, p. 51; Turner & Killian, 1957). Yet emotions can sometimes denote immorality, while activists are sometimes considered to be insane, alienated (Kornhauser, 1959), and socially dysfunctional (Lasswell, 1986). Rational-actor, structural, and organizational models, then, shifted their focus away from analyses of emotions (e.g., Gamson, 1975; McAdam, 1982), as political participants have been treated as being rational and morally acceptable, driven by an organization-based instrumental logic that “prevent[s] their being emotional” (Goodwin et al., 2000, p. 70).

Yet as later studies have argued, emotionality should not be treated as counterposing, but rather as complementary to and interlaced with rationality. As Goodwin et al. (2009, p. 9) explained, “emotions can be strategically used by activists and be the basis for strategic thought.” The integration of the cultural–emotional dimension of social movements—“the cultural turn” coined in some studies (e.g., Goodwin et al., 2000, p. 77; Goodwin et al., 2004)—restores and revives the necessity to recognize and capture emotional motivations and moral sensitivities for political action (Hoggett & Thompson, 2012; Jasper, 2008). As Goodwin and Pfaff (2001, p. 301) argued, “bringing emotions back in” is important not so much for the experiential richness it uncovers but because it “promises … a better causal understanding of the ‘nuts and bolts’ of popular mobilization, including a better grasp of factors like social networks, collective identities, and shared beliefs.”

With acknowledgment of emotion as a significant element in movement and activism, studies have explicated various roles that many types of emotions and moral impulses play in inspiring, energizing, or inhibiting political action when citizens engage with politics in different contexts. As a moral emotion “based on moral intuitions and principles” (Jasper, 2011, p. 287), anger is often considered to be a pivotal factor in the recruitment to, motivation for, and sustainability of political participation (Gould, 2009; Kühne & Schemer, 2015; Rodgers, 2010; Stürmer & Simon, 2009). As the most prevalent emotion in movements (Goodwin & Pfaff, 2001, p. 285), fear or moral panic would do the most to cripple collective action and destroy political rationality, as it leads people to act hastily—to panic—rather than to evaluate actions carefully (Jasper, 2018, p. 38). While positive emotions like pride, joy, happiness, and compassion would move people to engage in protest and express discontent (Ammaturo, 2016; Goodwin et al., 2000), negative emotions such as frustration, disgust (Herzog & Golden, 2009), shame (Goodwin & Pfaff, 2001), and guilt (Norgaard, 2006) may discourage engagement in political action (for a general discussion, see Whittier, 2011). In reality, political activists strategize which types of emotions to display, as emotions differ in their hierarchies of values and moral (in)superiority and their subsequent capacities to stimulate or suppress various participation behaviors (Goodwin et al., 2004).

While the question of how different online or computer-mediated emotion is from face-to-face emotion may remain somehow contested (e.g., Manstead et al., 2011; Rice & Love, 1987), studies have increasingly acknowledged the similarity of the communication of emotions in face-to-face and computer-mediated interactions (Derks et al., 2008; Garde-Hansen & Gorton, 2013; Manstead et al., 2011). Following such acknowledgment, the explanatory value of emotions in political behavior has been employed in the elaboration of online activism. For instance, blended with opinion, fact, and emotion, tweets during the Egyptian Uprising of 2011 entailed emotive and phatic expressions, consequently establishing “affective publics” that were mobilized through expressions of sentiment, and engaging them with politics emotionally (Papacharissi, 2015; Papacharissi & de Fatima Oliveira, 2012). Margolin and Liao (2018) explained the role of emotional expression in building solidarity and sustaining participation among social media crowds. Valenzuela et al. (2012) found that Facebook use illustrates political grievances as “the most important driver of protest behavior.” Himelboim et al. (2016) interrogated how emotional valence—positive and negative affect—shapes Twitter conversations on politics. Terms like “affective online environment” (Knudsen & Stage, 2012, p. 149) and “online emotional appeals” (Jones et al., 2013) have emerged to denote the emotion-rich circumstance of the online environment and emotion-driven political expression and activism within it.

Without denying the relevance of existing scholarship, we wish to point to two limitations, which this study addresses. First, even though studies have illustrated the role of emotions in online activism, most of them have delimited the scope of online political participation as posting or sharing (i.e., reposting) behavior on social media. To be clear, previous studies have oversimplified a variety of forms and degrees of political participation behaviors online by primarily focusing on what people post (e.g., Ahmed et al., 2017; Himelboim et al., 2016; Margolin & Liao, 2018) or repost (Song et al., 2016) on social media. Yet the conceptualization of online political participation involves a range of political “acts” (Verba & Nie, 1987, p. 2) that capture different means and interactions that are enabled by the affordance of digital technology and taken by citizens to engage in politics beyond (re)posting behavior (e.g., Bakker & De Vreese, 2011; Vissers & Stolle, 2014). In a general discussion, Bakker and De Vreese (2011) differentiated between digital active participation (including responding to information online, signing a petition online, and online poll participation) and digital passive participation (visiting different websites) on the Internet. Taking Facebook-based participation and traditional offline participation into consideration, Vissers and Stolle (2014) illustrated how Facebook fosters a range of political participation activities, such as “liking” and starting or joining a Facebook group. Furthermore, Carlsen et al. (2021) illustrated the influence of patterns of online interaction on shaping divergent individual-level participation activities in political protest. Given the consideration of diverse participation behavior online, we hypothesize the following:

Hypothesis: Different emotional expressions exert varying influence on various participation behaviors online.

The other limitation points to the fact that existing studies have been predominantly situated in the democratic context, with little attention being paid to the authoritarian context, where freedom of expression may be curtailed by repression and emotional expression thus encounters suppression by the regime (Calingaert, 2010; Riis & Woodhead, 2010). Emotions are furthermore contextually articulated, experienced, perceived, and regulated (Barrett et al., 2011; Mesquita & Boiger, 2014; Scherer et al., 2011; van Kleef et al., 2016), as “context both produces emotion and shapes how emotion is interpreted” (Greenaway et al., 2018, p. 2). Activists subsequently perform “emotion work,” or “the act of trying to change in degree or quality an emotion or feeling” (Hochschild, 1979, p. 561), to shape the trajectory of the movement and leverage its outcome. We hence ask the following:

Research Question (RQ): How do online users express themselves via emotion work in the authoritarian context, and with which kind of political participation behaviors as the result, when they face the regime’s suppression?

Method

Case Selection

We take online environmental activism in the “carbon nine leak incident” (hereafter “the incident”) in Quangang, in southeast China’s Fujian Province, as a paradigmatic case study (Flyvbjerg, 2006, p. 232) for emotions and online political participation, a case that highlights general characteristics of online environmentally driven political participation in contemporary China (also see, e.g., Brunner, 2017). The incident involved a petrochemical spill into the sea, with water and air pollution and 52 nearby residents hospitalized for medical treatment, due to the suspicion of being exposed to the leaked petrochemical contaminant (Shen, 2018). Both news media, like the Communist Party mouthpiece People’s Daily, and social media, including Weibo, covered this incident, so that it drew national attention. The discussions included Weibo users calling on the public to pay attention to this incident, arguing against the government’s reaction, questioning the authenticity of the information, and urging the authorities to publish the truth and take effective action to reduce the damage.

We choose the discussion of the incident on Weibo for the following three reasons. First, Weibo maintains an influential platform in contemporary China. Over 130 million, daily active users have established Weibo as a vibrant, contested, and high-visibility space in which people express and share opinions on political issues, disclose and criticize government malfeasance, and mobilize political action even “before authorities and censors [can] react” (Chan et al., 2013, p. 384). For that reason, Weibo remains a prime mechanism for exploring the evolving participation in online activism. Second, environmental activism is received with more tolerance by the authorities than other types of activism. Environmental activism mainly concerns environmental issues and does not challenge the authoritarian role, which fundamentally lowers the political risk of the activism itself, decreases the level of censorship by the regime, and hence spurs political participation (e.g., Sullivan & Xie, 2009; Yang, 2009).

Third, while “affective appeals” (Brunner, 2017, p. 666), such as communication of grievances (Pu & Scanlan, 2012), flourish in online activism, in recent years the regime has adopted new strategies to govern online expression via the discourse of “wenming,” or civility, to suppress negative emotional energies like anger and indignation in order to demobilize activism online (Yang, 2018). Discerning emotional expressions in online activism in China hence offers a worthwhile opportunity to probe into the issue of how such new strategies of governance may discourage or undermine online activism, or how Internet users tactically employ emotion work to counter the government’s “civilizing” initiative—thereby offering invaluable insight into an understudied field.

Research Design

We employed an exploratory mixed-methods (quantitative and qualitative) research design to analyze the data set. This design was most appropriate because we wanted to explore and explain the nature of emotions and online political participation by reducing overreliance on statistical data to explain a social occurrence and experiences that were mostly subjective (i.e., emotions) in nature. More specifically, in attempting to analyze the data, multiple linear regression and qualitative content analysis were combined according to the type of data analysis needed. While quantitative regression analysis can provide much room for identifying predictive variables, qualitative analysis allows for a nuanced interpretation and insight into meanings within online posters and interactions. For the qualitative part, we selected examples from posters on the Quangang event for analysis. The research was conducted in phases between November 4, the day that the incident occurred, and November 30, 5 days after the authorities announced the official result of the investigation. The data were collected sequentially to explore and to explain participation patterns that emerged in relation to various emotions. In short, statistical analysis and qualitative content analysis were combined and considered complementary to each other (Johnson et al., 2007) because they all helped in elaborating different aspects of emotions and online participation on the site as directed by the research questions.

Sample

To operationalize our hypothesis and RQ about how emotional expressions and emotion work shape various online participation behaviors, we collected original content (Weibo posts; their released time; and numbers of likes, comments, and shares) over the 26-day period. Given the affordances of Weibo, the types of online participation behaviors in this case involve posting, sharing, “liking,” and commenting.

We adopted “Quangang carbon nine” as the keyword on an hourly basis on the advanced search page and extracted the publicly accessible content of the posts via the User Timeline Application Programming Interface (API) function, as allowed by Weibo.Footnote 1 We chose publicly accessible posts rather than censored ones, if any, because the former allowed us to explore the observable public’s emotional reaction to the incident.

In total, 70,869 Weibo posts were collected. From among them, we randomly selected 1% (i.e., 709 posts). After data cleaning to remove content such as advertisements, we got 497 valid posts as the dataset for this study.

Coding, Measurement, and Analytical Strategies

We started with manual coding of the types of emotions observed in the posts and of the types of participation behaviors online. Then, through interpretive inquiry (Creswell & Poth, 2017, p. 39) concerning the content, we explored plausible relations among emotional expressions, emotion work, and political participation behaviors online.

For the quantitative analysis, we did not apply automatic sentiment detection methods, as it is still difficult for computer programs to automatically identify emotions in rhetoric (Quan & Ren, 2010) and the specific context of emotional content (Küster & Kapps, 2013). Expression on Weibo would be even more complicated and obtuse than on other social media like Twitter, since people adopt various rhetorical skills to evade censorship (Yang & Jiang, 2015). Manual coding, instead of automated computational methods, ensures accuracy and reliability. To do so, we established a coding scheme to identify different emotional expressions of posts and different online political participation behaviors. For emotional expressions, we first differentiated between posts with emotional expression or not, in terms of the definition of Derks et al. (2008, pp. 767–768), i.e., emotional communication as “the recognition, expression and sharing of emotions or moods between two or more individuals” in both explicit and implicit ways. For posts with emotional expressions, we then adopted Ekman’s model that divides emotions into six basic types, i.e., happiness, sadness, anger, fear, surprise, and disgust (Ekman, 1994; Ekman & Friesen, 1971), and we integrated the definitions in VandenBos (2007) and Cherry (2020). Meanwhile, as emotional expressions could be ambiguous and complex, we added “others” as the seventh type. A detailed coding and measurement process, through an iterative process, deployed the following categorization:

  1. 1.

    Whether posts contained emotional expression or not. This variable identified Weibo content that involved emotional expression or nonemotional content, such as a statement of a fact (e.g., a news report, official announcement, scientific knowledge about the pollutant, and so on), or a post only involving a hashtag without any subjective emotional expression.

  2. 2.

    Among posts with emotional expression, we identified and labeled such emotions:

    Happiness, a pleasant emotional state characterized by feelings of contentment, joy, gladness, gratification, satisfaction, and well-being.

    Sadness, an unhappy emotional state characterized by feelings of disappointment, grief, hopelessness, disinterest, and dampened mood.

    Anger, characterized by feelings of hostility, frustration, and antagonism toward others. It manifests itself as behaviors designed to remove the object of the anger (e.g., determined action) or behaviors designed merely to express the emotion (e.g., swearing).

    Disgust, a strong aversion, e.g., to the taste, smell, or touch of something deemed revolting, or toward a person or behavior deemed morally repugnant.

    Surprise, typically resulting from the violation of an expectation or the detection of novelty in the environment, which can be positive, negative, or neutral.

    Fear, a basic, intense emotional response to an immediate threat.

    And Others, i.e., ambiguous cases.

Examples of each type of emotional Weibo post are shown in (Appendix, Table 12.3).

Concerning the types of political participation behaviors online, as stated we looked at (a) posting behavior, represented by the number of posts every day; and (b) corresponding reactions to posts with emotional expression, represented by the numbers of shares, comments, and “likes.” The relationship between different emotional expressions and their reactions exemplifies the complexity of emotions and various participation behaviors online.

Two native Chinese speakers familiar with Weibo and Chinese politics applied the set of codes. They assessed each of the seven types of emotions in every Weibo post in the dataset. For instance, in our data, when one post stated “So many [people] are reposting information [on this incident], but it [the topic] still cannot be seen on the list of the trending topics? It is shocking!!!,” such narrative exemplifies how the poster perceived the control over social media trends in this case as the violation of an expectation—or, the emotion of “surprise.” Similarly, when a post claimed that “Do you not feel embarrassed or ashamed when eating people’s ‘steamed bun’? That’s too much!!!!!!!!!!!!!!,” the multiple exclamation marks indicate extreme anger. Furthermore, if a post contained multiple emotional expressions, all types of emotions would be recorded. The two coders jointly coded the first 120 posts, and after a discussion of the differences and achievement of consensus, they independently coded the remaining 377 posts. The intercoder reliability was between 0.940 and 0.730 (Cohen’s kappa, more details in Appendix, Table 12.4). As a result of this coding, the number of each type of Weibo posting is shown in Table 12.1. The total number of posts of each specific type exceeds the total number of emotional Weibo posts because when a post contains many kinds of emotions, it will be marked several times.

Table 12.1 Distribution of Weibo with different emotional types
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In the establishment of a multiple linear regression model, the independent variables were the daily emotional intensity of seven types of emotions, indicated by the number of Weibo posts of each type of emotion per day, and the dependent variables were the participation behaviors of actors every day , represented by the number of instances of forwarding, comments, and “likes.” Statistical analysis was conducted via SPSS 20.0.

Analysis Results

Descriptive Analysis

Figures 12.1 and 12.2 show the number of Weibo posts that included the keyword “Quangang carbon nine” and the numbers of their corresponding shares, comments, and likes on a daily basis. As Fig. 12.1 shows, the discussion began to ferment and grow on November 5, illustrated by an increase in posting behavior as people actively joined in the discussion. The number of discussions reached a first peak on November 6 and a second one on November 8, before decreasing. On November 25, the day when the government released the official result of the investigation, the number of discussions increased.

Fig. 12.1
figure 1

The number of Weibo posts on a daily basis

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Fig. 12.2
figure 2

The numbers of shares, comments, and “likes” on a daily basis

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The trend for the numbers of shares, comments, and “likes,” representing different participation behaviors, demonstrates a similar pattern, as shown in Fig. 12.2.

Regarding various emotional expressions, disgust (mean [M] = 3.67) is the strongest emotion, followed by sadness (M = 2.19), anger (M = 1.41), surprise (M = 0.56), and happiness (M = 0.44). Yet surprisingly, fear (M = 0.37) is not as strong as other types of emotions, even though the Quangang carbon nine event was a serious pollution accident that was supposed to trigger frightened responses about the health threat by air and water pollution from the leakage. Moreover, the “others” type is also relatively strong (M = 1.67).

A closer look at the evolution of various emotional expressions (see Fig. 12.3) tells us that emotional expressions escalated between November 5 and November 11 and achieved a peak for disgust, sadness, anger, and other emotions. Then, around November 25, emotional expressions heightened again, when the local government released the official investigation, conceding that the actual leakage volume turned out to be almost ten times that was announced in the beginning (Quangang District Environmental Protection Bureau, 2018). Disgust, anger, surprise, sadness, and other emotions then intensified between November 25 and 27.

Fig. 12.3
figure 3

The trajectories of different types of emotional expression

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Taking the trajectories of various emotional expressions in Weibo posts and different online participation behaviors into consideration, we see, first, that the general trend of emotional intensity was by and large consistent with that of online discussions on a daily basis. Second, as for participation behaviors for posts with emotional expressions—i.e., shares, comments, and likes—people’s emotions mounted in the same way as the numbers of shares, comments, and likes around November 10 and 25. Yet on November 7, when the intensities of disgust, sadness, and anger dropped significantly, sharing and liking behavior reached a small peak instead. Similarly, the next day, when emotional expressions accelerated, their level of participation declined—which seems contrary to most extant studies reported (Gould, 2009; Kühne & Schemer, 2015; Leach et al., 2006; Rodgers, 2010). This implies that there would be a disparate impact of different emotions on various participation behaviors.

Hypothesis Testing

We started with a statistical analysis of the hand-coded sample of observed emotions in Weibo posts. To explore the influence of different emotional expressions on online political participation behaviors, we conducted multiple linear regression with the numbers of seven types of emotional expression (i.e., six basic emotions and “others”) in Weibo posts as independent variables (IVs) , and the numbers of shares, comments, and likes as dependent variables (DVs) on a daily basis. After modal optimization, invalid IVs were excluded automatically. The regression analysis revealed different types of emotional expressions and their divergent impact on different types of participation behaviors online (Table 12.2).

Table 12.2 OLS Regression models of the relationship between emotional expressions and online political participation behaviors
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More specifically, Table 12.2 first reveals that different emotional expressions exerted a distinct influence on the same type of participation behavior. For the sharing behavior, surprise (B = 330.844***), sadness (B = 65.051**), and others (B = 33.997*) showed a positive relationship with the number of shares, while disgust (B = −77.406***) had a negative relationship. For the commenting behavior, surprise (B = 264.728***), anger (B = 49.320*), and fear (B = 81.463*) exerted a positive impact, while disgust (B = −53.591***) remained a negative impact. For the “like” behavior, surprise (B = 407.849***) had a positive impact, yet fear (B = −265.408**) had a negative one.

Second, as illustrated in Table 12.2, we found that the same type of emotional expression generates diverging influence on participation behaviors. While surprise can best lead to all three types of online participation behavior—which has been less recognized in the literature—disgust inhibits both sharing and commenting behavior. Sadness facilitates sharing behavior, while anger encourages commenting behavior. Fear promotes commenting behavior but hinders “like” behavior. To summarize, these findings confirm our hypothesis that different emotional expressions have a varied impact on different participation behaviors online.

Discussions

To answer the question regarding how online users express themselves via emotion in the authoritarian context, and with which types of political participation behaviors as the result, in this section, we complemented the statistical findings with qualitative interpretations of the content of the posts, to explain the appropriateness of emotions and morality as well as subsequent participation behavior.

The Trajectory of Emotions and Online Participations

An overview of the evolving of the event sets the background for the discussion. Online activism participation reached its peak on November 7, 10, and 25 (Fig. 12.2). On November 7, an unverified Weibo user circulated a sentimental post in a prose-like way, expressing grief at the pollution of Quangang. This post attracted a significant number of incidences of sharing and praising. On November 10, Toutiao Xinwen, i.e., Sina News Center, released an open letter from the United Front Department of Quangang District on the leakage of carbon nine, calling on the public not to believe or spread rumors. Against its expectations, the post instead triggered strong contention, resulting in a large number of Weibo users expressing their dissatisfaction through sharing and commenting behavior. On November 25, CCTV News, the official account of the state television broadcaster China Central Television (CCTV) ‘s news center, released a briefing on the Quanzhou Municipal Government’s press conference, claiming that the incident was a malicious concealment of the real leakage volume by the enterprise involved and that compulsory measures had already been taken against the persons responsible. This briefing further sparked the third wave of online participation.

Against the backdrop, throughout the event, the disgust emotion mainly involves the public’s criticism and dissatisfaction with the government’s reactions to the aftermath of the accident, along with the public’s aversion to the government’s excessive control over the flow of information. The sadness, next, mainly refers to sympathy and compassion for the victims of the accident, but also disappointment and helplessness in the face of local government inaction. The emotional content of anger is similar to that of disgust. Nevertheless, the expression of anger is more intense and confrontational than that of disgust. After the accident happened, some responses of the local government, such as very short and indifferent news briefings, were considered to illustrate a lack of concern for the victims and thus a violation of the basic moral principles of the public, which subsequently caused people’s aversion and moral outrage. Then, the surprise emotion in this scenario mainly denotes the public’s surprise to the information about the accident announced by the local government. Furthermore, the surprise entails the public’s doubt and distrust of the local government. The starting point of fear is both the short-term and long-term health threats caused by air and water pollution from the accident. The happiness emotion is significantly different from the general meaning of pleasure and delight. It instead exemplifies people’s support and appreciation of media organizations and individual Weibo users, both of which dared to express their true voice on the social media.

Emotional Expressions Toward the Incident, Morality, and Political Participation

A scrutiny of the content of the Weibo posts reveals that fear, sadness, disgust, and anger largely derived from the attitude toward the incident per se, including toward the government’s reaction. While fear revolved around environmental pollution, sadness disclosed disappointment and helplessness toward local authorities’ inaction and censorship of the incident, as well as sympathy and compassion for the local victims. Disgust and anger furthermore pointed to the government’s evasion of responsibility and information control.

Fear, first of all, stemming from public concern about the environment and human health, explicitly soared, since the incident resulted in serious harm to the well-being of neighboring residents and the local environment. Weibo users employed exclamation marks and metaphors to express their anxiety and panic—and more precisely, fear—about possible deleterious effects of the leakage on human health. For instance, describing the incident as “a Holocaust,” one Weibo user exclaimed, “Too horrible!! … It [the leakage] is about the lives of hundreds of thousands of people … I have asked my mother not to buy any seafood in spite of the low price recently! Trembling with fear!” (@User A, anonymized name to protect identity, the same hereinafter). Similarly, another user compared the leakage to “Resident Evil,” the Japanese horror game with pollution-infected zombies. Fear, essentially triggered by environmental concern, attracted people’s attention and sparked participation.

Second, sadness derived from two follow-up aspects. For one thing, it involved disappointment and helplessness toward the local authorities’ inaction and, in particular, their suppression of online discussion. For instance, in the face of the local government’s control of dissent and its improper handling of the aftermath of this accident, Weibo users felt that they had no choice or ways to fight. Subsequently, they maintained a pleading tone to ask for more media coverage and thereby public attention by media organizations such as CCTV; The Paper, a slick state-funded media agency; and NetEase, one of the largest Internet companies providing news coverage, among other services. As one person posted,

I hope this can attract more attention. I beg everyone to distribute more. @China Daily @CCTV Topics in Focus @iFeng @iFeng News @The Paper @Headline News @CCTV News @NetEase News Client @Kankan News @ CCTV News Comment @Sohu News Client @News Weekly @Beijing News. (@User B).

The statement illustrates what Jasper (2018, pp. 96–98) coined as a “nothing-left-to-lose effect,” or that people have been forced into a strategic dead end, with few options left, while these dead ends generate desperate moods, especially for those who try institutionalized political channels but are rebuffed.

For another thing, sadness also entails compassion for the local victims. As Jasper (2018, pp. 140–141) suggested, “our own life experiences allow us to gauge what someone else is going through, as signaled by their utterances. … [E]mpathy leads to sympathy, opening us to the possibility of action on others’ behalf.” Expressions of sadness, including emoticons, easily engendered empathy among Weibo users for the affected area and residents and consequently encouraged participation motivation to speak for local victims. For example, some users posted “Save the people in Quangang [cry] [cry] [cry]” or “Please save our children in Quangang [sick].”

Morality arises from the basic human capacity to feel sympathy for others (Jasper, 2018, p. 140). In practice, two moral experiences are involved in activists’ compassion: one is empathy, i.e., the starting point of forming a sense of solidarity with others. In daily lives, we are more inclined to empathize with those similar to us and whose place we can imagine occupying (Jasper, 2018, p. 140). In this case, although the majority of Weibo users were not all the victims of the disaster, many empathized with the victims based on the love for their compatriots. This establishes the compassion and a sense of solidarity among the public. The other moral experience is sympathy, i.e., having a feeling as a result of another person’s feeling, and the premise of this feeling is based on the judgment that others are experiencing a bad situation. Here, in the face of serious water pollution and air pollution, many actors felt the same feelings as the victims did, which subsequently led to sympathy for those who were experiencing this accident. Given moral empathy and sympathy, many Weibo users expressed their sadness and, more specifically, their compassion by asking for help for the victims, so as to get more public attention and participation in the activism.

Third, apart from emotional expressions toward the incident per se, disgust and anger emotions were furthermore augmented against the government’s inaction and censorship in this event. Regarding the government’s response to the aftermath of the incident, many posts criticized the untimely release—and thereby nontransparency—of information disclosure and the inappropriate measures to avoid public panic. Disgust was exemplified by how many people pointed out that, after the incident, the local government failed to pay sufficient attention and to disclose the pollutant and its potential harmful effects on human health and the environment. The public was disgusted with the government’s lack of action and initiative.

Some negative moral emotions, such as disgust and anger, are often defined as emotional reactions to the moral violations of others (Rozin et al., 2000, p. 575). To be specific, disgust has been seen as an “emotion of social rejection ” (Schnall et al., 2008) because it is often accompanied by the marginalization of people who are considered to violate social norms of behavior or who have negative social value (Hatemi & McDermott, 2012). Yet the government was severely criticized out of a sense of morality by many Weibo users, as it failed to fulfill the fundamental ethical requirements to show enough care for vulnerable groups, and it did not take effective measures to reduce the harm caused by the accident to victims, especially local children.

To avoid causing widespread public panic, the government did not suspend class attendance in primary schools, and many students insisted on wearing masks during class. Since underage children are relatively vulnerable groups in society, many emotional expressions mentioning children as a group indicated dissatisfaction and galvanized online participation. For example, one post read, “Do you [the authorities] still have a conscience? What did children do wrong? Are the children in the countryside not the flowers of our motherland? Are their lives so worthless?” (@User C).

Many posts denounced both the authorities and the Weibo platform by using an accusatory tone. Regarding censorship, many people expressed dissatisfaction with and resentment of how officials suppressed public opinion concerning this incident. For example, one post raised a question: “It has been four days since the incident happened. How long will it be hidden [by the authorities]? How long can it be hidden?” This dissatisfaction and resentment pointed not only to the authorities but also to the Internet company, Weibo. In the public’s eye, both participated in the censorship practice. A post contested this practice by saying, “is it useful to remove our posts? Can you [the authorities and Sina] control the spread of the toxic gas?” (@User D). In practice, the official suppression of online discussion aroused resonance among Weibo users and mobilized their participation.

Emotion Work and Political Participation: Beyond the Incident

Apart from the emotional expressions that revolved around the incident, we also observed performative and manageable emotional expressions, or emotion work (Hochschild, 1979), that were shaped by the institutional context of the Chinese Internet environment, which is subject to censorship. In other words, emotional expressions were strategically deployed and fostered to engender sufficient commitment among activists and to maintain their ongoing participation (Juris, 2008).

In reality, the awareness of Internet censorship among Weibo users fundamentally affects their emotional expressions and thereby determines which types of emotional expressions would be appropriate and could survive on Weibo, or not. Against this backdrop, happiness and surprise were employed to adapt to the specific institutional context through strategic, deliberate packaging and manipulation.

First, many posts converted negative emotional expressions into positive ones, such as happiness, which would promote online participation behaviors. For example, some users expressed their gratitude to the media and individuals who dared to release or publish true information about the incident. One said, “Thanks to the person who tells the truth. #Quangang notified the handling situation of leakage of carbon nine#” (@User E). Another stated, “I wish the authorities stops deceiving themselves, and thank the People’s Daily for its voice. #Carbon 9 leakage in Quangang, Fujian#” (@User F). Reading between the lines, the gratitude rather implies dissatisfaction with and resentment against the official suppression of online discussion and the inadequate information released concerning the incident. Yet Weibo users chose deliberately not to express such criticism, instead expressing their affirmation and appreciation for those who published the facts, in the face of the information control.

Second, many posts consciously turned their dissatisfaction with and distrust of the government into a surprise emotion, using a rhetorical and ironic tone, which denoted their doubt and criticism of the government’s insistence that “air quality has returned to normal” (Quangang District Environmental Protection Bureau, 2018) after the accident. This transformation not only facilitated discussions but also boosted various political participation behaviors, as a reaction. One person asked, “#Carbon 9 leakage in Quangang, Fujian# Why (this incident) cannot appear on the hot search list (in Weibo)??? Can such a significant thing be covered?” (@User G). Another compared the incident to the Gulf of Mexico oil spill in 2010, which “caused up to 10 years’ damage,” challenging the official statement by saying that “the so-called official declaration of air quality and water quality indicators return to normal within one day … now our powerful Quangang’s official agencies are able to solve it [the pollution] in one day? … #Carbon 9 leakage in Quangang, Fujian#” (@User H).

On the surface, the posts expressed shock, disbelief, or unexpected emotions toward either the government’s information release or Weibo’s reaction to the posts about the incident in a questioning way. The underlying meaning entails dissatisfaction, criticism, and especially irony toward the government and the social media company. The adoption of this ironic technique in political participation demonstrated people’s moral judgment. Here, irony mainly focused on two aspects: (a) to query the fact that such a severe environmental accident could not make it to the Weibo hot search list; the query implied the public’s dissatisfaction with the government’s speech control and information censorship; and (b) to question the authenticity of the accident handling results announced by the government, which showed doubts about the openness and transparency of government information. The common ground of both aspects involved the consideration that the government violated some fundamental moral expectations of its people—that is, the pursuit of facts and truth, and especially the sense that after such crisis events related to life and health, the government should have objectively and transparently disclosed the truth. However, the local government blindly suppressed the relevant speech by deleting posts and rather insisted that the environmental indicators had returned to normal despite the fact that the local residents could still detect the pungent smell. This situation was morally offensive. These expressions exemplified the fact that Weibo users maneuvered emotion work that not only was created and survived in the politically repressive online environment but also provoked resonance and subsequent online political participation.

Third, many posts adopted rhetorical ways of expressing negative emotions in a sarcastic, bantering, or mocking way, which cultivated a seemingly “relaxed” and “pleasant” emotional atmosphere. This kind of emotion work transformed negative expressions into humor, which is consistent with the style of expression in Chinese cyberspace and makes it easy to mobilize engagement online (e.g., Yang, 2009, 2015). Some posts satirized the authorities in the genre of “duanzi” or joke, with an entertaining and rhyming tone, which is easy to proliferate on the Internet, while subtly expressing dissatisfaction. One example was the following:

To blow toxic gases away only by wind, to clean to sewage only by scouring, to blind people to accomplish environmental protection, and to talk a good game only to achieve governance. This is what they [the authorities] did in the first time after the incident. (@User I).

Kruschke and Vollmer (2014) showed that moral psychology and humor share a common ground, as people’s moral foundations can be reflected in their sense of humor. According to moral foundation theory, people’s moral foundation has at least the following five aspects: care, fairness, loyalty, authority, and sanctity (Graham et al., 2013; Haidt & Graham, 2007). This catchy doggerel used both humor and sarcasm to satirize the measures taken by the government to deal with the aftermath of the accident. The moral basis behind the post was that the government’s measures to deal with the accident were not satisfactory and the local residents who were suffering were not given enough care.

In addition, some users expressed their dissatisfaction with the lack of attention to this incident by using a joking tone. For example, one post by @Sicong Wang, the billionaire son of China’s richest real estate developer and a Weibo celebrity with over 40 million followers, read as follows:

Hello, you topped the hot search list (in Weibo) even when you were devouring a hot dog. However, our people in Quangang cannot go up to the list due to the heavy suppression, regardless of how much we struggle. Would you lend us a helping hand to let the authorities pay enough attention to us ordinary people? Thank you [Flower]. (@User L).

What was behind this joke was people’s ridicule of the government for not paying enough attention to the accident. It meant that the daily life of an entertainment star could become the focus of netizens’ attention on Weibo, while such a serious environmental pollution accident could not become a hot topic in social media. This was regarded an unfair and unreasonable, and contrary to the moral foundation of fairness. Research shows that the moral foundation of fairness can increase people’s sensitivity to cheating and unfairness (Graham et al., 2013; Haidt & Graham, 2007). This once again relates to the fact that the pollution figures released by the government twice after the accident were different by a factor of 10, which made people believe even more that the government deliberately concealed the truth of the accident, thus questioning the credibility of the government. This type of expression, with emotion work, does not involve excessive political risk and hence can easily survive with possible political participation.

To sum up, our research suggests that the relationship between different emotional expressions and online participation remains rather complicated and hence cannot be grouped together, without regard for the specific event and its context. Our findings suggest that, first, to explicate the relationships among emotions and political behavior, we need to consider emotional reactions to the nature of the event, but also the context and emotion work involved in the event. For one thing, in this case emotional expressions directly and explicitly generated by the event triggered resonance and facilitated participation. For another, given the influence of contextual elements, emotion work will also be strategically adapted. The contextualization of emotion work allows some emotional expressions a wider response than others, leading to different participation behavior.

Second, the study of emotions and (online) activism should not be limited to the investigation of negative emotions, but it rather requires a nuanced, situated analysis of various types of emotion in relation to both mobilization and demobilization in a specific context. As our findings show—and as acknowledged by a few studies (Stürmer & Simon, 2009)—emotions can also inhibit people’s political participation. The mobilization effect of emotional expression on social movements is inseparable from the context it is rooted in. This also confirms our emphasis on the need to contextualize so as to understand emotions in social movements. In different social environments, the expression strategy, applicability, and mobilization effect of emotions may be diverse. Meanwhile, the mobilization effect of emotion is also inseparable from the risk that individuals who deploy emotional expression may face in a certain context. When the risk is considered to be high, the mobilization effect of some emotions that were originally considered to play a key role in the protest—for instance, anger (Jasper, 2014)—may be weakened or even have negative effects (as in this case, disgust). It would be relevant and promising to dissect the complexity of the distinctive influence a specific type of emotion has on various political participation behaviors, as illustrated in our findings.

Third, our findings offer an example from the authoritarian context to enrich the existing understanding of emotions and political behaviors that is largely based on the democratic context. As demonstrated, consideration of emotion work presents specific insights into how emotions undergo appropriation and management in a repressive context, in which people have to strategically maneuver emotional expressions in order to survive censorship. Such appropriation and management have shaped emotional expressions into different roles than those in a democratic context.

Conclusion

This study focused on emotions and morality in online political participation. We used the case example of environmental activism to explore the relationships among different emotions, morality, and various political participation beyond posting and sharing behavior.

First, via statistical analyses of a hand-coded sample of observed emotional expressions in Weibo posts, we revealed how different emotions exerted different effects on participation behaviors, while the same emotion had different effects on different types of participation behaviors.

Then, through the text analysis of Weibo posts, we explained the relationship between emotion and political participation behavior shown by our mixed-method analysis. In this case study of a detrimental environmental incident, many posts directly and explicitly involved dissatisfaction with (disgust) and condemnation of (anger) the authorities’ crisis management, sympathy for the victim, and helplessness due to the suppression of online speech (sadness), as well as anxiety and panic concerning the possible toxic effect on human health (fear). Part of the reason why these emotional expressions could attract attention and encourage participation was due to basic human moral principles and foundations behind them, such as sympathy for the weak, care for people who are suffering, and pursuit of the truth. The occurrence of morally offensive behavior hence promoted the generation and expression of activists’ emotions, which were magnified and strengthened through their spread on Weibo.

On the other hand, in view of China’s repressive Internet policy, social media users engaged with emotion work that transformed negative emotional expression into other types of expression that would have a better chance of surviving and encouraging participation. Understanding the relationship between emotions and participation in online activism thus required us to look beyond emotional expressions and consider emotions and emotion work, both of which shaped but were also shaped by specific sociopolitical context and experience. As argued, different social contexts also affect the “risk” of emotional expression. In a repressive speech environment, the expression of negative emotions against the regime will incur higher political risks, which may demobilize individuals’ participation in social movements. To avoid the foreseeable risk, activists will rather choose to adapt emotion work to strategically express their emotions and attitudes. In a broader sense, both emotion and emotion work cannot be understood through a universal, definitive interpretive framework, and efforts to interpret emotion should recognize the specific feeling rules that contextualize any study of (re)actions, communities, and objects. Therefore, a contextualized understanding of emotions in social movements is of great importance, as it not only affects the emotional expression of activists but also affects the political action participation of social actors.

While divulging a significant aspect of emotions and political participation online in the authoritarian context, our study also has a number of limitations. First, the research on the relationships among public emotion, morality, and political participation behavior is still relatively rough. In the future, researchers can conduct a more detailed study from the perspectives of both the temporal evolution of emotions and the spatial communication structure of emotions, such as the impact of the evolution of activists’ emotions on their participation in or withdrawal from political activism, and how the contagion of individuals’ emotions promotes the participation in certain collective action. Second, consideration of other factors beyond the content of the post helps us to better understand the relevance (or not) of emotions in political behavior in the online environment. Future research might integrate other factors, such as the visibility of posts, to explore the combined effects of emotions and other factors.