“Click First!”: The Effects of Instant Activism Via a Hoax on Social Media

Abstract

To facilitate the immediate effects of social media activism, some activists adopt a deceptive strategy, swaying lay individuals’ perceptions and manipulating their behavior despite ethical considerations. This study identified instant activism, which targets lay individuals’ effortless supportive actions (e.g., clicking) on social media and examined its effects in the context of GMO (genetically modified organisms) labeling issues in the United States. Grounded in the situational theory of problem solving, this study investigated who engages in instant activism and what their behavioral consequences are. Results of an online survey (n = 483) suggested that (a) individuals with a low level of issue knowledge but a high level of issue involvement tend to believe a social media hoax and (b) belief in the hoax leads individuals to engage in active communicative activities that involve problem solving and behavioral changes when mediated by situational motivation. Theoretical and practical implications were discussed.

Keywords

social media activism instant activism hoaxes GMO labeling situational theory of problem solving

Debates on social media activism have continued since social media technology first allowed people to support an issue easily by clicking (Men & Tsai, 2013). Although some scholars hold an optimistic view that the phenomenon will be transformed into meaningful activism and the participants will evolve into an active public (e.g., Kristofferson et al., 2014; Lee & Hsieh, 2013; Morozov, 2009), others criticize these effortless actions. Furthermore, activists have been tempted to abuse the power of the click. Encouraging lay individuals to share, like, or comment on an issue on social media is much easier than finding people who are willing to participate in a protest or donate money to activist groups (Hon, 2015). With respect to the current social media activism, Forbes noted that activists who have “. . . the ability to instantly reach thousands if not millions of people online has opened entirely new possibilities for organizers” (Brickman, 2017). Moreover, these simple actions (i.e., clicking, liking, sharing) may give activists and the issue they advocate for legitimacy (Veil et al., 2012).

To facilitate the immediate effects of social media activism, some activists adopt a deceptive strategy (e.g., Veil et al., 2015) and attempt to sway lay individuals’ perceptions and manipulate their behavior despite ethical considerations. For example, some activists spread hoaxes on Facebook that include sensational images and messages that help attract prompt public attention and their reactions. Although such a deceptive strategy serves only as a one-time resource mobilization, it may be considered manipulation that sways public opinion unethically to achieve their goals. Botan (1997) noted that “. . . the more successful the campaign is at influencing others, and hence the greater its reach or impact, the more significant the ethical questions become” (p. 189), but there has been limited academic attention to the phenomenon, and there are ambiguous perspectives from which to view it.

Accordingly, this study proposes the concept of “instant activism” to explicate the popular, but problematic, phenomenon that attempts to gather vocal power by inciting people to pay prompt attention to an issue and participate in effortless social media activism through clicking. Moreover, a new pseudo-public, referred to as the “instant public,” is discussed as a target of instant activism. To pursue this discussion, the current study adopts the strategy of evaluating the results from non-profits that spread hoaxes regarding GMO (genetically modified organisms) labeling issues as a real-world example of instant activism.

The situational theory of problem solving (STOPS; Kim & Grunig, 2011) provides insights into how people become active publics who engage in active communicative actions in problem solving (CAPS). However, the theory may be limited as an attempt to explain the characteristics of the instant public and their communicative behaviors responding to hoaxes. Specifically, while STOPS assumes that publics evolve from passive communicators to active problem solvers with deliberative assessment on an issue, instant publics can appear in prompt response to extra triggers. Building on the STOPS (Kim & Grunig, 2011), this study examines the relations between exposure to social media hoaxes and lay individuals’ engagement with an issue on social media in the context of GMO labeling issues.

This research begins with the expectation that it will serve as a turning point to alert other scholars in the public relations field that pseudo-activism is a serious social problem subject to abuse without social surveillance and regulations. The study’s goal is to contribute information to advance activism and public segmentation literature further. The study examines current GMO labeling issues by applying an existing theory (i.e., situational theory of problem solving) and then compares the notable differences between current social media activism and traditional activism. Via this process, the goal of the current research is to characterize a new type of public.

Literature Review

Conceptualizing Instant Activism

The STOPS suggests the way people engage in problem-solving behavior (Grunig & Kim, 2017; Kim & Grunig, 2011). When individuals face an uncertain situation that generates feelings of discomfort, they identify the situation as a problem (Kim & Grunig, 2011). The STOPS states that conscious problem recognition triggers individuals’ information processing to look for a way to resolve the uncertainty (Grunig & Kim, 2017; Kim & Grunig, 2011; Krishna, 2017).

When it comes to activism, which refers to collective actions to solve a problematic social issue, cultivating active publics has been regarded as a crucial strategy based on a traditional view of public mobilization. An active public is expected to monitor cross-situational social issues continually and be ready to engage in supportive actions (Grunig & Kim, 2017). What one might consider traditional activism, including marches, protests, sit-ins, donations, and phone calls, requires effort and costly public behavior (Brodock, 2010; Glaisyer, 2010; Hon, 2015). Public engagement in such supportive behaviors was based on individuals’ serious consideration of principles embedded in an issue (Hallahan, 2001a; Seo et al., 2009). Thus, scholars have focused on identifying and segmenting the active public with the expectation that such individuals help mobilize action on an issue (e.g., the aware, aroused, inactive, or non-public segments; Hallahan, 2001b). As a result, previous public mobilization strategies have focused on (a) educating the inactive public so that it recognizes a problem and develops a sense of urgency to motivate and create an active public in response to the problem (Hallahan, 2001a; Kim & Ni, 2013) and (b) building quality relationships with a continually active public as a long-term strategy to generate new supporters and maintain present supporters (Taylor et al., 2001).

In contrast to traditional activism led by active publics, some current activists tend to target the inactive public on social media to accomplish short-term mobilization. According to previous research, inactive publics are individuals who have low levels of knowledge and involvement about an organization’s action. Inactive publics tend not to recognize the consequences of related issues (Hallahan, 1999). Because the success of social media activism is not necessarily evaluated by how well individuals know and sympathize with the issue, activists target the inactive publics’ engagement. For example, as activists, non-profits can promote individuals to engage in simple supportive actions on social media (e.g., liking, sharing, and commenting) with respect to an issue for which they advocate, particularly in uncertain situations. Even if these simple actions do not reflect the actors’ serious consideration of the issue or are not expected to lead to continuous actions, they can be visualized and vocalized as massive public support on social media (Meikle, 2014; Zuckerman, 2014).

In this process, tempting cues (e.g., hoaxes) are often adopted to grab lay individuals’ attention for an issue and to promote their participation in simple online activism. Previous research has indicated that the non-public can be activated to engage in certain issues through external stimuli (Kim et al., 2012). Krishna (2017) demonstrated empirically that some people scored very high in their problem-specific motivation and activity levels with respect to an issue as a result of significant, and even long-term, acquisition of inaccurate knowledge about that issue.

This study suggests terms to describe the phenomenon and its resulting audience. This study defines a strategy that motivates individuals to forego deliberative consideration and engage in an issue immediately as “instant activism.” The study also proposes the concept of “instant public,” which represents the target individuals of instant activism. The instant public can be defined as a reaction to a type of public inflammatory data, findings, events, or reporting, whether true or constructed falsely, which motivates them to be aware of a problem immediately, and participate actively in solving it. However, the instant public’s seemingly active participation is limited to low-cost communicative actions in advocating an issue. This new type of public can be characterized by the discrepancy between the extent of its behavioral activity in the social media sphere and the absence of principles embedded in its members’ daily lives. The instant public serves to segment further other elements of the public described above that previous studies have discussed (Hallahan, 1999, 2001b)

Hoax Spreading: How Instant Activism Works in Social Media

Recent research has indicated that non-profits use social media to gather supporters who contribute in some way to the organization (Curtis et al., 2010; Lovejoy & Saxton, 2012). Spreading hoaxes is one among the various social media strategies of certain advocacy groups (Veil et al., 2012, 2015). A hoax refers to a deceptive message that alludes to a conspiracy theory, which is associated with a group or an individual that is suspected of taking advantage of others (e.g., van der Linden, 2015; Veil et al., 2012, 2015). While some activists disseminate hoaxes intentionally to garner public attention and elicit public support, others do so accidentally. Some activists spread hoaxes without being aware that the information is inaccurate. Circulating hoaxes accidentally occurs often because not all activists are experts who have knowledge about an issue. If they are members of the lay public, then they may spread scientifically inaccurate data unwittingly because it supports their position on an issue and, thus, is consistent with their understanding of the problem (Kata, 2010). However, regardless of whether activists create or disseminate a hoax, it is undeniable that doing so is intended to incite the public and manipulate their behaviors through this inaccurate messaging (Veil et al., 2012).

The spreading of a hoax, or partial truth, even for the purpose of promoting the public good, still constitutes a deceptive practice. The hoax strategy, however, can be effective in maximizing public attention and giving the appearance that the issue and the advocacy group have wide public support (van der Linden, 2015). Furthermore, exposure to hoaxes may manipulate the inactive public and cause them to employ heuristic decision-making to complete cursory processing of an issue that oversimplifies it and its related problems (van der Linden, 2013). Hence, these hoaxes may motivate them to engage in related issues promptly, regardless of the truth of the information. Based on theoretical discussions, this study proposes two hypotheses in regard to who believes a social media hoax and thus engages in instant activism:

Hypothesis 1 (H1). Individuals with a lower level of issue involvement are more likely to believe a hoax related to the issue.

Hypothesis 2 (H2). Individuals with a lower level of issue knowledge are more likely to believe a hoax relate to the issue.

Situational Motivation in Problem Solving in Response to Instant Activism

Although the results of recognizing a problem are demonstrated in a similar form (i.e., supportive actions), this study investigates different segments of the public compared with the original STOPS study. According to STOPS, there is an assumption that each problem-solving communicator is “. . . highly motivated and active in thinking and acting” about their problems (Kim & Grunig, 2011, p. 145), as an extension of Grunig’s (1997) public research, which regards individuals as rational and active. The current study, in contrast, proposes that the instant public lacks knowledge of, and involvement in, the issue. Therefore, the instant public may not act according to the STOPS’ description of a problem-solving communicator. Based upon this distinction, this study compares the differences between the instant public and the active public by examining the way instant activism works within the process of STOPS.

STOPS suggests a route that individuals engage in problem-solving behaviors mediated by situational motivation. Kim and Grunig (2011) described situational motivation as the driving force in problem solving. “A person stops to think about, is curious about, or wants more understanding of a problem” (p. 16), in which individuals assess their situation with respect to the problem deliberatively. Thus, when individuals recognize and consider seriously that an existing issue is a problem, they (a) develop a high regard for their involvement with the problem, (b) ignore constraints in solving the problem, and (c) activate a high level of situational motivation in solving the problem (Kim & Grunig, 2011). The theory’s original approach tends to reinforce the importance of the public’s autonomous information process that activates each element.

This study establishes that extraneous triggering can alter an individual’s assessment of a problem (Aldoory & Grunig, 2012; Chen et al., 2016; Kim et al., 2012). For example, some individuals become engaged quickly as a result of exposure to media coverage, particularly if the event/problem/coverage involves scandals or national problems (Aldoory & Van Dyke, 2006; Grunig, 1997). Furthermore, when “. . . a controversial triggering issue occurs” (Grunig & Kim, 2017), party and political identity, like other forms of identity, can produce and/or exacerbate differences in the extent of the public’s activity (Chen et al., 2016; Kim et al., 2012).

In this regard, the current study assumes that a hoax can lead individuals to immediately become motivated to engage in problem-solving actions without further cognitive assessment. As a form of conspiracy theory, which suspects people of plotting secretly to accomplish some unjust goal, hoaxes are associated generally with well-known individuals or organizations (van der Linden, 2015). Essentially people process an issue with the hoax speedily by activating a myth that they were exposed to previously. Thus, the following hypothesis is proposed:

Hypothesis 3 (H3). Belief in a hoax is positively related to situational motivation to solve the problem implied in the hoax.

CAPS

As discussed in the earlier section, instant activism targets lay individuals of the inactive public and encourages them to engage in simple actions that are visible indicators of support and do not require the lay public to embed principles related to the issue. Earl and Kimport (2011) argued that the digital mobilization strategy gives participants more cost advantages, because digital activist techniques usually require minimal time and effort. Individuals can participate in actions without experiencing the limitations of time and place as well as the dangers of social stigma that can plague protesters. In this respect, when individuals are motivated to instantly process an issue because of exposure to instant activism, they can participate in social media action that supports their decision without considering their position carefully or engaging in high-effort activism. Previous research has suggested that people enjoy participating in these activities, which increase their perceived efficacy, without the effort required for deep consideration (Breuer & Groshek, 2014). Thus, instant activism can be a “quick-and-dirty” strategy in online mobilization that avoids cultivating and evolving the non-active into the active public.

Mobilizing the instant public (i.e., instant activism) may have two primary benefits. First, it accommodates and makes space for a new public element willing to engage in communication regarding an issue. In this way, as campaign leaders, activists can mobilize supportive voices rapidly to demonstrate their activities’ legitimacy. The outcomes of instant activism may provide significant legitimacy for the issue, as well as for the organization’s presence. Second, the instant public’s communicative actions can position the issue on the more salient social stage, transforming what might be a low-level advocacy issue into a high-level social problem (i.e., hot issues; Aldoory & Grunig, 2012) that requests immediate attention and actions on the part of society overall. Once an issue becomes a hot issue, other general elements of the population not only draw attention to it, as triggered by media coverage, but become willing to engage actively in processing the issue (Chen et al., 2016). These two effects of instant activism can interact to increase public resources to address and potentially solve the problem, thus achieving the activists’ goal overall.

However, previous research has indicated that such a vocal public that is motivated to promote and promulgate an issue is not necessarily well informed; nor do the individuals have objective perspectives (Grunig & Kim, 2017). For example, previous studies have suggested that some individuals tend to be motivated highly in their communicative actions because they hold extreme views and lack knowledge related to the problem (Krishna, 2017). This vocal power is not expected to exist in perpetuity. A unit of instant activism (as a one-time strategy) is a targeted issue (inflammatory data, findings, events, or reporting) within a larger problem, unlike traditional activism, in which the objective of leaders is to mobilize and cultivate the public to engage in social movements consistently (e.g., Kristofferson et al., 2014). Hence, while maximizing vocal power without cultivating sincere principles might be a useful tactic in the short term, it generates fleeting, hollow support, the ethics of which can be criticized.

This study uses STOPS to address the process of instant activism and to determine the instant public’s behavioral characteristics. Communication can be regarded as an instrumental tool to solve problems and increase communicators’ perceptions and motivations in relation to a certain issue (Kim et al., 2012). When individuals are motivated to engage in a problem, they participate in “purposive coping behavior” to resolve it (Grunig & Kim, 2017, p. 13). Communicative behaviors include proactive actions (active information behaviors) and reactive actions (passive information behaviors: Kim & Grunig, 2011). In the proactive coping process, individuals gather/seek information actively, reject a source of information actively as a result of developing an information preference (forefending), and forward information without being prompted or asked (forwarding: Kim & Grunig, 2011). Proactive communicative actions can be described as not only active but also motivated or self-propelled behaviors (Moon et al., 2016). On the contrary, in reactive information processing, individuals receive information passively (attend), delay active rejection of information because of a tendency to accept (permit), and share information about the issue only when asked (share: Kim & Grunig, 2011).

The theory suggests that active individuals maintain a high level of behaviors related to all information, while passive individuals maintain a high level of behaviors related only to reactive information. Scholars have addressed the dynamic role of the active public in issue activation. Members of an active public not only turn to different information sources but also initiate informal conversations within their own social networks (Kim et al., 2010), and thereby may become influential opinion leaders in these networks who serve to raise others’ awareness of a problem. Eventually, the active public can motivate other people to engage in solving the problematic situation (Kim et al., 2012).

Public evolution has been regarded as a gradual, progressive process. Active individuals (the active public) evolve from passive individuals (the aware/latent public) when they increase their communicative behavior from a passive to active level. Kim and Grunig (2011) used the term evolving to describe the process by which passive individuals become active. Through this process of evolution, “. . . as one becomes a more active problem solver, one’s information selectivity evolves from unsystematic to systematic, from general to specific and from related to relevant” (p. 127). In a similar vein, other research on the public has stated that a public evolves in the process of communication through such actions as discussion (Hallahan, 2001a).

Instant activism seeks to generate vocal support for an issue on the part of lay individuals who are not seriously aware of, or informed about, the issue otherwise. For example, an information forwarder is eager to disseminate his or her problem perception, and the preferred way to solve a problem is through association with other communicators. Thus, at a later stage, the purpose of information transmission is to reproduce a similar problem perception and promote the solution preferred (Kim & Grunig, 2011). Information-forwarding behaviors include forms of visual support, such as sharing, commenting, and liking posts on social media. On the contrary, information-sharing behaviors are not a form of visible support. Moreover, an external stimulus triggers the instant public to engage in the problem-solving process within a short period and without deliberation. In this case, they seem to choose to process information either actively or passively without careful regard. Thus, instant activism targets the instant public’s active, but visible communication, while at the same time, the public bypasses the cognitive deliberation step. Therefore, this study finds that active communicative actions are possible despite the absence of deliberation.

Examining the strategy of spreading a hoax as an example of instant activism, an exploration of was made of the immediate behavioral changes that take place in the formation of the instant public. In this case, non-profits spread hoaxes about GMO labeling issues to generate individuals’ active communicative behaviors on social media, thereby generating an instant public. The following hypotheses are proposed (Figure 1):

Hypothesis 4 (H4). Belief in a hoax is positively related to active CAPS.

Hypothesis 5 (H5). Situational motivation is positively related to active CAPS.

Hypothesis 6 (H6). Situational motivation positively mediates the relationship between belief in a hoax and active CAPS.

Figure 1.

Theoretical model and paths of this study.

Instant Publics’ Embedded Issue Commitments

The effects of online activism on cultivating a chronic active public are still controversial (Skoric, 2012). Previous research has demonstrated the practical power of situational motivation, which leads individuals “to do” something (e.g., organ donation; Kim et al., 2011) and maintain attention to an issue (e.g., a problem chain-recognition effect; Kim et al., 2011) that extends beyond participating in activism just once. On the contrary, as Morozov (2009) noted, social media activism is believed to have no effect on real-life political outcomes, but only increases users’ sense of personal satisfaction. With respect to the GMO labeling issue, according to a previous survey, 90% support GMO labeling, although only 10% responded that they will consume non-GMOs (Irani et al., 2001).

Accordingly, this study assumes that, in the current online communication environment, communicative action should be considered separate from actual behavior with an embedded commitment to the issue they support online. The instant public can be generated to achieve a disposable mobilization without chronic awareness of related issues or a deliberative process of evolving as a public. Although such instant activism could serve to promote superficial principles about the issue, it would be difficult to cultivate embedded principles in the instant public that has been transformed from an inactive public in a short time. Thus, the following research question is proposed:

Research Question 1 (RQ1). To what extent do hoax beliefs and situational motivation have an impact on individuals’ behavioral commitment?

Methods

Research Design and Procedures

An online experimental survey was administered via Qualtrics, and participants were recruited through an online panel company, Amazon Mechanical Turk (MTurk), with a cash incentive (US$0.80). Exploring a social media phenomenon, this study tried to reach people who are familiar with the online and social media environments. Thus, the survey participants were recruited via MTurk. Previous research demonstrated that MTurk provides quality samples for survey researchers (Kees et al., 2017) because it allows the selection of participants randomly, not limited to demographic and psychographic variables (Ross et al., 2010). Upon agreement to participate in the online survey, participants were asked a screening question: “Do you use Facebook at least once a week?” Those who answered “yes” could participate in the survey.

After participants indicated their level of perceived knowledge and involvement on GMO labeling issues, a Facebook message was shown with a brief explanation (i.e., this message has been posted on Facebook by JustLabelIt, which is a non-profit organization supporting “direct” GMO labeling). After viewing the Facebook message, participants were asked to complete the questionnaire based on their perceptions.

Stimulus Development

Conducting the experimental survey, this study used a Facebook message with a hoax to estimate how instant activism affects the promotion of public engagement on social media in the context of the issue of GMO labeling. Unlike general GMO issues (i.e., whether they are safe, or whether genetic modification technology should be allowed in food products), only a small portion of the general population has specific knowledge about current GMO labeling issues, including their pros and cons. In response to current legislation, which allows indirect labeling (e.g., ARS numbers, QR codes), non-profit organizations use social media to actively publicize GMO labeling issues (Senapath, 2017). The message revised in the current context was based on an existing Facebook campaign message posted by JustLabelIt, which is a non-profit that advocates to change the new federal law which allows indirect GMO labels. The message includes a hoax (i.e., “People are intentionally misled with deceptive GMO labeling, like a QR code,” “Someone is conspiring to conceal the identity of GMOs.”), images, and descriptions about the flaw in the federal GMO labeling law.

This study regards a hoax as a deceptive message that alludes to a conspiracy theory that is associated with a group or an individual that is suspected of taking advantage of others (e.g., van der Linden, 2015; Veil et al., 2015). To operationalize the definition, this study adopted a message that discloses a conspiracy that “People are intentionally misled with deceptive GMO labeling, like a QR code, . . .” and “someone is conspiring to conceal the identity of GMOs.” Further information was provided about the way the new GMO labeling law deceives people.

Sample

A total of 605 Facebook users, who were US residents, participated in this survey. Responses with incomplete items and/or with wrong answers for attention-checking questions were removed from the final dataset. A total of 483 responses were used for the final analyses. The average age of the participants was 37.29 years, ranging from 18 to 88 (standard deviation [SD] = 11.64). Of the participants, 51.8% were females (n = 250), and 48% were males (n = 232). Among them, Whites (non-Hispanic) represented 73.5%, and African Americans were 11.6%. Most participants (45.6%) had an annual household income of US$40,000–US$79,999 (less than US$−19,999 [12.8%], US$20,000 to US$29,999 [9.5%], US$30,000 to US$39,999 [10.8%], US$80,000–US$89,999 [4.6%], US$90,000–US$99,999 [4.3%], US$100,000–US$149,999 [9.7%], and US$150,000 or more [2.7%]). A total of 83% of the participants had college experiences (Table 1).

Table 1.

Sample Characteristics (N = 483).

Demographic characteristics	Frequency	Percentage
Gender
Male	232	48
Female	250	51.8
Prefer not to specify	1	.2
Age
18-25	51	10.6
26-30	105	21.7
31-40	184	38.1
41-50	71	14.7
50+	72	14.9
Ethnicity
White (non-Hispanic)	355	73.5
Hispanic American	27	5.6
African American	56	11.6
Native American/Asian American/Pacific Islander	41	8.5
Two or more races	4	.8
Education
Some high school or less	3	.6
High school graduate or equivalent	50	10.4
Some college but no degree	106	21.9
Associate degree in college (2 years)	55	11.4
Bachelor’s degree in college (4 years)	192	39.8
Master’s degree	63	13.0
Doctoral degree	7	1.4
Professional degree (JD, MD)	7	1.4
Household income
Less than US$10,000	22	4.6
US$10,000 to US$19,999	40	8.3
US$20,000 to US$29,999	46	9.5
US$30,000 to US$39,999	52	10.8
US$40,000 to US$49,999	62	12.8
US$50,000 to US$59,999	66	13.7
US$60,000 to US$69,999	53	11.0
US$70,000 to US$79,999	39	8.1
US$80,000 to US$89,999	22	4.6
US$90,000 to US$99,999	21	4.3
US$100,000 to US$149,999	47	9.7
US$150,000 or more	13	2.7

Measures

All the measurement items of main variables were measured with a 7-point bipolar or Likert-type Scale (1 = strongly disagree to 7 = strongly agree).

Issue Involvement

This study measured individuals’ involvement in GMO labeling issues with Zaichkowsky’s (1994) Personal Involvement Inventory (PII) scale. This scale focuses on measuring personal relevance that leads individuals to be affected by and motivated to respond to related messages (Zaichkowsky, 1994). Of the PII scale, this study adapted six adjective bipolar items: “significant–insignificant,” “does matter to me–does not matter to me,” “important–unimportant,” “of much concern–of no concern,” “serious–not serious,” “relevant–irrelevant.” (Cronbach’s α = .98, M = 3.95, SD = 1.86)

Issue Knowledge

This study measured GMO labeling issue knowledge by asking how participants know about the issue. In addition to the subject knowledge-level scale developed by Flynn and Goldsmith (1999), this study added items to measure how participants actually know specific details of the issue, such as “I can explain what the new GMO labeling law is,” “I have heard about the arguments around the new GMO labeling law,” “I know that the federal government has adopted the indirect ways of GMO labeling, such as QR codes or ARS,” “I know the difference between the direct ways and the indirect ways for GMO ingredients labeling,” “I know how the new federal law is different from a Vermont law on GMO labeling” (Cronbach’s α = .97, M = 2.72, SD = 1.49)

Hoax Belief

To measure how individuals believe in the hoax presented at the stimulus, this study created two items that described the hoax. Participants were asked to indicate their level of agreement with the following items: “There is a group of people behind GMO labeling issues, who are trying to purposely mislead the public,” “The GMO labeling is not telling the public the truth” (Cronbach’s α = .85, M = 4.92, SD = 1.40).

Situational Motivation and Active Communicative Actions

All the variables used to represent the situational theory of problem solving were adopted from previous studies (Kim & Grunig, 2011; Krishna, 2017). Each item was revised for the GMO labeling issue context for this study and measured by asking participants their degree of agreement with the specific items.

Situational motivation was measured with eight items, including “I am curious about this problem,” “I often think about this problem,” “I want to better understand this problem,” “I want to make this problem a priority these days,” “I want to work hard to develop a better understanding to solve this problem,” “I consider this problem a very important issue today,” “I am determined to fix this problem as soon as possible,” and “I am willing to expend any effort to solve this problem” (Cronbach’s α = .96, M = 3.90, SD = 1.55).

Active CAPS was measured with three sub-categories: information forefending, information forwarding, and information seeking.

Information forefending was measured via six items: “I have a selection of trusted sources that I check for updates on this problem,” “Others respect my perspective on this problem because it is simple and clear,” “Some publicized statements about this problem are worthless,” “I have invested enough time and energy to understand this problem,” “I know where to go when I need updated information regarding this problem,” “I can easily judge the value of information about this problem/issue” (Cronbach’s α = .87, M = 3.70, SD = 1.18).

Information forwarding was measured using eight items: “I want to post my opinion of and experience with this problem on the Internet,” “I am willing to talk about my opinions on this problem with my friends and coworkers,” “I will make sure that my friends know about this problem,” “I bring this problem to the attention of people I know,” “I am willing to engage in heated conversations about this problem,” “I want to share my knowledge and perspective regarding this problem,” “If possible, I take time to explain this problem to others,” and “I will look for chances to share my knowledge and thoughts about this problem” (Cronbach’s α = .96, M = 3.73, SD = 1.59).

Information seeking was measured with eight items: “I will search for information about this problem on the Internet,” “I actively search for information about this topic,” “I will subscribe to news services that discuss this problem/issue (via print or RSS feeds),” “I want to have a collection of news channels that I regularly check for new information,” “I will regularly visit Web sites (e.g., USDA) relevant to the problem,” “I will regularly check to see if there is any new information about this problem on the Internet,” “Please select ‘Somewhat disagree’. This is an attention-checking item,” “I will search online resources or physical bookstores to find useful information about this problem,” and “I will spend a lot of time to learn about this problem” (Cronbach’s α = .96, M = 3.67, SD = 1.61).

Behavioral Commitment

Behavioral commitment was measured by asking the participants’ intention to adopt specific tactics to check GMO ingredients in their everyday life, with a 7-point scale (1 = definitely not to 7 = definitely yes). Each item includes a behavior, which requires high effort and high cost, to check food labeling different from cognitive intentions. The specific items were, “I will never purchase foods, which do not clearly indicate information about their GMO ingredients,” “I will never consume any foods that I cannot make sure what the food items contain,” “I will purchase food items indicate directly their ingredients over items with no information or indirect indications (e.g., QR codes, ARS numbers) although they often cost more,” “I will not purchase food items that hinder me to figure out whether they contain GMOs for myself in the future,” “I will not purchase food items that hinder me to figure out whether they contain GMOs for my (future) family,” “I will seek products that are specifically labeled GMO ingredients,” and “I will recognize fruit and vegetable label numbers” (Cronbach’s α = .93, M = 3.80, SD = 1.51).

Correlations among the main variables are provided in Table 2.

Table 2.

Descriptive Statistics and Correlations (N = 988; range = 1–7).

Variables	Min	Max	M (SD)	Correlations
Variables	Min	Max	M (SD)	1	2	3	4	5	6	7	8
1. Issue involvement	1	7	3.95 (1.86)	1
2. Issue knowledge	1	6.78	2.72 (1.49)	.35**	1
3. Hoax belief	1	7	4.92 (1.40)	.38**	.03	1
4. Situational motivation	1	7	3.90 (1.55)	.64**	.40**	.47**	1
5. Information forfending	1	6.75	3.70 (1.18)	.30**	.64**	.06	.40**	1
6. Information forwarding	1	7	3.73 (1.59)	.54**	.46**	.35**	.82**	.52**	1
7. Information seeking	1	7	3.67 (1.61)	.52**	.46**	.31**	.84**	.50**	.84**	1
8. Behavioral commitment	1	7	3.80 (1.51)	.56**	.39**	.42**	.79**	.39**	.72**	.72**	1

p < .01.

Control Variables

Controlling for variables reduces the confounding effect of irrelevant variables that are not intended to be studied (Baron & Kenny, 1986). In addition to demographics, this study adopted social media active use and attitudes toward general JustLabelIt and general politicians. All control variables were measured by a 7-point scale.

Analysis

This study employed a two-step Structural Equation Modeling (SEM) with the AMOS 24.0 program to analyze the collected data. This study tested the second-order measurement model to measure the active CAPS with three sub-dimensions (i.e., information forefending, information forwarding, and information seeking), following the prior theoretical conceptualizations of the constructs (i.e., Kim & Grunig, 2011). Control variables (i.e., demographics, previous attitude toward JustLabelIt and general politicians) were added, and then the final SEM model was tested.

Results

Confirmatory Factor Analysis: Measurement Model Test

Confirmatory factor analysis (CFA) confirmed the conceptual structures of the main variables (i.e., issue knowledge, issue involvement, hoax belief, situational motivation, and active CAPS [information forefending, information forwarding, and information seeking]). In accordance with the previous literature, this formed a second-order construct with their respective underlying first-order factors. All indicators of the CFA model showed larger than .05 loading. The model demonstrated a good model fit: comparative fit index (CFI) = .92, Tucker–Lewis index (TLI) = .92, normed fit index (NFI) = .88, incremental fit index (IFI) = .92, root mean square error of approximation (RMSEA) = .060 (90% confidence interval [CI] = [.057, .062]), χ² = 3,648.26, degrees of freedom (df) = 1,342, χ²/df = 2.72, n = 483. Hu and Bentler (1999) recommended using combined criteria of at least two acceptable levels of a model fit index (i.e., CFI ⩾ .95, IFI ⩾ .90, NFI ⩾ .90, TLI ⩾ .90, RMSEA ⩽ .06) to evaluate the SEM model fit. Detailed results of CFA are provided in Table 3.

Table 3.

Results of Confirmatory Factor Analysis.

Variables	Scale items	Loadings
Issue involvement (α = .98)	7 = significant to 1 = insignificant	.94***
	7 = does matter to me to 1 = does not matter to me	.89***
	7 = important to 1 = unimportant	.96***
	7 = of much concern to 1 = of no concern	.95***
	7 = serious to 1 = not serious	.93***
	7 = relevant to 1 = irrelevant	.93***
Issue knowledge (α = .97)	I can explain what the new GMO labeling law is	.89***
	I have heard about the arguments around the new GMO labeling law	.87***
	I know that the federal government has adopted the indirect ways of GMO labeling, such as QR codes or ARS	.88***
	I know the difference between the direct ways and the indirect ways for GMO ingredients labeling	.90***
	I know how the new federal law is different from a Vermont law on GMO labeling	.93***
	I have heard about the arguments around the new GMO labeling law	.84***
	I know that the federal government has adopted the indirect ways of GMO labeling, such as QR codes or ARS	.81***
	I know the difference between the direct ways and the indirect ways for GMO ingredients labeling	.87***
	I know how the new federal law is different from a Vermont law on GMO labeling	.80***
Hoax belief (α = .85)	There is a group of people behind GMO labeling issues, who are trying to purposely mislead the public	.86***
Hoax belief (α = .85)	The GMO labeling is not telling the public the truth	.85***
Situational motivation (α = .96)	I am curious about this problem	.77***
	I often think about this problem	.80***
	I want to better understand this problem	.78***
	I want to make this problem a priority these days	.92***
	I want to work hard to develop a better understanding to solve this problem	.89***
	I consider this problem a very important issue today	.87***
	I am determined to fix this problem as soon as possible	.91***
	I am willing to expend any effort to solve this problem	.89***
Information forefending (α = .87)	I have a selection of trusted sources that I check for updates on this problem	.72***
	Others respect my perspective on this problem because it is simple and clear	.75***
	Some publicized statements about this problem are worthless	.51***
	I have invested enough time and energy to understand this problem	.77***
	I know where to go when I need updated information regarding this problem	.81***
	I can easily judge the value of information about this problem/issue	.76***
Information forwarding (α = .96)	I want to post my opinion of and experience with this problem on the Internet	.78***
	I am willing to talk about my opinions on this problem with my friends and coworkers	.79***
	I will make sure that my friends know about this problem	.86***
	I bring this problem to the attention of people I know	.87***
	I am willing to engage in heated conversations about this problem	.77***
	I want to share my knowledge and perspective regarding this problem	.92***
	If possible, I take time to explain this problem to others	.91***
	I will look for chances to share my knowledge and thoughts about this problem	.93***
Information seeking (α = .96)	I will search for information about this problem on the Internet	.83***
	I actively search for information about this topic	.85***
	I will subscribe to news services that discuss this problem/issue (via print or RSS feeds)	.84***
	I want to have a collection of news channels that I regularly check for new information	.82***
	I will regularly visit Web sites (e.g., USDA) relevant to the problem	.90***
	I will regularly check to see if there is any new information about this problem on the Internet	.91***
	I will search online resources or physical bookstores to find useful information about this problem	.88***
	I will spend a lot of time to learn about this problem	.91***
Behavioral commitment (α = .93)	I will never purchase foods, which do not clearly indicate information about their GMO ingredients	.91***
	I will never consume any foods that I cannot make sure what the food items contain	.90***
	I will purchase food items indicate directly their ingredients over items with no information or indirect indications (e.g., QR codes, ARS numbers) although they often cost more	.72***
	I will not purchase food items that hinder me to figure out whether they contain GMOs for myself in the future	.92***
	I will not purchase food items that hinder me to figure out whether they contain GMOs for my (future) family	.90***
	I will seek products that are specifically labeled GMO ingredients	.60***
	I will recognize fruit and vegetable label numbers	.73***

GMO: genetically modified organisms; CFI: comparative fit index; TLI: Tucker–Lewis index; NFI: nonnormed fit index; IFI: incremental fit index; RMSEA; root mean square error of approximation; CI: confidence interval; df: degrees of freedom.

CFI = .92, TLI = .92, NFI = .88, IFI = .92, RMSEA = .060 (90% CI = [.057, .062]), χ² = 3,648.26, df = 1,342, χ²/df = 2.72, n = 483, α = Cronbach’s α.

***p < .001.

Structural Model Results and Test of Hypotheses

SEM was performed to test the proposed hypotheses. In addition to the main variables tested in CFA, control variables (i.e., demographics, previous attitude toward JustLabelIt, and general politicians) were included in the final structure equation model. The hypothesized structural model also achieved a good fit with the data: CFI = .90, TLI = .89, NFI = .90, IFI = .90, RMSEA = .061 (90% CI = [.059, .063]), χ² = 4,789.0, df = 1,729, χ²/df = 2.77, n = 483. The results are described in Figure 2.

Figure 2.

The structural model with standardized path coefficients.

In H1, a negative relationship was expected between issue knowledge and hoax belief. The results showed that individuals’ level of issue knowledge on GMO labeling issues negatively predict how they believe a hoax related to the issue (β = −.11, p < .05). Therefore, H1 was supported. Similarly, H2 claimed that an individuals’ level of issue involvement was negatively associated with hoax belief. However, the results suggested a positive relationship between issue involvement and hoax belief (β = .51, p < .001). Thus, H2 was rejected.

H3 predicted that hoax belief was positively related to situational motivation to solve the problem. The results showed the higher hoax belief on GMO labeling issues that individuals have, the higher situational motivation to solve the problem they have (β = .49, p < .001). Therefore, H3 was supported. H4 was about a positive relationship between hoax belief and active CAPS. According to the result, individuals’ level of hoax belief on the GMO labeling negatively predict their willingness to engage active CAPS about the issue (β = −.10, p < .01). Therefore, H4 was rejected.

For H5, a positive relationship was expected between situational motivation and active CAPS in the context of GMO labeling issues. The results suggested that situational motivation in solving GMO labeling issues was significantly associated positively with the active CAPS (β = .96, p < .001). Therefore, H5 was supported.

H6 predicted a mediation role for situational motivation on the relationship between hoax belief and active CAPS. The results showed positive associations between hoax belief and situational motivation (i.e., H3), and situational motivation and active CAPS (i.e., H4) (β = .47, p < .001). Thus, H6 was supported.

Finally, RQ1 explored how hoax and situational motivation predict individuals’ behavioral commitment to GMO labeling issues. First, the results showed that hoax belief on GMO labeling is positively associated with individuals’ behavioral commitment (β = .08*). The results also suggested a positive relationship between situational motivation in solving GMO labeling issues and behavioral commitment (β = .78, p < .001). In addition, situational motivation had a statistically significant mediating role in the relationship between hoax belief and behavioral commitment (β = .38, p < .001). Therefore, the results showed direct and indirect paths that hoax belief predicts behavioral commitment.

Discussion

Building on previous literature on the public’s communicative behaviors in problem solving (i.e., Grunig & Kim, 2017; Kim & Grunig, 2011), this study investigated an emerging pseudo-activism phenomenon on social media. The study proposed the concept of instant activism, in which some activists target inactive publics to engage immediately in effortless supportive actions on social media. The targeted individuals in instant activism are conceptualized as members of the instant public, who are incited by sensational cues and participate in social media activism without serious consideration. To test these theoretical arguments empirically, this study conducted an online experimental survey in the context of GMO labeling activism on Facebook. The effects of non-profits’ strategy of spreading hoaxes were tested as an instant activism tactic.

Findings and Theoretical Implications of This Study

The study suggests that the instant activism engendered by a hoax strategy played an exceptional role that shortened the individuals’ process in becoming motivated and engaging in problem-solving actions on social media. However, the social media hoax has limited effects in leading people to engage in social media supportive actions, which are intended by activists adopting instant activism.

This study also investigated who believes in a social media hoax, and thus who gets engaged in instant activism in suggesting the characteristics of instant publics. The finding indicated that when people have a higher level of issue involvement, they are less likely to believe a social media hoax related to the issue. The result showed that people who identify a higher involvement on GMO labeling tend not to accept a social media hoax about the issue. In addition, this study found a significant relationship between low levels of issue knowledge and hoax belief. When people have a lower level of knowledge on GMO labeling, they are more likely to believe a social media hoax that GMO labeling has involved a conspiracy. Our findings do not fully support the theoretical assumption that individuals from inactive publics who have low level of issue involvement and knowledge might be swayed by a hoax on social media. Rather, the results of this study showed that aroused publics with a high level of involvement (Hallahan, 2001b) could be more easily affected by a social media hoax than inactive publics. Hallahan (2001b) conceptualized aroused publics who have low levels of knowledge but have a sense of potential issues. The level of involvement among aroused publics can be strengthened and activated by external stimuli including issue creation efforts by activists (Hallahan, 2001b). This study’s findings may extend the previous theoretical approach in suggesting that the issue involvement of individuals without knowledge can lead them to believe a hoax on social media.

Exploring the effects of instant activism, this study tested how a social media hoax promotes people to engage in problem-solving behaviors. First, the finding showed people with a belief in a social media hoax designed to promote a social issue might get motivated to solve the problem. The results are consistent with a line of previous studies that indicate external triggering may prompt individuals to engage in a problem-solving process (e.g., Aldoory & Grunig, 2012; Chen et al., 2016; Kim et al., 2012).

However, the results of this study showed limited effects of social media hoax in causing people to engage in actual behaviors. Our findings indicate that when people believe a social media hoax, they are less likely to engage in active CAPS. As discussed in the “Literature Review” section, the active CAPS includes visual supportive behaviors, such as sharing, commenting, and liking posts on social media (Alhabash & McAlister, 2015). Also, the hoax-spreading strategy targets people who are willing to engage in visible supports, which might be regarded as massive public supports for the issue they advocate. However, as the results showed, the hoax belief was not positively related to the visible supports on social media, and this may reflect the individual’s intention to manage their impression on social media. By engaging in those visible supportive actions, individuals may expose their belief in a hoax to their networked friends on social media. Individuals tend to disclose information about themselves with a sense of how they are presented to others (Goffman, 1959). According to previous research, people consider the consequences of their posts or comments before publishing on social media, and thus they engage in internal social media communication strategically after ensuring the contents are relevant and appropriate (Madsen & Verhoeven, 2016). Hence, people might avoid linking with hoax-related content on social media, which potentially describes them as irrational.

On the contrary, the findings of this study showed a significant association between levels of belief in a hoax and behavioral commitment on the related issue. When people believe a social media hoax about GMO labeling issue more completely, they are more likely to engage in actual behaviors checking GMO labeling in their real-world situations. In this regard, the findings supported a direct effect of hoax-spreading strategy on leading people to change their behavior, although the strategy has no direct effect on promoting social media activism.

Individuals’ situational motivation showed significant mediating effects on the relationships between hoax belief and active CAPS, and between hoax belief and behavioral commitment. The findings suggested people may have the situational motivation to solve a problem depending on their belief in a social media hoax, and the motivation leads people to engage in both active supportive actions on social media and to change actions in their everyday life. Those findings are in accordance with the role of situational motivation as a critical driver to engage in problem-solving behaviors that previous research addressed based on the STOPS (Kim & Grunig, 2011). However, while the STOPS claims that the situational motivation activates as a result of individuals’ deliberative assessment on the related issue, the findings of this study showed that the situational motivation could appear to be triggered by external activation, such as a hoax. The results extend a line of research that shows the ways individuals quickly engage in supportive actions by adding an original route.

Theoretical and Practical Implications

This study defined theoretically and suggested empirical evidence the way the instant public can be generated. However, some might question whether or not the instant public is observable in the real world and whether it differs from other elements of the pseudo-public (i.e., the slacktivists, hot-issue public), which has been discussed in previous research on social media activism. Past slacktivism research has tended to focus exclusively on the possibility of the transmission or evolution of slacktivism into chronic activism offline (e.g., Kristofferson et al., 2014; Lee & Hsieh, 2013; Morozov, 2009). In contrast, the goal of activists who use instant activism is to take advantage of a one-time effect that generates a significant amount of vocal support on the part of the instant public to demonstrate their mobilized power.

In considering motivations to become a member of the activist public, the instant public can be discussed in terms similar to the hot-issue public. The hot-issue public refers to those who are “. . . active only on a single problem that involves nearly everyone in the population and that has received extensive media coverage” (Grunig, 1997, p. 13). On the contrary, the instant public is generated by other available cues (e.g., hoaxes) even before the issue, such as current GMO labeling issues, is known to the general population. Moreover, this study showed that the instant public recognizes a problem in a short time and engages in vocal actions promptly, while the hot-issue public examines the issue with care before engaging in external action (Grunig, 1997; Kim et al., 2012).

This article claims that, in addition to the instant public, instant activism can generate both the hot-issue public and slacktivists. This study suggested that the concept of the instant public provides a framework within which scholars can understand the way people engage in behavior related to extant issues and the way those issues become social problems and/or hot issues. This study presented the dynamic interplay between issues and the public with this perspective.

The study also offers several practical insights. The study demonstrated the limitations of pseudo-activism for public relations practitioners. Although activists could generate an immediate change in individuals’ everyday life by spreading a hoax, individuals’ belief in the hoax might not make them quickly engage in visible supports on social media. Even though a social media hoax has impacts on having a situational motivation, which leads to social media supports, the mediated process might be a relatively deliberative decision rather than an instant reaction. For the general population, this study draws careful attention to engaging in social movements without deliberative considerations. As the findings of this study showed, individuals who are less knowledgeable on a social issue might be involved in an irrational activism on social media.

Limitations and Future Research

Although this study attempts to suggest theoretical and empirical evidence to address current social media phenomena, the results of this study have limitations in generalizing to broad social media activism. This study introduced a hoax-spreading strategy committed by some non-profit advocacy groups as an example of instant activism. Also, this study tested the effects of a social media hoax in the context of GMO labeling issues. Thus, future research is needed to provide empirical evidence of these new concepts and elements of the public. The authors of this study ask for caution to the readers in interpreting the results.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Keonyoung Park

Author Biographies

Keonyoung Park (MA in Mass Communication, University of Minnesota) is a PhD candidate in S.I. Newhouse School of Public Communications at Syracuse University. Her research interests include social media activism, ethics, and corporate political advocacy.

Hyejoon Rim (PhD in Mass Communication, University of Florida) is an Assistant Professor in the Hubbard School of Journalism and Mass Communication at the University of Minnesota. Her research focuses on corporate social responsibility, consumer skepticism, and political socialization and media use. She has published her research in Journal of Communication, Journalism & Mass Communication Quarterly, Journal of Business Research, Public Relations Review, and Journal of Public Relations Research.

References

Aldoory

Grunig

J. E.

(2012). The rise and fall of hot-issue publics: Relationships that develop from media coverage of events and crises. International Journal of Strategic Communication, 6(1), 93–108.

Aldoory

Van Dyke

M. A.

(2006). The roles of perceived “shared” involvement and information overload in understanding how audiences make meaning of news about bioterrorism. Journalism & Mass Communication Quarterly, 83(2), 346–361.

Alhabash

McAlister

A. R.

(2015). Redefining virality in less broad strokes: Predicting viral behavioral intentions from motivations and uses of Facebook and Twitter. New Media & Society, 17(8), 1317–1339.

Baron

R. M.

Kenny

D. A

. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51(6), 1173–1182.

Botan

(1997). Ethics in strategic communication campaigns: The case for a new approach to public relations. Journal of Business Communication, 34(2), 188–202.

Breuer

Groshek

(2014). Online media and offline empowerment in post-rebellion Tunisia: An analysis of Internet use during democratic transition. Journal of Information Technology & Politics, 11(1), 25–44.

Brickman

(2017, April 18). 3 ways to win at social media activism. Forbes. https://www.forbes.com/sites/laurabrickman/2017/04/18/three-commandments-for-online-activism/#68705f8b427f

Brodock

(2010). Economic and social factors: The digital (activism) divide. In Mary

(Ed.), Digital activism decoded: The new mechanics of change (pp. 71–85). International Debate Education Association.

Chen

Y. R. R.

Hung-Baesecke

C. J. F.

Kim

J. N.

(2016). Identifying active hot-issue communicators and subgroup identifiers examining the situational theory of problem solving. Journalism & Mass Communication Quarterly, 94(1), 124–147.

10.

Curtis

Edwards

Fraser

K. L.

Gudelsky

Holmquist

Thornton

Sweetser

K. D.

(2010). Adoption of social media for public relations by nonprofit organizations. Public Relations Review, 36(1), 90–92.

11.

Earl

Kimport

(2011). Digitally enabled social change: Activism in the Internet age. The MIT Press.

12.

Flynn

L. R.

Goldsmith

R. E.

(1999). A short, reliable measure of subjective knowledge. Journal of Business Research, 46(1), 57–66.

13.

Glaisyer

(2010). Political factors: Digital activism in closed and open societies. In Mary

(Ed.), Digital activism decoded: The new mechanics of change (pp. 85–98). International Debate Education Association.

14.

Goffman

(1959). The moral career of the mental patient. Psychiatry, 22(2), 123–142.

15.

Grunig

J. E.

(1997). A situational theory of publics: Conceptual history, recent challenges and new research. In Moss

MacManus

Verčič

(Eds.), Public relations research: An international perspective (pp. 3–46). International Thomson Business.

16.

Grunig

J. E.

Kim

J. N.

(2017). Publics approaches to health and risk message design and processing. In Oxford research Encyclopedias. Oxford University Press. http://communication.oxfordre.com/view/10.1093/acrefore/9780190228613.001.0001/acrefore-9780190228613-e-322

17.

Hallahan

(1999). Seven models of framing: Implications for public relations. Journal of Public Relations Research, 11(3), 205–242.

18.

Hallahan

(2001a). The dynamics of issues activation and response: An issues processes model. Journal of Public Relations Research, 13(1), 27–59.

19.

Hallahan

(2001b). Inactive publics: The forgotten publics in public relations. Public Relations Review, 26(4), 499–515.

20.

Hon

(2015). Digital social advocacy in the Justice for Trayvon Campaign. Journal of Public Relations Research, 27(4), 299–321.

21.

L. T.

Bentler

P. M.

(1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

22.

Irani

Sinclair

O’Malley

(2001, April). Whom do you trust? The influence of culture, gender, geography on consumer perceptions [Conference session]. Association of International Agricultural and Extension Education Conference. Baton Rouge, LA.

23.

Kata

(2010). A postmodern Pandora’s box: Anti-vaccination misinformation on the Internet. Vaccine, 28(7), 1709–1716.

24.

Kees

Berry

Burton

Sheehan

(2017). An analysis of data quality: Professional panels, student subject pools, and Amazon’s Mechanical Turk. Journal of Advertising, 46(1), 141–155.

25.

Kim

J. N.

Grunig

J. E.

(2011). Problem solving and communicative action: A situational theory of problem solving. Journal of Communication, 61(1), 120–149.

26.

Kim

J. N.

Grunig

J. E.

(2010). Reconceptualizing the communicative action of publics: Acquisition, selection, and transmission of information in problematic situations. International Journal of Strategic Communication, 4(2), 126–154.

27.

Kim

J. N.

(2013). Two types of public relations problems and integrating formative and evaluative research: A review of research programs within the behavioral, strategic management paradigm. Journal of Public Relations Research, 25(1), 1–29.

28.

Kim

J. N.

Kim

S. H.

Kim

J. R.

(2012). What makes people hot? Applying the situational theory of problem solving to hot-issue publics. Journal of Public Relations Research, 24(2), 144–164.

29.

Kim

J. N.

Shen

Morgan

S. E.

(2011). Information behaviors and problem chain recognition effect: Applying situational theory of problem solving in organ donation issues. Health Communication, 26(2), 171–184.

30.

Krishna

(2017). Motivation with misinformation: Concep-tualizing lacuna individuals and publics as knowledge-deficient, issue-negative activists. Journal of Public Relations Research, 29(4), 176–193.

31.

Kristofferson

White

Peloza

(2014). The nature of slacktivism: How the social observability of an initial act of token support affects subsequent prosocial action. Journal of Consumer Research, 40(6), 1149–1166.

32.

Lee

Y. H.

Hsieh

(2013, April). Does slacktivism hurt activism? The effects of moral balancing and consistency in online activism. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 811–820). Association for Computing Machinery.

33.

Lovejoy

Saxton

G. D.

(2012). Information, community, and action: How nonprofit organizations use social media. Journal of Computer-Mediated Communication, 17(3), 337–353.

34.

Madsen

V. T.

Verhoeven

J. W.

(2016). Self-censorship on internal social media: A case study of coworker communication behavior in a Danish bank. International Journal of Strategic Communication, 10(5), 387–409.

35.

Meikle

(2014). 27 Social media, visibility, and activism: The Kony 2012 campaign. In Ratto

Boler

(Eds.), DIY citizenship: Critical making and social media (pp. 373–384). MIT Press.

36.

Men

L. R.

Tsai

W. H. S.

(2013). Beyond liking or following: Understanding public engagement on social networking sites in China. Public Relations Review, 39(1), 13–22.

37.

Moon

B. B.

Rhee

Yang

S. U.

(2016). Developing public’s information transmitting behavior (ITB) model in public relations: A cross-national study. Journal of Public Relations Research, 28(1), 4–18.

38.

Morozov

(2009, May 19). The brave new world of slacktivism. Foreign Policy. https://foreignpolicy.com/2009/05/19/the-brave-new-world-of-slacktivism/

39.

Ross

Irani

Silberman

Zaldivar

Tomlinson

(2010, April). Who are the crowdworkers? Shifting demographics in Mechanical Turk. In CHI’10 extended abstracts on Human factors in computing systems (pp. 2863–2872). Association for Computing Machinery.

40.

Senapath

(2017, March 6). Nestlé stands strong despite GMO labeling bullies’ latest tactic. Forbes. https://www.forbes.com/sites/kavinsenapathy/2017/03/06/nestle-has-no-plans-to-cave-to-gmo-labeling-bullies-latest-tactic/#26537e5e33a5

41.

Seo

Kim

J. Y.

Yang

S. U.

(2009). Global activism and new media: A study of transnational NGOs’ online public relations. Public Relations Review, 35(2), 123–126.

42.

Skoric

M. M.

(2012). What is slack about slacktivism? In Skoric

M. M.

(Ed.), Methodological and conceptual issues in cyber activism research (pp. 77–92). Asia Research Institute, National University of Singapore.

43.

Taylor

Kent

M. L.

White

W. J.

(2001). How activist organizations are using the Internet to build relationships. Public Relations Review, 27(3), 263–284.

44.

van der Linden

. (2013). What a hoax: Why people believe in conspiracy theories. Scientific American Mind, 24(4), 41–43.

45.

van der Linden

. (2015). The conspiracy-effect: Exposure to conspiracy theories (about global warming) decreases pro-social behavior and science acceptance. Personality and Individual Differences, 87, 171–173.

46.

Veil

S. R.

Reno

Freihaut

Oldham

(2015). Online activists vs. Kraft foods: A case of social media hijacking. Public Relations Review, 41(1), 103–108.

47.

Veil

S. R.

Sellnow

T. L.

Petrun

E. L.

(2012). Hoaxes and the paradoxical challenges of restoring legitimacy: Dominos’ response to its YouTube crisis. Management Communication Quarterly, 26(2), 322–345.

48.

Zaichkowsky

J. L.

(1994). The personal involvement inventory: Reduction, revision, and application to advertising. Journal of Advertising, 23(4), 59–70.

49.

Zuckerman

(2014). New media, new civics? Policy & Internet, 6(2), 151–168.