Understanding the Internet Water Army: Domain, Characteristics, Purposes, Messages and Affordances, and Consequences

The general domain consists of large numbers of users, whether identified or anonymous, contributing to an online site. These refer to processes (general domain), rather than named entities (specific domain), and focus on generally acceptable behavior, such as contributing metainformation or promoting products. A very general domain is crowdsourcing, or “a type of participative online activity in which an individual, an institution, a non-profit organization, or company proposes to a group of individuals of varying knowledge, heterogeneity, and number, via a flexible open call, the voluntary undertaking of a task” (Estellés-Arolas & González-Ladrón- De-Guevara, 2012, p. 197). We would generalize this to remove the requirement of a specific call by and organization to engage, or in some cases even the conscious awareness of the users. Examples include Wikipedia, Flicker photo tags, Amazon recommendations, YouTube likes, Q&A sites, Linux, and GoFundMe (Doan et al., 2011). Most crowdsourcing is unpaid, but some involves compensation, such as prizes (e.g., for innovation challenges) (Doan et al., 2011). Human flesh search is a form of online crowdsourcing, whereby many users are invoked via a Q&A format to identify, track down, and even punish a perpetrator – a form of cyber-vigilantism (Xu, 2015, p. 264). Similarly, voluntary online sedition hunters have identified a number of the U.S. Capital insurrectionists on January 6, 2021(Mak, 2021).

Another general concept is social media influencers, “independent, third-party endorsers who shape attitudes through…social media” (Freberg et al., 2011, p. 90). A form of online social influencing is a brand ambassador, who focuses on particular brands (Smith et al., 2018, p. 8). Social influencers are typically independent from the referred organization, while the brand ambassador is typically associated through an explicit affiliation, helping both to legitimize the organization and increase the online influence and status of the promoter. They typically do not receive financial compensation, but may receive free products they then discuss (Dhanesh & Duthler, 2019). Other general related user types include crowdsourced promotion (Kim et al., 2018), Internet public relations (Wu et al., 2013), smart and flash mobs (Rheingold, 2002), and self-branders (Khamis et al., 2017). Currently receiving vast public, legal, political, and research attention is the general multi-dimensional concept of fake or fabricated news (Molina et al., 2021), the dissemination of false content.

Another instance of this general domain is the use of machine-generated bots and digital propaganda – in particular, their effects on interfering with the political agenda and public opinion, such as Russian bots in the 2016 U.S. election (Singer & Brooking, 2018; see also Stukal et al., 2017), or social bots in manipulating public opinion about India-Pakistan conflicts and Indian elections (Neyazi, 2020). Computational propaganda, applying a mixture of algorithms, anony mit y, au tomat i o n , and human management, is an organized attempt to generate false amplification and misinformation in order to create a bandwagon effect or false consensus. A particular form is automated fake engagements (Kwon et al., 2022).

Click farms and follower factories use (X) and increasingly Instagram (esp. its Stories feature) to game the use of likes, views, numbers of followers, and other indicators of attention and popularity (Lindquist, 2018) – essentially, an informal and often illegal process of purchasing followers. Lindquist describes the extensive accessibility to follower/click sellers, and how they are self-taught, began working while teenagers, and come from lower-middle-class families. These entrepreneurs use software and sites that offer a wide array of services, targeting different categories of followers (e.g., by gender, country), and provide followers and clicks to many resellers. The “followers” may be actual users, or generated by automated scripts; the followers may be automatically purchased and resold through website interfaces; and they may actually originate in other countries, such as India or Russia.

Crowdturfing is a negative and more specific side of crowdsourcing, disseminating malicious URLs, developing fake grassroots campaigns, and distorting search engine results (Lee et al., 2013). Sites with from 70-95% of tasks involving crowdturfing include MinuteWorkers, MyEasyTask, Microworkers, and ShortTask (Wang et al., 2012). PR firms, agents, or businesses generally use crowdturfing platforms or systems developed for specific crowdsourcing applications, to initiate and coordinate mass action, for positive and negative purposes. These systems themselves have to deal with evaluating and filtering both the content (e.g., poor or false quality) and users (e.g., malicious, fraudulent) involved in these activities. Crowdturfing systems are rapidly growing, both in revenue and users (Wang et al., 2012). Similar services can be found at the US website Subvert and Profit (www.subvertandprofit.com), which claims they can access 25,000 users to perform tasks, and the UK website socioniks.com (Fielding & Cobain, 2011). Search optimization, account creation, and spam campaigns are also offered on Freelancer and eBay (Wang et al., 2012).

A sock puppet is defined as malicious and/or deceptive individuals holding multiple identities to vandalize online discussion and/or control public opinions (Bu et al., 2013; Kumar et al., 2017). However, some define sock puppets as individuals who, through alternative accounts, provide fake reviews of, or praise or defend, their own works that were earlier posted under their identified account (Seymour, 2011).

A large group of services is specifically devoted to governmental or political purposes. One is the Chinese 50 Cent (50c) or US Cent party (King et al., 2017; Wu et al., 2013). “50c party” (五毛党) users provide “social media comments posted at the direction or behest of the regime, as if they were the opinions of ordinary people” (King et al., 2017, p. 484). King et al.’s (2017) analysis of the estimated nearly half billion Chinese 50c Party posts in 2013 show that while posters have typically been thought of as similar to the IWA – i.e., as atomized, largely independent users – they are actually primarily governmental employees (though others voluntarily make similar posts). Their posts are designed primarily to divert attention away from any oppositional or controversial content (esp. if that might lead to collection action) rather than to engage in confrontation or argument, and to present positive conversations about salient topics and cheerleading for government actions or policies.

Bradshaw and Howard (2017) review what they call cyber troops, or “government, military or political party teams committed to manipulating public opinion over social media” (p. 3) in 28 countries (see their Table 1, p. 13). Cyber troops include contracted companies, paid individuals, political supporters, computational propaganda (bots), and fake or stolen accounts, all to spew fake news and spam, manipulate likes and retweets, shape or distract attention, and misrepresent posts as grassroots opinion. For example, China implemented a worldwide campaign aimed at Americans to promote disinformation and physical protests in a wide array of languages, social media platforms, websites, and forums (Serabian & Foster, 2021). For example, Mozur et al. (2024) report on leaked documents showing how China’s government-sponsored campaign targeting foreign governments, telecommunications firms, Chinese citizens domestically and abroad, and ethnic minorities buys data and cyberattack tools, and hires hackers, from private enterprises and contractors. Bradshaw and Howard (2017) show that all authoritarian regimes (in the countries studied) use these cyber troops to manipulate their publics. Democratic countries also implement cyber troops to influence other countries’ populations, as well as to counter terrorist propaganda, in addition to political parties using them for domestic campaigns.

Jothi and Me (2020) also note that this business model exists around the world, such as the U.K. SocioNiks or the Australian uSocial. In The Philippines, keyboard trolls were hired to promote and continue to support candidate and President Duterte (Bradshaw & Howard, 2017). In Nigeria, social media entrepreneurs (using cheap smartphones and a variety of inexpensive social media and private messaging apps, esp. WhatsApp groups) who provide political support, discredit opponents, deliberately spread false information, and manipulate photos are called propaganda secretaries (Hassan & Hitchen, 2019). Other related specific governmental or political user types include the Russian online army, troll armies, or web brigades (Karpan, 2018), seminar users (Darwish et al., 2017), (Internet) pushing hands, and vote spammers (Wu et al., 2013).

The specific phenomenon of the Internet Water Army in Chinese social media primarily involves real people (i.e., not bots). Taobao and other Chinese online platforms enable different forms of discussions such as posts, articles, videos, and Q&A sessions, in which IWA users may create various types and forms of misinformation (Emerging Technology, 2011), or create the false perception of supportive networking links and retweets. IWA workers may engage in “slander, entrapment or defamation to attack their competitors, fabricate pseudoevents, and confuse the public” (Kuang, 2018, p. 116). Silverman et al. (2020) also describe examples of marketing and PR organizations in over 15 countries creating and spreading disinformation, deception, and harassment for hire, as similar to the activities of the IWA; this growing development has been referred to as the professionalization of deception.

IWA workers differ from sock puppet representatives in several ways: (1) IWA users are usually a low-income population, and thus they are less likely to create fake accounts to promote their own books or Wikipedia articles, while sock puppets are likely to be higher status content producers (such as authors), or professionals hired by a government or corporation; (2) IWA users are usually part of large, transient groups of people hired by PR companies to work for someone else rather than themselves, while sock puppets typically operate for their own purposes; (3) the IWA industry has a fairly common organizational structure (see below), while sock puppets are mostly independent users; (4) the IWA does not emphasize an individual identity to tell the story, and a frequent goal is to create an impression of general consensus among the public, while sock puppets heavily rely on fake (not anonymous) identities to foster a fake reality. Separately, King et al. (2017) distinguish the 50c Party from the IWA and other similar terms (e.g., volunteer 50c members, little red flowers, American Cent Party, etc.) in that the 50c Party exclusively serves the interests of Chinese government, while the IWA mainly works for companies and nonpolitical individuals.

The IWA is an example of what Grohmann and Corpus Ong (2024) call “disinformation for hire as everyday digital labor.” They emphasize the wide range of industries, platforms, and workers involved in this digital ecosystem, and the tensions and challenges of developing, implementing, and enforcing policies and regulations concerning such activ ities. Lindquist and Weltevrede (2024), focusing on these governance issues, refer to this general phenomenon as the “engagement as a service” market.

To further explain the IWA, the following sections describe four dimensions of the IWA: characteristics, purposes, messages and affordances, and consequences (adapted from Chaffee, 1991; see Table 1 for a summary).

Table 1.

Dimensions and Subdimensions of the Internet Water Army

The Internet Water Army consists of individual posters (workers), organized for a short time, often posting an overwhelming amount of potentially meaningless messages, operating through multiple online identities, to simulate a large number of other (regular) users, and who are paid after each task (Wu et al., 2013). The individual poster is often referred to as a “sailor” and the professional team leader the “navy head.” There is no face-to-face contact, and the identity of the individual “pusher” or sailor is typically not known (either anonymous or pseudonymous), even to the hiring PR firm or IWA agent (Kuang, 2018). IWA workers are typically activated for a given task, and dismissed afterwards, though typically return for multiple missions. The main force consists of people with lower socioeconomic status, plenty of spare time, and need for money, such as migrants, housewives, college students, and even prisoners (Chen et al., 2013, 2016; Elsner, 2013). A general requirement is knowledge about and potential user experience with the target social media platform(s).

Because the initial purposes of the IWA are to attract (or distract) attention and influence opinion, IWA users attempt to create an impression on other internet users that the topics they are discussing are popular, and that their opinions strongly resonate with other users. To accomplish this goal, they may initiate a large number of discussions by using multiple IDs to spread the same message (Nanjing Marketing Group, 2011; Xu et al., 2014), indicating that a given topic, post, or user is receiving extensive attention.

Researchers have noted some common characteristics of IWA accounts. Chen et al. (2013) collected user data from an IWA campaign and manually identified 70 potential IWA users out of 552 in total. They concluded that IWA users tend to stay active for a shorter time compared to legitimate users, often discard their IDs, and do not keep track of the conversations once they finish their tasks. The same IWA user ID may be active at different geographical locations within a short time interval, as the IWA account may be assigned by the resource team to different IWA users across their diverse geographical locations. IWA users do not build their personal networks through their IWA accounts, so there is an extremely low possibility that they have as many bilateral relationships as regular users (Wang et al., 2014). Moreover, Chen et al. (2013) reported that IWA users tend to create posts or comments rather than reply to other people’s posts and comments, largely because most IWA users do not have the intention of holding conversations or exchanging opinions with others. Chen et al. (2013) estimated that 50% of IWA users post every 2.5 minutes. Moving from one topic to another and posting to different types of discussions are also more likely to be higher than for legitimate users.

IWA businesses are distinctively organized and operated based on their own systems and rules. Chen et al. (2013) explain that the structure typically consists of the requester; the mission (set of tasks); and the IWA “agent”, which consists of a team or project manager (there may be multiple project leaders) who coordinates a trainer, posters/workers, online resources, and relationships with the public (see also Kim et al., 2018). The resources team is in charge of initiating and registering new IDs for the posters, and serves as human resource staff responsible for recruiting adept writers. A specific IWA mission or campaign (a set of goals and associated tasks) is initiated when a client requests a mission/campaign. The general process involves: receive request, input task and funds into system; distribute tasks (may be multiple); finish tasks; submit results (such as screenshot or links); evaluate task completion; make (typically very low) payments (Chen et al., 2013; Wang et al., 2012). More specifically, the mission is usually transferred and forwarded by a project manager, who is responsible for carrying out the whole project and leading the team. The project (or “mission”) may include several teams with different responsibilities. The trainer team coordinates with the poster team (IWA workers), gives them the necessary training, and schedules tasks for specific posters. The poster team is grouped and assigned with tasks by the training team after receiving instructions on the specific tasks. There is also a quality control process conducted by the project manager in order to validate if the posts meet the numeric and quality threshold required by the clients (Chen et al., 2013; Emerging Technology, 2011). Such a topdown organizational structure facilitates IWA task completion efficiency and maximizes worker utility, as each individual worker’s role is distinctly defined.

The IWA provides several different services depending on the requirements of their clients. In order to boost the digital popularity of celebrities, a PR company may pay the IWA to be fake followers and to extensively comment on, repost, or like the celebrity’s (or their PR agent’s) posts. The posts are designed to be seen by and propagated through online networks of people interested in some aspect of either the original or the subsequent artificial post (Wu et al., 2013). The mission may include a range of posting tasks such as articles, Q&A sessions, and even video clips. An analysis of 2869 Zhubajie campaigns for 1280 customers on the Chinese microblog Sina Weibo included tasks to extend a sponsored message via tweets, retweets, or buying followers (Wang et al., 2012). IWA users are hired to create fake reviews and posts on Taobao, the Chinese version of eBay, in an attempt to promote their clients’ products (Nanjing Marketing Group, 2011).

Wang et al. (2012) noted a variety of associated obstacles to the desired IWA activities: bots or search engines generating clicks on the crowdturfing site, workers using multiple accounts, and spam detector systems deleting worker posts. Once the targeted website notices the IWA activities and attempts to delete their posts, the IWA public relationship team is expected to contact the manager of the targeted website and persuade them to reverse the deletion. Establishing and maintaining a good relationship with the web manager benefits and even multiplies the exposure of the IWA posts. For example, the website may prioritize IWA comments among others under a certain post (Wang et al., 2012).

The IWA may be employed by social influencers to promote the influencers themselves or their works, which may consequently make them stand out and lead to various commercial opportunities (Pan, 2019). Celebrities, movie stars, and singers (via their agents) may hire the IWA to publicize their new movies, albums, or TV shows (Chen et al., 2013). For example, on August 2019, a Chinese idol quickly gained extensive coverage by China’s national media CCTV. When he publicized his new music video on Weibo, there were roughly 100 million reposts, which constituted at that time one-third of all Weibo users (Pan, 2019). The extraordinarily large number of reposts drew the attention of several governmental officials, and he was later accused by the Communist Youth League of China on their official social media account of faking his online popularity (Sohu, 2018). Regardless, these inauthentic numbers brought him numerous commercial opportunities (Pan, 2019).

Product companies may also employ the IWA to promote their products and compete with other companies. Paid online reviewers may receive professional training in writing such reviews and developing relationships with website webmasters (Liao et al., 2021). Some IWA users may pretend to be real product users and comment or write positive reviews on the product. This strategy is often applied to attract potential adopters of the products at the beginning stage of product diffusion because the early majority category of adopters relies heavily on the information from opinion leaders to evaluate whether they wish to adopt it (Rogers, 2003). Also, some companies may employ the same strategy as celebrities promoting their movies and TV shows, by initiating extensive discussion to attract attention. For example, a 2009 online article titled “Junpeng Jia, you mother asked you to go back home for dinner” (translated) posted in the online community of the computer game World of Warcraft attracted over 300,000 replies and more than 7 million views in only two days after it was posted (Chen et al., 2013).

Based upon a client’s request, the IWA may attempt to crowd out or delete negative reviews or comments about a certain person or company (Duan, 2010). The hiring PR company may first bribe the online media platforms such as Weibo to delete the unfavorable content. If the bribing fails, it may hire the IWA to post a massive amount of comments under a certain entry to dominate the comment section so that other online users will not be able to notice the negative comments.

Companies may also employ the IWA to attack their adversaries or competitors (Nanjing Marketing Group, 2011). By comparing similar products with different brands, companies often attempt to demonstrate the relative advantages (Rogers, 2003) of their products, services, personalities, ideology, etc. over those of their competitors to persuade customers to purchase their brand. This strategy can be convincing when companies are able to present statistical or other types of valid evidence. However, it may also be misleading, unethical, or illegal when companies intentionally post misinformation, sometimes even causing social upheaval. For example, a 2010 post on Sina Weibo that claimed that the milk powder of Yili (a company that sells milkrelated products) could cause premature puberty was created and disseminated by a PR company employed by competitor Mengniu (Herold, 2015).

A government may utilize the IWA as a tool to promote their policies and ideology, frame a discussion or set an agenda, exert influence on public opinion, or suppress discussion of a controversial topic or by oppositional forces (Wikipedia, 2020). For example, in China, 50c Party is recognized as a form of the IWA that is used only for political purposes (King et al., 2017). The main purposes are to influence public opinion, provide positive support for the government, and promote unity and stability (especially during emergency events), as well as to distract public attention from activities associated with collective action, and avoid controversy, while not explicitly censoring other content (King et al., 2017), via tens of thousands of online posters on microblogs and chatrooms (Barr, 2012). In the early 2010s, over 2 million IWA users, including prisoners (in return for reduced sentences) were reported being hired by websites, municipalities, provinces, and various government offices (Elsner, 2013).

Two types of posting strategies emerge from the literature: quantity-based messages and quality-based messages. Quantity-based messages are generated when there is a need for public attention toward a specific post or topic within a short time period (Xu et al., 2014). To achieve this goal, IWA workers may copy existing posts or comments, making slight changes, and repost them (Chen et al., 2013, 2016). Their comments or posts can sometimes be meaningful or related to the topic, while sometimes not, as their main objective is to attract attention and increase, or decrease, the popularity of the topic. As a result, similarity and relatedness are often the main criteria used to distinguish IWA messages from others (Chen et al., 2013; Sun et al., 2014). Quality-based messages are designed with logical expression, reasoning, credible, and persuasive (Xu et al., 2014) in order to influence the audience’s evaluation and even decision making. IWA users may initiate both quantity- and quality-based content to create an impression that their reviews are popular and reliable (Fayazi et al., 2015).

The way that the IWA message conveys valence (positivity or negativity) may affect how the target audience views a specific person, product, or social event (Binder et al., 2015). Message valence is often overlooked in quantity-based message design. Within quality-based messages, the use of phrases and words that express emotions becomes important as the goal is to persuade the audience. For example, King et al. (2017) identified six types of 50c Party “cheerleading” content: “expressions of patriotism, encouragement and motivation, inspirational slogans or quotes, gratefulness, discussions of aspirational figures, cultural references, or celebrations” (p. 486). Guo et al. (2017) proposed that IWA product reviews may include as many positive emotional words as possible. A sentiment analysis of a large number of IWA workers’ and non-workers’ tweets found that workers’ content included less swearing, less anger, and less first person singular; overall, they were less personal (Lee, 2013).

Media affordances provide additional insight to such messages. “Media affordances are relationships among action possibilities to which agents perceive they could apply a medium, within its potential features/capabilities/ constraints, relative to the agent’s needs or purposes, within a given context” (Rice et al., 2017, p. 109), and include pervasiveness, editability, self-presentation, searchability, visibility, and awareness. We specifically discuss communication visibility, as it is a central affordance (Treem et al., 2020). Communication vi sibi l i t y includes message (content) transparency and user network (relationship) translucence, as well as user anonymity (low identifiability or low visibility). We argue that though media affordances do not constitute an IWA message per se, they provide critical boundary conditions based on which an IWA campaign may be more or less effective in achieving its goals.

Message Transparency. The very nature of most online and social media (except perhaps for those featuring only short-term, disappearing posts), is to share and make visible content, both within and across groups (boyd & Ellison, 2007). The pervasive transparency of social media messages, due to rapid dissemination, enduring storage, low cost, easy access by unintended or unknown users, searchability, links, retweets, hashtags, and various forms of notifications, facilitate the fundamental aspect and purpose of IWA activities. To the extent that different poster strategies (e.g., quantity, quality) and platform features (e.g., popular hashtags, trend monitoring) afford different levels or kinds of message transparency, IWA posters and their clients may be more or less successful. Indeed, many content trends in Sina Weibo are due to ongoing retweets by a low percent of fraudulent accounts designed to inflate specific posts, making the content more transparent (Yu et al., 2012).

Network Translucence. Network patterns associated with crowdsourcing sites, IWA workers, followers, and threads are a central focus of IWA detection studies (Jothi & Me, 2020). In many IWA campaigns, the message content and its quality (transparency) are not the primary goal form of visibility; rather network translucence data such as message quantity and attention (the number of followers, likes/dislikes, ratings, posts, comments, retweets) are.

Crowdsourced promotion workers tend to be interconnected through a small-world network (Kim et al., 2018). Kim et al. (2018) posted two tasks promoting two YouTube videos before they were formally released, hired 28 workers for one week, and used the resulting data to determine activity, network patterns, and ratio of legitimate users to workers’ followers, with effectiveness measured by number of hits to the video links. They noted that workers can falsely promote their own effectiveness by following themselves through additional self-accounts or by having co-workers follow them. Indirect measures of effectiveness include the number of tasks performed over time, the number of followers, or Klout scores (since shut down), though in their study, none of these was associated with actual effectiveness.

Lee et al. (2013) distinguished three types of crowdturfing workers: professional, casual, and middlemen. They specifically analyzed twitter-related campaigns, comparing nearly 350,000 worker tweets to nearly 1.9 million non-worker tweets. Professionals had more followings and followers, included more links, but far fewer tweets, with well-connected networks fostering dissemination; however, they rarely communicated directly with other users. 50c Party posts are neither random nor equally distributed, but organized into bursts of high-volume activity synchronized with major government policy statements or national events (King et al., 2017, p. 488), indicating substantial strategic governmental coordination. Liu et al. (2015) refer to the quite sparse links among IWA posters as “an unnatural social network.” They analyzed 50 source nodes, a total of 9,000 nodes and 15,000 edges, over 10 days, from the massively popular Sina microblog. They distinguished professional workers, who take on tasks very frequently, from gray workers, who do so only occasionally. However, based on their overlapping membership in multiple worker cliques, the gray workers generated greater propagation than did the professional workers.

User Anonymity. Anonymity refers to the extent to which the source of message is unidentified and unacknowledged by communicators (Scott, 1998). Anonymity is a central feature or option for much computer-mediated communication, online sites, and social media (Szulc, 2019), and it lowers communication visibility. Many Chinese social media platforms such as Weibo still allow anonymity, in spite of the 2011 “Beijing Municipal Provisions on Microblog Development and Management,” which outlawed anonymity and even pseudonyms (Jia & Han, 2020). In IWA posts, typically the goal is to make the worker’s identity anonymous (including to the IWA agent), but to make the message and network links, both from the worker and from and among the users, as visible (transparent and translucent) as possible. Further, the invisibility of the anonymized IWA worker (including using multiple anonymous accounts) is an attempt to increase the credibility of the post(s) by portraying the content or links as generated by unique third parties rather than by the source personality or company or by a persistent pseudonym.

This type of consequence depends on whether the effects of IWA activities (e.g., quantity and quality of online posts) are functional/ beneficial or dysfunctional/harmful, for different stakeholders. For example, companies may hire IWA users to promote their movie and tag it as “worth watching”, and thus people may be attracted to buy tickets (Chen et al., 2016). This consequence may be perceived as desirable by the company and its media client, but, depending on their experience, undesirable by the customers. Another undesirable consequence is diminished online trust and information credibility (Chen et al., 2013, 2016). Vote-spamming distorts shared information and discourse outcomes (Zhang & Labiod, 2019), contributing to cyber-pessimist views of the civic consequences of new media (Zhao, 2014). Massive criticism of a particular position can generate a spiral of silence, crowding out discussion, minimizing minority opinions, and maximizing a false perception of the majority view (Noelle-Neumann, 1993).

Kwon et al. (2022) identified two complementary individual and social consequences of a computational propaganda operation (the 2018 South Korean “Druking” case). Their analysis of 1389 fake accounts generating over 56,000 engagements designed to significantly alter topranked posting visibility, and comments by over 45,000 users, on an online news site within a three-hour period, showed that bot-assisted flooding of anti-government opinions counter to those in more general online media, represented two related effects. First was the false amplification of opinions by the fake posters; second was the resulting diminution of users’ political commenting, representing an artificial spiral of silence. These both lead to what the authors refer to as “a distorted opinion environment.”

This type of consequence depends on whether the effects occur as a first-order response to IWA activities or as a second-order result of those initial consequences. For example, a direct consequence can be that public attention is gathered and public opinion is affected (Xu et al., 2014), while an indirect consequence can be lowered authenticity and general perceived value of information in online discussions (Guo et al., 2017). Manipulating public opinion may undermine participation and trust in cyber collective actions such as crowdsourcing (Estellés-Arolas & González-Ladrón-De- Guevara, 2012; Zeng et al., 2014). The low level of relevance of some IWA content to the referred earlier posts may confuse general users and lower their level of perceived interactivity and their impetus to create their own usergenerated content (Carr & Hayes, 2015). Official associations such as the Public Relations and Communication Association, and the International Communications Consultancy, have attempted to reinforce principles against such unethical practices, which harm the reputation of legitimate PR firms (Silverman et al., 2020; Jiaze, 2021), yet PR companies may feel they have to engage in those activities in order to stay competitive (Wu et al., 2013).

This type of consequence depends on whether the effects are intended or expected by the innovation promoters or members of a social system. As an anticipated marketing strategy, companies may hire the IWA to attack their competitors or spread rumors (Sun et al., 2014), yet generate unanticipated consequences. As an example, the fake news that Yili’s milk powder is detrimental to health that Mengniu disseminated caused extreme panic and antipathy at the national level (Nanjing Marketing Group, 2011). Although the anticipated outcome of Mengniu was that potential customers would switch their purchases from Yili to Mengniu, the unanticipated outcomes were more critical, social, and legal. The contradictions and tensions associated with paid online posting in China are to some extent a result of ambiguous Chinese regulation stemming from emphasizing both political control and economic growth, and the facilitation of digital communicative labor (Han, 2018). For example, in China, Internet mercenaries are not legally recognized, but they are also not legally prohibited (Wu et al., 2013).

As with innovations in general (Rogers, 2003), the different types of IWA consequences typically occur in combination (such as undesirable, indirect, and unanticipated). Low (2018) reported that IWA companies may post inappropriate content such as pornography in an attempt to trigger deletions of message threads or discussions, but that may diminish the level of civility and undermine the online communication environment. The negative impacts of the IWA on the quality of online discussion have received attention from the Chinese government. As a legislative reaction, a Cybersecurity Law was introduced by the Chinese government in June 2017, which put 200 suspects under arrest and deleted more than 5000 accounts (Low, 2018). While one perspective on this transnational economy is to emphasize the unregulated and harmful nature of the system as well as the ethics of the sweatshop aspect of digital click workers, Lindquist (2018) instead focuses on the reality, economics, and motivations of click farmers (specifically, in Indonesia). Thus, Lindquist positions this digital and personal capitalist ecosystem as multi-consequential: dynamic, evolving, multiple, and interdependent patron-client agreements requiring trust but also frequent turnover and repair. Similarly, Ong and Cabañes (2019) situate the generation of digital disinformation by anonymous paid click workers as part of production culture, akin to highly competitive piece work, short-term projects, and freelance gig work.

Message framing is the way that communicators (e.g., IWA agents or users) design the message to emphasize or deemphasize aspects of an issue or an event, in order to shape audience attention to and interpretations of that message (Binder et al., 2015). At the individual level, future research may continue to study what frames influence how social media users evaluate the credibility and trustworthiness of an IWA message, especially among quality-based messages (Xu et al., 2014).

At the macro-level, Kuang (2018) applied agenda-setting theory and spiral of silence theory to understand the IWA process. For a given topic, the IWA attempts to move the topic to, or higher up on, the agenda of a specific public, focusing attention on praise or condemnation through massively repeated content. It is therefore important to gain a better understanding of the uses and effects of IWA campaigns at the organizational and political levels. Novel approaches to measuring such effects, such as computational tools, may be especially helpful.

As noted above, digital media provide numerous features or affordances to leverage IWA efforts, such as copy-and-pasting, reposting, retweeting, hashtags. In turn, this process may generate the spiral of silence effect, whereby ordinary people quickly come to feel their opinions are in the minority or deviant, and thus refrain from counter-posting. Therefore, future research may test how media affordances such as visibility and anonymity facilitate or constrain the intended effects of IWA messages, while at the same time, enable other undesirable, indirect, or unanticipated consequences.

Chen et al. (2003) developed the aging theory of online bursting topics to study the life cycle of online discussion topics, involving five stages: latency, emergence, evolution, recession, and death. Xu et al. (2014) argued that most IWA messages are sourced during the latency and early evolution stages, in which public attention starts to be aroused. The persuasive effects of the IWA might be strongest during this time because the audience is receiving information and forming their personal attitudes. They also suggested that IWA users may initiate their activities with quantity-based messages to gather attention and then engage in quality-based messages to increase their persuasiveness. Yet, few studies specify the stages during which a specific IWA message type is utilized.

The sequenced development of online discussion topics and public attitudes through IWA activities can also be studied from the perspective of diffusion of innovations theory (Rogers, 2003). This theory identified five stages through which an innovation is diffused and leads to a decision of adoption, reinvention, discontinuance, or rejection: knowledge, persuasion, decision, implementation, and confirmation. During the knowledge stage, the audience is exposed to the basic information about the innovation. Then, during the persuasion stage, they start to form a personal attitude toward the innovation by receiving other people’s evaluation information. From this perspective, IWA users may start posting the discussion topics and increasing their digital popularity with quantity-based messages during the knowledge stage. Then, they may apply quality-based valenced messages during the knowledge stage, in which the target audience starts actively seeking other people’s opinions, retweeting posts, and shaping their own attitudes. The diffusion of innovations concept of critical mass is useful to focus on when online links (followers, reposts) become viral. Studying IWA strategies during each diffusion stage can help facilitate development of interventions that detect and label potential IWA content.

In the case of IWA, a few Chinese cultural and political issues are particularly relevant. Official Chinese discourse about Internet governance emphasizes personal security, social stability, and moral goodness. So, a large number of messages from IWA workers reinforcing this discourse, attempting to reduce the possible “destabilizing field of contentions” (Cui & Wu, 2016, p. 265), resonates with many online users in China as well as the Communist Party. Kuang (2018) also notes that most Chinese users expect a stable social context, that governmental (especially local) units deal with problems, and to feel that their opinions are valued. The Chinese government seeks to avoid the incursion of external ideologies, while maintaining control, through shaping Internet technology use and features, as well as online dialog (Wang, 2013). Thus, practices such as 50c Party and the IWA may serve the purpose of focusing, congealing, and maintaining attitudes. Future research, especially in the political arena, may study how the phenomenon of IWA-type behavior intertwines with the Chinese practice of weiguan (围观), or mass gatherings for public spectacles, applied to online political participation with virtual crowds expressing public opinions and complaints about offline controversies, both to experience expression but also to generate pressure for resolution: that is, online weiguan (网络围观) (Xu, 2015).