To Access or Not to Access: Influencing Factors for Government Microblogging Information Seeking and Avoidance among Chinese Generation Z

Zheng, Yu

doi:https://doi.org/10.1155/2024/8288503

Human Behavior and Emerging Technologies

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Abstract Introduction Literature Review Results and Discussion Conclusion Data Availability Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2024 | Article ID 8288503 | https://doi.org/10.1155/2024/8288503

To Access or Not to Access: Influencing Factors for Government Microblogging Information Seeking and Avoidance among Chinese Generation Z

Yu Zheng¹

Academic Editor: Tze Wei Liew

Received13 Jul 2023

Revised02 Dec 2023

Accepted15 Dec 2023

Published06 Jan 2024

Abstract

In recent years, the effective enhancement of information communication effect through governmental social media in has emerged as a universally concerned issue on government governance within the social media era. As Generation Z represents the primary and frequent users of social media, understanding the factors influencing their behaviors regarding information seeking and avoidance on governmental social media platforms is essential (in China, the principal governmental social media platform is government microblogging). Employing the grounded theory methodology, 31 participants of Chinese Generation Z were recruited for the present study, and data were collected using an in-depth interview. The results showed that the factors influencing the information-seeking behavior of Generation Z towards government microblogging mainly include heuristic seeking factors (personal preference, emotional value, and following hot topics), systematic seeking factors (task demand and expert recommendation), and defensive seeking factors (defending stance, authority seeking, and impression management). The factors influencing the information avoidance behavior of Generation Z towards government microblogging mainly include heuristic avoidance factors (clickbait titles, content layout, excessive length, and high redundancy), systematic avoidance factors (selective ignorance and terminological density), and resource-limited avoidance factors (demand scarcity, time scarcity, and vitality scarcity). This study contributes to a more comprehensive understanding of the government microblogging information behavior of Generation Z. Implications for government microblogging governance, strategy recommendations, and indicates directions for future research are discussed.

1. Introduction

Accelerated by the rapid advancement of mobile Internet technologies, social media has become a fundamental channel for the exchange of information [1]. It has been increasingly utilized by various organizations to bolster public communication and service quality. In the context of governance, social media has progressively transformed into an indispensable platform, not only for the dissemination of public services but also for enabling dynamic interactions between governmental agencies and citizens [2]. This integration, termed “Social Media in Government,” leverages these digital platforms to tackle diverse social and political challenges [3]. Government agencies and officials are increasingly engaging with the public via social media, fostering transparency and direct communication [3]. Echoing the vision of “Transparent and Open Government” by Barack Obama, former President of the United States, the Obama Administration had championed the use of new media tools by federal departments for enhanced information dissemination and public interaction [4]. Governmental use of social media has thus become instrumental in fostering direct dialogue with citizens, innovating public participation in governance, and significantly contributing to the dissemination of public information, governance improvement, and public communication enhancement [5, 6]. Comparative studies on information seeking and avoidance have mainly concentrated in the field of medical informatics [7, 8]. In the field of public information, the public is facing the changes and challenges brought about by a new media environment for modes of public information release and interaction, and there is still a lack of a theoretical framework in the field [9]. Current research pertaining to this important subject largely focuses on elucidating the dissemination of government information and public communications. However, there exists a noticeable deficiency in the quantity and quality of theoretical and empirical research dedicated to comparative studies of public information-seeking and avoidance behaviors within the social media landscape. To address these challenges, researchers interested in understanding public information behavior need to pay more attention to theorizing in this field [10].

In China, Sina microblogging is one of the main platforms used for social media in government. Since its launch in 2009, as of the end of 2020, the number of daily active users had reached 225 million. In recent years, with the extensive development of the digital government in China, government microblogging has rapidly risen and developed. Government microblogging is defined as an official public affair interactive online platform that operates on third-party websites, providing services such as public information dissemination, public opinion communication, online public crisis management, and acceptance of citizens’ suggestions or feedback [11]. Its ability to interact with citizens and its level of public service are continually improving. According to the Fifty-first China Internet Development Statistics Report, released by the China Internet Network Information Center (CNNIC), as of December 2022, there were one hundred forty five thousand government microblogging accounts certified by the Sina microblogging platform. Compared with traditional government websites, government microblogging provides more convenient, transparent, and effective services and interactions, and it has stronger real-time information dissemination and interactivity during emergencies [11].

According to the fifty-first China Internet Development Statistics Report, the number of Chinese netizens has reached 1.067 billion, with a significant proportion being young netizens aged 10-29, predominantly from the main Generation Z (born mid-1990s to early 2010s) [12]. This study focuses on this demographic’s microblogging usage. Data from the “Chinese College Student Social Psychology Survey Database (2020)” indicates that microblogging is particularly prevalent among Chinese youth, with a usage rate of 47.55% [13]. However, their interaction with mainstream media via microblogging shows a divide: approximately half primarily consume information with minimal engagement, while the other half engage more deeply [14]. Notably, traditional “text and image” microblog posts are more popular among young people than innovative formats like H5 and comics [14]. The study also finds that active online engagement, such as expressing opinions and participating in discussions, is linked to increased trust in grassroots government [15]. This underscores the importance of leveraging online platforms for political engagement and social participation to enhance government-public interaction and improve the effectiveness of public services, thereby fostering political trust among young people [15].

Indeed, government microblogging is not only an effective channel for the government to provide public information and services but also a good platform for public participation in public issues and expressing public opinion. The information dissemination and interaction of government microblogging are more dynamic and transparent, contributing to the improvement of the relationship between the government and the public [16]. However, existing research indicates that the actual public attention and participation in government microblogging are not high, which has not achieved the expected interactive effect [17, 18], restricting the benign development and value of government microblogging. As shown in the China Government Microblogs Report 2020, as of December 31, 2020, the level of likes, comments, and shares by citizens on government microblogs was low, even among the top ten most influential government microblogs in China [19]. The issue of underutilization hinders the full potential of government microblogs in achieving administrative transparency and public communication. As an important platform for disseminating public information and providing public services, government microblogging can only effectively perform its public functions by garnering tangible public attention. How can government microblogging gain more active attention from the public instead of active disregard? Therefore, it is of significant research value to explore how to increase the attention and participation of the primary user group of Chinese microblogging—Generation Z —towards government microblogging. As digital natives, Generation Z’s unique information behavior patterns offer valuable insights for contemporary research. This demographic exhibits distinct information behaviors compared to previous generations, a phenomenon that warrants thorough investigation [12]. Exploring their microblogging habits, preferences, and interaction styles is crucial for understanding evolving trends in government social media usage. A nuanced comprehension of Generation Z’s engagement on microblogging platforms can inform the development and innovation of these platforms, aligning them more closely with the needs and expectations of this user group. This alignment is anticipated to drive higher levels of user engagement and overall platform dynamism. For government agencies, an in-depth understanding of Generation Z’s microblogging behaviors is imperative. Such knowledge is instrumental in crafting and executing more effective online communication strategies, thereby enhancing policy outreach and elevating the quality of public service delivery. Through deepening the understanding of the information behavior of Chinese Generation Z on government microblogging, this study explores the influencing factors for Chinese Generation Z to actively obtain or deliberately avoid government microblogging information. This will help to better predict and explain the information behavior patterns of an important user group of government microblogging—Generation Z—and provide more effective social media management strategies for government agencies. The following research questions were developed to guide the study: (1)RQ1: What factors influence Chinese Generation Z to engage in information-seeking behavior on government microblogging?(2)RQ2: What factors influence Chinese Generation Z to engage in information avoidance behavior on government microblogging?(3)RQ3: What are the differences between information-seeking and avoidance behavior on government microblogging among Chinese Generation Z, and how can these differences be understood?

2. Literature Review

2.1. Information-Seeking Behavior and Generation Z

Individual information behavior can be divided into avoidance, seeking, and encountering. Information encountering is a passive behavior, while avoidance and seeking are active behavior [20, 21]. Information seeking refers to the purposeful and active acquisition of information; its influencing factors can be individual and external, and individual factors can be further divided into cognitive and emotional categories. From the cognitive perspective, antecedent variables such as Big Five personality traits, age, cognitive ability, trust perception, benefit perception, ease of use perception, and self-efficacy have been found to significantly affect differences in individual information seeking [22, 23]. From the emotional perspective, it has been argued that individuals seek information after forming cognition from an elicited emotion [24]. External influences include factors related to tasks, the system, and the environment. For example, a task is a prime mover for active information seeking and is the main factor influencing the behavior [25].

As an audience that has grown up in the new media environment, youth have more opportunities to access various types of information online and are more receptive to new things. Researchers have pointed out that Generation Z is a generation that incorporates the Internet as part of their lives [26]. Thus, their information-seeking behavior occurs more frequently and is more dependent. For example, the information-seeking behavior of college students in China is also characterized by high frequency; 69.01% of Chinese college students use the network every day, 90% of college students consider their college life to depend heavily on the network, and social news (74.19%) and entertainment news (54.84%) are the main information categories to which Chinese college students pay attention [27]. In terms of environmental factors, on network information platforms, which are the main social sphere of young adults, interpersonal and environmental factors jointly govern young adults’ subjective norms for information seeking [28]. During the COVID-19 pandemic, Generation Z used social media as their primary source of information, including health-related information because they are a generation more familiar with the digital world and more inclined towards social media. This predilection can be attributed to the fact that social media information exists not only in text form but also provides images and videos, making the information easier to comprehend, more importantly. The rapid development of mobile Internet technology has made sharing on social media increasingly convenient, leading Generation Z to be more willing to share information with others through such platforms [29]. However, based on the research during the pandemic, Generation Z, while inclined to obtain information from social media, remains skeptical of the abundance of health-related information published on these platforms [29]. Generation Z is more willing to seek social information on social media, and male users tend to seek more cognitive/functional information [30]. Cross-generational comparison research found that emotional satisfaction is a powerful predictor of information-seeking behavior, regardless of the generation [30]. An exploratory study on Generation Z’s financial information-seeking behavior revealed that anxiety and information needs increase Generation Z’s information-seeking behavior [31]. Notably, future goal pursuits also increase Generation Z’s current information-seeking behavior [31].

2.2. Information Avoidance Behavior and Generation Z

Information avoidance refers to the behavior of consciously ignoring and avoiding certain information that is available and actively choosing not to acquire it [32]. Having more information does not always reduce uncertainty [33]; that is, sometimes, when people are faced with massive amounts of information, they need to spend more cognitive resources in choosing what to engage with, which generates more anxiety, reduces individual self-efficacy, and leads to the active choice to avoid certain types of information [34, 35]. It has also been argued that information overload leads to a scarcity of time for individuals. In other words, people tend to choose the information they need and prefer first within a limited time, so categories of information that individuals find to be “unwanted” and “disliked” are actively ignored, resulting in information avoidance [36]. Fear and disgust can also lead to information avoidance. These two emotions may originate from the information itself (e.g., the way the information is presented and the expression of the information content), from the consequences of the information (the cognitive, emotional, and behavioral consequences of acquiring the information), or from the individual’s emotional response to thinking about the information content, thus forming a “projection” in information selection [37].

Some researchers have emphasized that, among young people (the study used millennials as the sample), the convenience of information can be seen as a situational criterion because convenience can affect every stage of the information-seeking process [38]. This influential effect of convenience might be related to the low information retrieval skills among Generation Z. Some researchers found that Generation Z faces significant challenges in information-seeking, and they are uncertain where to find the information they need [31]. Apart from searching on the Internet, they prefer to obtain the required information from others, especially from family and friends [31]. Does Generation Z’s such tendency to seek information from others due to a lack of confidence in their own retrieval abilities lead to information avoidance behavior on social media? A meta-analysis of information avoidance behavior during the COVID-19 pandemic found that social psychological factors are less correlated with information avoidance behavior, and channel belief and information overload are the most powerful antecedent variables for information avoidance behavior, but there are generational differences [39]. For example, among the younger generation, perceived efficacy has a greater impact on information avoidance behavior than among the older generation. Researchers analyze this may be because young people’s beliefs and attitudes are easily influenced and changeable, which may lead to a stronger reaction and result in avoiding relevant risk information [39]. Other researchers have found that among young people, coping self-efficacy is related to information avoidance behavior, not general self-efficacy [40]. They further found that compared with participants who did not reflect on coping strategies, participants who reflected on positive coping strategies were less likely to avoid relevant health risk information [40].

2.3. Information Seeking vs. Avoidance on Government Social Media Platforms

At present, based on the uncertainty reduction theory and social information processing theory, both of which emphasize the role of social information in interpersonal interactions, a research team has found that expectations of quality for public information posted on social media can influence the public’s trust in the content and that content and quality trust both promote public recognition and participation in public administration. This relationship is influenced by the public’s familiarity with social media, the importance of interaction with the government, and the views of others [41].

Based on the deliberative policy theory, which emphasizes the crucial role of trust in public participation to enhance the effectiveness of public policies, some researchers have developed a decision-making model rooted in trust elements, highlighting trust’s important role in the public decision-making process [42]. Good governance of social media in government can affect public trust in the government [43], and increased public participation in government social media can more effectively demonstrate the efficacy of public service and policy implementation [44]. Therefore, how can good governance of government social media be achieved to attract active public participation? Some studies have found that when the public has information-seeking needs, the quality of information provided by government social media has a significant impact on public information behavior, such as whether government social media can provide sources of information needed by the public and the completeness and accuracy of the information [45]. Research also reveals that the perceived usefulness and ease of use of information provided by government social media are key factors that trigger public information behavior [46–48]. Perceived usefulness refers to the public’s belief that the information provided by government social media meets their needs and is valuable, and perceived ease of use refers to the convenience, flexibility, and user-friendliness of the information provided by government social media [46–48]. Moreover, there is a study which found that responsiveness is a key characteristic influencing the degree of citizen participation in government social media [49]. The quality of feedback and responses usually motivates citizens to participate more frequently in government social media [50]. These studies collectively suggest that government social media has the attributes of information technology applications, reflecting the government’s use of information technology with the aim of information disclosure and interaction with citizens [11].

Research on information avoidance behavior on government social media is scarce. From the perspective of public user experience, it has been found that public participation is lower on government social media that is perceived as less useful and less easy to use [51]. It is perceived that government social media cannot respond quickly to public needs, leading to low trust in government social media [51]. Some researchers have found through data from 75 local governments in 15 countries that an increase in the number of government posts on channels like Facebook and Twitter does not necessarily result in higher levels of citizen participation, which means that posting government information on social media does not necessarily promote citizen participation [52, 53]. Notably, some researchers have found a significant negative correlation between the number of government social media posts and public participation [54].

In terms of user experience on government social media, aside from studies focusing on the information technology attributes of government social media, some researchers believe that emotions also impact its use, for example, public satisfaction with the government, as a subjective emotion, can, to a certain extent, influence their participation behavior on government social media, with positive emotions more likely leading to digital participation [55]. Satisfaction within the user experience is a key factor for continued usage. In situations where satisfaction with the government is high, the public is more likely to engage in more information behavior on government social media [56]. An amount of past research has found that a nation’s human capital foundation can influence whether a government can better harness the positive impacts of e-governance. For instance, some studies have discovered a positive correlation between a country’s human capital and its level of e-governance, with different population characteristics affecting the frequency of public use of social media [57]. In this context, the public’s level of education and information technology literacy significantly influence the use and development of government social media [58, 59]. Consequently, sufficient attention should be given to the information behavior demonstrated on government social media by Generation Z, a cohort that has grown up alongside the development of the Internet.

3. Methodology

3.1. Grounded Theory

This study collected data through in-depth interviews and analyzed the results from Chinese Generation Z using government microblogging based on grounded theory. As an exploratory qualitative study, grounded theory uses empirical data through an iterative research process and is an inductive bottom-up research method [60]. The fundamental research logic of grounded theory involves collecting data through in-depth studies of natural situations and continuously comparing these data. Through abstract thinking, conceptual thinking, extraction, and induction, concepts and categories are summarized from the data, providing the foundation upon which theories are constructed.

3.2. Participants

In this study, based on the indicator of the number of Internet broadband access users in various cities in China from the “China Urban Statistical Almanac (2020),” stratified sampling was performed for Sina microblogging registrations according to the proportion of each province and city to the total. The method of obtaining users is as follows: obtaining root users—initially, user information was collected from popular “Super Topics,” hot microblogging comments, regional “Super Topics,” and location data from microblogging “Super Topics” across different provinces and cities in China; obtaining branch users—the validity of users was confirmed through specific microblogging content, and more user branches were obtained using microblogging’s “Related Recommendations” feature, achieving a tree-shaped user collection effect; verifying the interviewees—the users’ area, education level, birth year (Generation Z), and gender were verified through the personal information page retained when the user registered for microblogging, and users who had not posted microblogging content for three months or more were deleted. After the above checks, 109 interviewees were retained. The purpose and content of the present study were sent to the respondents through microblogging messages, seeking their willingness to participate. In the end, 31 respondents replied that they were willing to participate in this study and were included in the official interviews. All participants were interviewed anonymously. The demographic data of the participants is shown in Table 1.

3.3. Data Collection

Information among government microblogging was the main subject of research in this study. A semistructured questionnaire was utilized to conduct in-depth interviews with a representative sample, aiming to understand the causes and processes of Chinese Generation Z’s public information seeking and avoidance. This was followed by the compilation of interview data and the application of the grounded theory framework to construct a theory based on the results. The outline of the formal interview was based on a review of the relevant literature and condensed according to the specific requirements of the interview. Time and form of the formal interviews were determined based on the convenience of the interviewees, and interviews were conducted with online or by telephone. Interviews were exploring many aspects of government microblogging information behavior (see Table 2 for representative questions from the interview). When the information provided by the interviewee (basically) reached saturation, the two parties jointly decided to end the interview. After the interviews were completed, the interview data were compiled to form the data for textual analysis, two-thirds of which were randomly selected for focus coding and model construction, and the remaining one-third of which was used for a theoretical saturation test [61].

3.4. Data Analysis

3.4.1. Open Coding

Open coding of the interview data was conducted by a master’s student and a doctoral student. First, all data were labelled with the interviewees’ original words and analyzed sentence by sentence to extract and form initial concepts. The initial concepts repeated more than three times were then open coded based on the similarity of their attributes and dimensions to cluster the initial concepts into categories. Table 3 shows the initial concepts and categories formed by the open coding of government microblogging seeking and avoidance.

3.4.2. Axial Coding

Axial coding involves discovering and establishing the potential logical relationships of categories based on their causal relationship and similarity, thereby forming the main category and corresponding subcategories. Based on the analysis of the results in Table 3, the categories obtained in open coding appear to be intrinsically linked at the conceptual level. In this study, 17 categories were finally classified into six main categories according to their internal relations and logical relations. The connotations of these factors are shown in Table 4.

3.4.3. Selective Coding

Selective coding involves inducing and reintegrating the content formed by spindle coding, systematically linking it with other categories using a typical model, analyzing and verifying the linkage between them, and sorting out the “story line” to illustrate the relational conditions and behavioral phenomena of the model, thereby forming a theoretical framework. The present study connected the six main categories through the “story line” method. The main category relation structure and its connotations are shown in Table 5.

3.4.4. Saturation Test of Grounded Theory

The theoretical saturation test was conducted using one-third of the original interview data reserved in this study, which were analyzed and compared independently by two researchers with doctorates in the field and not involved in the study, who did not find any new concepts or categories. It was therefore inferred that the model reached theoretical saturation [61].

4. Results and Discussion

4.1. Results

The previous analyses reveal that the influence of government microblogging on information-seeking and avoidance behavior among Chinese Generation Z can be effectively explained by the model shown in Figure 1. Specifically, the factors influencing the government microblogging on information seeking and avoidance behavior can be summarized into the following six main categories: systematic seeking, heuristic seeking, defensive seeking, systematic avoidance, heuristic avoidance, and resource-limited avoidance, all of which are consistent with the model shown in Figure 1. Through the grounded analysis of government microblogging information avoidance and seeking among Chinese Generation Z, this study found that both are active forms of information-related behavior, and the factors influencing this behavior have both relative commonality and distinguishing attributes. The relative commonality is in terms of heuristic and systematic factors, which can influence active government microblogging information seeking and avoidance. The defensive factors of individuals elicited by government microblogging information can also lead Chinese Generation Z to engage in information seeking, while the resource-limited factors can lead them to engage in avoidance. It should be noted that the distinguishing attributes of the influencing factors for these two behaviors indicate that the defensive factor affects only information seeking but not avoidance, and the resource-limited factor only has an impact on avoidance but not on information seeking.

4.2. The Heuristic and Systematic Factors

Figure 1 presents a model built based on the information behavior on government microblogging, a specific type of social behavior. Among the existing research on the explanatory frameworks of social behavior, the heuristic-systematic model (HSM) has strong explanatory power in various scenarios. The heuristic-systematic model emphasizes the dual processes that humans go through when dealing with information, forming attitudes, and implementing decisions based on individual behavioral level [62]. The heuristic process refers to individuals relying on mental schemas to process information, which is a rapid, automated way of information processing, requiring less cognitive load. The systematic process refers to individuals carefully thinking and reasoning to form attitudes and make judgments, which consumes more cognitive resources [62]. The present study builds a model for the influencing factors of information-seeking and avoidance behavior in governmental microblogging. The active choice of information “seeking” or “avoiding” governmental microblogging is also the active choice of how to process information and make decisions. Existing research has found that there are multiple motivations for information seeking and avoidance under social media environment [63]. This study attempts to classify the main categories obtained from the grounded theory research method using the concepts of “systematic” and “heuristic” to clarify the multiple factors influencing the choices of whether to seeking or avoidance at government microblogging information by Generation Z in China.

The present study found that the information-seeking and avoidance behaviors of Generation Z in China towards government microblogging are both influenced by heuristic intuitive judgments. For the information-seeking behavior of government microblogging, intuitive rapid judgments may be influenced by factors such as personal preferences for government microblogging, emotional value, or following hot topics. As for the information avoidance behavior of government microblogging, intuitive rapid judgments may be based on clickbait titles, content layout, excessive length, and high redundancy. This finding is similar to existing research pointing out the significant influence of individual factors, information attributes, and information content on information-seeking and avoidance behavior [64]. Comparing the differences between these two conclusions of this study, it is found that the seeking behavior of government microblogging information relies more on the subjective factors of the Generation Z, such as personal preferences, emotional value, and hot topics, while the avoidance behavior of government microblogging information depends more on the characteristics of the information itself, such as the title, layout, length, and repetitiveness. Although both rely on intuitive judgments, the influencing factors and emphasis are different. The conclusions of this study have important significance for understanding how Chinese Generation Z obtain and avoid information on government microblogging. For government departments, they can optimize the release of microblogging information according to these research results to improve the efficiency and effectiveness of information dissemination. These are the following: (1) meeting user’s subjective needs—since the information-seeking behavior of government microblogging depends more on user’s subjective factors, government microblogging needs to meet the personal preferences and emotional needs of users as much as possible when posting information; for instance, experimental research had found that individual personality traits and emotional states had important roles in their information-seeking behavior [65]; existing research on information-seeking and avoidance behavior under the COVID-19 pandemic found that satisfying user’s subjective emotional needs had a significant impact on their information behavior [66]; (2) optimizing information quality and form—the information avoidance behavior of government microblogging depends more on the characteristics of the information itself, indicating that the form and quality of information have a great impact on the acceptance level of users. Therefore, government microblogging should carefully design the title, information layout, and content length and avoid publishing repetitive information, to reduce user avoidance behavior. The heuristic-systematic model points out that low user engagement leads to heuristic processing of information, and improving information quality can promote user’s cognitive processing of information, thereby enhancing user engagement [62]. Paying attention to the information quality of government microblogging will help promote public acceptance and participation in public information, which is an important goal of government microblogging governance. (3) In terms of integrating user’s subjective needs and information quality, social media platforms can understand user preferences through user behavior data analysis and then optimize information content and form based on these preferences. At the same time, social media platforms have various feedback mechanisms such as likes, shares, and retweets. By tracking and analyzing user feedback in real time, they can continuously adjust and improve the content and form of microblogging. The aforementioned methods may be effective in enhancing information-seeking behavior and reducing information avoidance behavior, but attention should be paid to user privacy protection issues in the implementation process [8].

The present study found that the information-seeking and avoidance behaviors of Chinese Generation Z towards government microblogging are both influenced by systematic judgment. For the information-seeking behavior of government microblogging, systematic processing may be influenced by task demand and expert recommendation factors; for the information avoidance behavior of government microblogging, systematic processing may be based on selective ignorance and terminological density factors. Both fall within the systematic path, meaning both types of information behaviors involve a more in-depth and logical way of information processing. However, comparing the differences in the “systematic” influencing factors of these two government microblogging information behaviors, it can be found that for the seeking behavior of government microblogging, the main influencing factors include task demand or expert recommendations. This suggests that when Generation Z have needs for specific tasks or goals, or when they receive advice from authorities or experts, they will search and process information more deeply. This represents a pathway in which social situational factors influence cognitive analysis. In contrast, the avoidance behavior of government microblogging is triggered by the individual’s evaluative judgment of their situation and cognitive status, such as selective ignorance and terminological density. This indicates that Generation Z might choose to actively avoid information after judging government microblogging information based on their current status. For Generation Z, social situational factors have an important impact on triggering active information search behavior, while their own situational evaluation plays an important role in triggering active avoidance behavior. This implies that for Generation Z, social factors might induce them to actively search for government microblogging information but not necessarily trigger them to actively avoid government microblogging information; the individual’s own situational evaluation has a significant influence on the avoidance behavior of government microblogging information, but their self-evaluation does not necessarily trigger them to actively search for government microblogging information. From this, it can be inferred that the characteristics of Generation Z’s information behavior may include a greater willingness to “view” information based on the opinions of others, while preferring to “not view” information based on their own opinions. The significance of the conclusions of this study lies in providing valuable insights for us to understand how Generation Z process information in a network environment. For governments and related agencies, understanding these information behavior patterns can help them optimize the content and form of governmental microblogs and enhance the acceptance and influence of information as shown in the following: (1) providing clear task direction or expert recommendation—since Generation Z’s information-seeking behavior is influenced by task demands or expert recommendations, government microblogging can provide clear task direction, such as specific action calls, or clear problem solutions; at the same time, expert views or recommendations can be introduced to help users acquire and process information more effectively; (2) reducing information complexity—as the avoidance behavior might be caused by the complexity or terminological density of the information, government microblogging needs to reduce the complexity of the information as much as possible. For instance, avoid using overly professional or complex terms, use more accessible language, or help young users better understand and analyze information through data visualization, case analysis, etc.

4.3. Theoretical and Practical Implications

Current research on information-seeking and avoidance behaviors tends to be conducted in isolation. Information seeking, for instance, is often divided into two primary strategies: browsing and searching. These strategies emphasize the role of user-environment interaction and sense-making, and their influence on information-seeking behaviors [65, 66]. In contrast, information avoidance is typically explored as a concept counter to information seeking [67], with extensive research underscoring the critical impact of selective exposure on avoidance behaviors [20, 68]. A notable discrepancy exists in the literature regarding the response to “uncertainty” in these behaviors. Some scholars posit that uncertainty can instigate information seeking as a means to alleviate the associated stress [69]. Conversely, others, drawing from uncertainty reduction theory and uncertainty management theory, argue that seeking behavior, while ostensibly reducing uncertainty, can paradoxically increase it by introducing new threats. For example, confirming a medical diagnosis might reduce uncertainty on one level but can simultaneously trigger emotional distress, thereby generating further uncertainty. In such cases, avoiding information can serve as a psychological safeguard for individuals [70, 71]. Conducting a comparative analysis to elucidate the underlying mechanisms of these two types of information behaviors is both essential and insightful, particularly as past research in this area is limited and predominantly focused on healthcare contexts. This study is aimed at bridging this gap by situating both information seeking and avoidance within the public sphere of the social media era. Specifically, it concentrates on the government microblogging behaviors of Generation Z, who are the digital natives in this social media era.

According to the results of this study, it can be seen that in the information processing of government microblogging, the information behavior of Generation Z may be influenced by both heuristic and systematic pathways. Importantly, these two pathways often coexist. Drawing from this study’s conclusions, Figure 2 presents a “Comparative Framework Diagram” that visualizes and contrasts information-seeking and avoidance behaviors in general and government social media contexts. This framework succinctly illustrates the differences and similarities identified in these behaviors across both platforms. In the model constructed by the present study, the defensive factor and resource-limited factor, respectively, represent two types of special influence factors where the systematic and heuristic pathways coexist. The defensive factor combines the influence paths of both heuristic and systematic, mainly reflected in information-seeking behavior carried out for the purpose of maintaining or supporting personal views, beliefs, or identities. There was research which revealed the information-seeking and avoidance behavior generated by the defensive motivation based on confirmation bias [63]. The resource-limited factor mainly affects the information avoidance behavior of Generation Z on government microblogging. When the public is unable or unwilling to process certain government microblogging information due to limited resources, they will avoid this information based on actual resource limitations, rather than intuitive judgments. This special situation is noteworthy, as the study found that even outside the systematic and heuristic information processing pathways, resource constraints can also become an important factor in determining information behavior. Especially for Generation Z, a generation more adapted to online life, faced with a richer and more exciting online world, how to attract more attention from this generation of young people under the premise of limited resources, and enhance their attractiveness, is a more complex and challenge task for the government microblogging. Accordingly, it is suggested that to more effectively design and disseminate government microblogging information, administrators of government microblogging should consider not only satisfying the personal needs of Generation Z but also their resource limitations, for example, providing information that aligns with the user’s views or identities, or simplifying information so that it can be effectively processed within limited time and energy.

4.4. Limitations and Future Directions

This study is a useful exploration in the research field with important theoretical and practical significance, but it also has limitations. Firstly, this study used a relatively limited sample of interviewees from the Generation Z population. A follow-up study could use a larger random sample from the target population and reevaluate the present study model. Secondly, existing research suggests that there may be a multistage, nonlinear process involved in information-seeking and avoidance behavior [8]. Based on the cross-sectional nature of the data, a longitudinal research design could be used in a future study in the context of the rapid development of mobile Internet technology to explain time-related effects, such as the evolution of government microblogging information seeking and avoidance among the Generation Z population over time. Thirdly, there are studies which have found that risk perception and risk situations have significant impacts on the public’s information-seeking and avoidance behavior [66, 72]. The content of information released by the government in crisis situations has a heterogeneous impact on the public’s cognition and attitudes, varying by gender, education level, and region, among other factors [73]. Future research could further explore whether there is domain-specificity in the public’s information behavior regarding social media in government. Finally, this study comparatively analyzed information seeking and avoidance based on the initiative of information-related behavior. However, in the use of social networks, intermittent discontinuance (the most common and typical negative behavior of network users) also has its own initiative: active abandonment or active reuse during usage. Research on this behavior has found that it has an important impact on improving network user experience and reducing user churn rate [74]. This behavior pattern can be incorporated into subsequent research to enrich model construction to further enhance the efficiency and accuracy of public information provision.

5. Conclusion

“Communication is the nerve of the government” [75]. If the reasons why the public actively chooses to search for or ignore the information released by the government are not better understood, then the recommendations for improving effective communication between the government and the public might be one-sided. In the era of social media, this could be even more important. This study focuses on Chinese Generation Z who have grown up with the development of social media and are extremely active on it, exploring the factors that influence their information-seeking and avoidance behaviors on government microblogging. This study found that both heuristic and systematic factors influence information-seeking and avoidance behaviors on government microblogging, but there are also intertwined factors that coexist. This study provides a new understanding framework for communication between the government and the Generation Z. It focuses on the information dissemination effects of the new generation of internet residents—Generation Z, as well as their information needs and information behavior characteristics. The research conclusions help to more comprehensively understand the information behavior of Generation Z on government microblogging and contribute to enhancing the communication effects of the government in the social media environment. This has important theoretical and practical significance.

Data Availability

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

Conflicts of Interest

The author declares that there is no conflict of interest regarding the publication of this article.

Acknowledgments

This research was supported by the National Natural Science Foundation of China (Grant No. 72074236) and the Adolescent Development Research Foundation of China (Grant No. 22JH013).

References

S. Stieglitz, M. Mirbabaie, B. Ross, and C. Neuberger, “Social media analytics – challenges in topic discovery, data collection, and data preparation,” International Journal of Information Management, vol. 39, pp. 156–168, 2018.
View at: Publisher Site | Google Scholar
A. L. Kavanaugh, E. A. Fox, S. D. Sheetz et al., “Social media use by government: from the routine to the critical,” Government Information Quarterly, vol. 29, no. 4, pp. 480–491, 2012.
View at: Publisher Site | Google Scholar
J. I. Criado, R. Sandoval-Almazan, and J. R. Gil-Garcia, “Government innovation through social media,” Government Information Quarterly, vol. 30, no. 4, pp. 319–326, 2013.
View at: Publisher Site | Google Scholar
P. McDermott, “Building open government,” Government Information Quarterly, vol. 27, no. 4, pp. 401–413, 2010.
View at: Publisher Site | Google Scholar
M. Graham and E. J. Avery, “Government public relations and social media: an analysis of the perceptions and trends of social media use at the local government level,” Public Relations Journal, vol. 7, no. 4, pp. 1–21, 2013.
View at: Google Scholar
X. Gao and J. Lee, “E-government services and social media adoption: experience of small local governments in Nebraska state,” Government Information Quarterly, vol. 34, no. 4, pp. 627–634, 2017.
View at: Publisher Site | Google Scholar
N. Sicherman, K. Law, P. H. Lipkin, G. Loewenstein, A. R. Marvin, and J. D. Buxbaum, “Information avoidance and information seeking among parents of children with ASD,” American Journal on Intellectual and Developmental Disabilities, vol. 126, no. 3, pp. 249–259, 2021.
View at: Publisher Site | Google Scholar
H. Sun, J. Li, Y. Cheng, X. Pan, L. Shen, and W. Hua, “Developing a framework for understanding health information behavior change from avoidance to acquisition: a grounded theory exploration,” BMC Public Health, vol. 22, no. 1, p. 1115, 2022.
View at: Publisher Site | Google Scholar
M. A. A. Alryalat, N. P. Rana, G. P. Sahu, Y. K. Dwivedi, and M. Tajvidi, “Use of social media in citizen-centric electronic government services,” International Journal of Electronic Government Research, vol. 13, no. 3, pp. 55–79, 2017.
View at: Publisher Site | Google Scholar
A. Q. H. Chung, P. Andreev, M. Benyoucef, A. Duane, and P. O’Reilly, “Where the shoe pinches: realizing dominant problems as an organizational social media business profile evolves,” International Journal of Information Management, vol. 41, pp. 33–49, 2018.
View at: Publisher Site | Google Scholar
L. Wang and X. Luo, “Understanding the interplay between government microblogs and citizen engagement: evidence from China,” Electronic Commerce Research, vol. 21, no. 2, pp. 487–520, 2021.
View at: Publisher Site | Google Scholar
M. Dimock, “Defining generations: where millennials end and Generation Z begins,” Pew Research Center, vol. 17, no. 1, pp. 1–7, 2019.
View at: Google Scholar
Y. J. Shi, Y. Gui, R. G. Huang, and W. Zheng, “Categorization, mechanism and influence of 'cocoons effect' in online media: an intermediary analysis based on social psychology survey of Chinese college students (2020),” Journalism & Communication, vol. 29, no. 5, pp. 43–59, 2022.
View at: Google Scholar
L. Y. Li and Y. C. Liang, “Analysis report on the questionnaire survey of media usage among Chinese youth,” Chinese Journalist, vol. 6, no. 582, pp. 48–56, 2022.
View at: Google Scholar
J. H. Yang and C. X. Wang, “The Young Netizens’Preference for Media Use and Political Trust,” Youth Studies, vol. 4, no. 439, pp. 1–10, 2021.
View at: Google Scholar
Z. F. Sun and Y. P. Zheng, “City government micro-blogging development and driving factors in China,” Journal of Public Management, vol. 18, no. 1, pp. 77–89, 2021.
View at: Google Scholar
W. Deng, X. L. Xu, T. Chen, and Y. Yang, “Research on the new media of government based on information sharing and use of smart city,” E-Government, vol. 10, no. 190, pp. 87–98, 2018.
View at: Google Scholar
F. Liu and S. L. Wang, “Audience participation and social influence of new media in government affairs,” Media, vol. 19, no. 312, pp. 53–55, 2019.
View at: Google Scholar
The People's Network Public Opinion Data Center, “China government micro-blogging report 2020,” 2021, https://weibo.com/5644433237/JEPJv2fln.
View at: Google Scholar
D. O. Case, L. M. Given, and J.-E. Mai, Looking for Information: A Survey of Research on Information Seeking, Needs, and Behavior, Emerald, Bingley, Fourth edition edition, 2016.
View at: Publisher Site
S. Erdelez and S. Makri, “Information encountering re-encountered,” Journal of Documentation, vol. 76, no. 3, pp. 731–751, 2020.
View at: Publisher Site | Google Scholar
H. Al-Samarraie, A. Eldenfria, and H. Dawoud, “The impact of personality traits on users’ information-seeking behavior,” Information Processing and Management, vol. 53, no. 1, pp. 237–247, 2017.
View at: Publisher Site | Google Scholar
M. Sanchiz, J. Chin, A. Chevalier, W. T. Fu, F. Amadieu, and J. He, “Searching for information on the web: impact of cognitive aging, prior domain knowledge and complexity of the search problems,” Information Processing and Management, vol. 53, no. 1, pp. 281–294, 2017.
View at: Publisher Site | Google Scholar
D. Nahl, “Measuring the affective information environment of web searchers,” Proceedings of the American Society for Information Science and Technology, vol. 41, no. 1, pp. 191–197, 2004.
View at: Publisher Site | Google Scholar
K. Athukorala, D. Głowacka, G. Jacucci, A. Oulasvirta, and J. Vreeken, “Is exploratory search different? A comparison of information search behavior for exploratory and lookup tasks,” Journal of the Association for Information Science and Technology, vol. 67, no. 11, pp. 2635–2651, 2016.
View at: Publisher Site | Google Scholar
E. J. Helsper and R. Eynon, “Digital natives: where is the evidence?” British Educational Research Journal, vol. 36, no. 3, pp. 503–520, 2010.
View at: Publisher Site | Google Scholar
Z. J. Lin and J. Wang, “A Study on the Types of Internet Preference of College Students in China,” Digital Library Forum, vol. 166, no. 3, pp. 36–42, 2018.
View at: Google Scholar
J. Ahn and L. A. Kahlor, “No regrets when it comes to your health: anticipated regret, subjective norms, information insufficiency and intent to seek health information from multiple sources,” Health Communication, vol. 35, no. 10, pp. 1295–1302, 2020.
View at: Publisher Site | Google Scholar
E. Roselina, T. Asmiyanto, and M. Andriany, “Health information-seeking behavior on the COVID-19 pandemic: social media usage by Gen Z in Jakarta, Indonesia,” Library Philosophy and Practice, pp. 1–7, 2021, article 4920.
View at: Google Scholar
M. Zhitomirsky-Geffet and M. Blau, “Cross-generational analysis of information seeking behavior of smartphone users,” Aslib Journal of Information Management, vol. 69, no. 6, pp. 721–739, 2017.
View at: Publisher Site | Google Scholar
A. Vaaler, L. Reiter, and A. E. Faulkner, “They seek, but do they find? Investigating the financial information-seeking behavior of college students,” College & Research Libraries, vol. 82, no. 2, pp. 267–285, 2021.
View at: Publisher Site | Google Scholar
P. Wilson, “Unused relevant information in research and development,” Journal of the American Society for Information Science, vol. 46, no. 1, pp. 45–51, 1995.
View at: Publisher Site | Google Scholar
C. C. Kuhlthau, “A principle of uncertainty for information seeking,” Journal of Documentation, vol. 49, no. 4, pp. 339–355, 1993.
View at: Publisher Site | Google Scholar
S. A. Rains and R. Tukachinsky, “An examination of the relationships among uncertainty, appraisal, and information-seeking behavior proposed in uncertainty management theory,” Health Communication, vol. 30, no. 4, pp. 339–349, 2015.
View at: Publisher Site | Google Scholar
B. T. Smith and R. Kouides, “The impact of information provided by consumer health information centers,” Journal of Hospital Librarianship, vol. 4, no. 3, pp. 53–62, 2004.
View at: Publisher Site | Google Scholar
L. A. Brannon, M. J. Tagler, and A. H. Eagly, “The moderating role of attitude strength in selective exposure to information,” Journal of Experimental Social Psychology, vol. 43, no. 4, pp. 611–617, 2007.
View at: Publisher Site | Google Scholar
S.-C. Huang, “Social information avoidance: when, why, and how it is costly in goal pursuit,” Journal of Marketing Research, vol. 55, no. 3, pp. 382–395, 2018.
View at: Publisher Site | Google Scholar
L. S. Connaway, T. J. Dickey, and M. L. Radford, “‘If it is too inconvenient I'm not going after it’: convenience as a critical factor in information-seeking behaviors,” Library & Information Science Research, vol. 33, no. 3, pp. 179–190, 2011.
View at: Publisher Site | Google Scholar
J. Li, “Information avoidance in the age of COVID-19: a meta-analysis,” Information Processing & Management, vol. 60, no. 1, article 103163, 2023.
View at: Publisher Site | Google Scholar
J. Hua and J. L. Howell, “Coping self-efficacy influences health information avoidance,” Journal of Health Psychology, vol. 27, no. 3, pp. 713–725, 2022.
View at: Publisher Site | Google Scholar
A. M. Aladwani and Y. K. Dwivedi, “Towards a theory of SocioCitizenry: quality anticipation, trust configuration, and approved adaptation of governmental social media,” International Journal of Information Management, vol. 43, pp. 261–272, 2018.
View at: Publisher Site | Google Scholar
D. N. Mah, D. M. Cheung, V. W. Y. Lam, A. Siu, Y. Sone, and K. Li, “Trust gaps in energy transitions: Japan’s National Deliberative Poll after Fukushima,” Environmental Innovation and Societal Transitions, vol. 39, pp. 249–269, 2021.
View at: Publisher Site | Google Scholar
M. Mansoor, “Citizens' trust in government as a function of good governance and government agency's provision of quality information on social media during COVID-19,” Government Information Quarterly, vol. 38, no. 4, article 101597, 2021.
View at: Publisher Site | Google Scholar
I. Mergel, “The social media innovation challenge in the public sector,” Information Polity, vol. 17, no. 3,4, pp. 281–292, 2012.
View at: Publisher Site | Google Scholar
S. Y. Hung, K. Chen, and Y. K. Su, “The effect of communication and social motives on E-government services through social media groups,” Behaviour & Information Technology, vol. 39, no. 7, pp. 741–757, 2020.
View at: Publisher Site | Google Scholar
A. Lee and Y. Levy, “The effect of information quality on trust in e-government systems' transformation,” Transforming Government: People, Process and Policy, vol. 8, no. 1, pp. 76–100, 2014.
View at: Publisher Site | Google Scholar
L. Chen and A. K. Aklikokou, “Determinants of E-government adoption: testing the mediating effects of perceived usefulness and perceived ease of use,” International Journal of Public Administration, vol. 43, no. 10, pp. 850–865, 2020.
View at: Publisher Site | Google Scholar
F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, vol. 13, no. 3, pp. 319–340, 1989.
View at: Publisher Site | Google Scholar
G. Lee and Y. H. Kwak, “An open government maturity model for social media-based public engagement,” Government Information Quarterly, vol. 29, no. 4, pp. 492–503, 2012.
View at: Publisher Site | Google Scholar
J. Y. Moon and L. S. Sproull, “The role of feedback in managing the Internet-based volunteer work force,” Information Systems Research, vol. 19, no. 4, pp. 494–515, 2008.
View at: Publisher Site | Google Scholar
M. Hutahaean, I. J. Eunike, and A. D. K. Silalahi, “Do social media, good governance, and public trust increase citizens’ e-government participation? Dual approach of PLS-SEM and fsQCA,” Human Behavior and Emerging Technologies, vol. 2023, Article ID 9988602, 19 pages, 2023.
View at: Publisher Site | Google Scholar
E. Bonsón, S. Royo, and M. Ratkai, “Citizens' engagement on local governments' Facebook sites. An empirical analysis: the impact of different media and content types in Western Europe,” Government Information Quarterly, vol. 32, no. 1, pp. 52–62, 2015.
View at: Publisher Site | Google Scholar
E. Bonsón, S. Royo, and M. Ratkai, “Facebook practices in Western European municipalities,” Administration & Society, vol. 49, no. 3, pp. 320–347, 2017.
View at: Publisher Site | Google Scholar
A. Haro-de-Rosario, A. Sáez-Martín, and M. del Carmen Caba-Pérez, “Using social media to enhance citizen engagement with local government: Twitter or Facebook?” New Media & Society, vol. 20, no. 1, pp. 29–49, 2018.
View at: Publisher Site | Google Scholar
S. M. Zavattaro, P. E. French, and S. D. Mohanty, “A sentiment analysis of U.S. local government tweets: the connection between tone and citizen involvement,” Government Information Quarterly, vol. 32, no. 3, pp. 333–341, 2015.
View at: Publisher Site | Google Scholar
A. Alawneh, H. Al-Refai, and K. Batiha, “Measuring user satisfaction from e-government services: lessons from Jordan,” Government Information Quarterly, vol. 30, no. 3, pp. 277–288, 2013.
View at: Publisher Site | Google Scholar
S. Krishnan, T. S. H. Teo, and J. Lymm, “Determinants of electronic participation and electronic government maturity: insights from cross-country data,” International Journal of Information Management, vol. 37, no. 4, pp. 297–312, 2017.
View at: Publisher Site | Google Scholar
S. R. Chohan and G. Hu, “Strengthening digital inclusion through e-government: cohesive ICT training programs to intensify digital competency,” Information Technology for Development, vol. 28, no. 1, pp. 16–38, 2022.
View at: Publisher Site | Google Scholar
C. A. Tremblay-Cantin, S. Mellouli, M. Cheikh-Ammar, and H. Khechine, “E-government service adoption by citizens: a literature review and a high-level model of influential factors,” Digital Government: Research and Practice, vol. 4, no. 1, pp. 1–24, 2023.
View at: Publisher Site | Google Scholar
J. M. Corbin and A. Strauss, “Grounded theory research: procedures, canons, and evaluative criteria,” Qualitative Sociology, vol. 13, no. 1, pp. 3–21, 1990.
View at: Publisher Site | Google Scholar
B. G. Glaser and A. L. Strauss, The Discovery of Grounded Theory: Strategies for Qualitative Research, Routledge, New York, 2017.
View at: Publisher Site
S. Chaiken, “Heuristic versus systematic information processing and the use of source versus message cues in persuasion,” Journal of Personality and Social Psychology, vol. 39, no. 5, pp. 752–766, 1980.
View at: Publisher Site | Google Scholar
S. Winter, M. J. Metzger, and A. J. Flanagin, “Selective use of news cues: a multiple-motive perspective on information selection in social media environments,” Journal of Communication, vol. 66, no. 4, pp. 669–693, 2016.
View at: Publisher Site | Google Scholar
K. Kim, “Information avoidance experience in the context of information seeking,” Culinary Science & Hospitality Research, vol. 28, no. 4, pp. 175–181, 2022.
View at: Google Scholar
H. K. Jach, C. G. DeYoung, and L. D. Smillie, “Why do people seek information? The role of personality traits and situation perception,” Journal of Experimental Psychology: General, vol. 151, no. 4, pp. 934–959, 2022.
View at: Publisher Site | Google Scholar
J. L. Ford, M. Douglas, and A. K. Barrett, “The role of pandemic fatigue in seeking and avoiding information on COVID-19 among young adults,” Health Communication, vol. 38, no. 11, pp. 2336–2349, 2023.
View at: Publisher Site | Google Scholar
B. Dervin, “Strategies for dealing with human information needs: information or communication?” Journal of Broadcasting & Electronic Media, vol. 20, no. 3, pp. 323–333, 1976.
View at: Publisher Site | Google Scholar
T. Jiang, “An exploratory study on social library system users' information seeking modes,” Journal of Documentation, vol. 69, no. 1, pp. 6–26, 2013.
View at: Publisher Site | Google Scholar
C. Atkin, Instrumental Utilities and Information Seeking, Sage, Oxford, 1973.
J. Chae, “Who avoids cancer information? Examining a psychological process leading to cancer information avoidance,” Journal of Health Communication, vol. 21, no. 7, pp. 837–844, 2016.
View at: Publisher Site | Google Scholar
D. E. Brashers, “Communication and uncertainty management,” Journal of Communication, vol. 51, no. 3, pp. 477–497, 2001.
View at: Publisher Site | Google Scholar
S. J. Hong and Y. Kim, “Testing risk information seeking and avoidance in the context of HPV vaccination: a comparison of disease risks and vaccine-related risks,” International Journal of Communication, vol. 16, pp. 4866–4889, 2022.
View at: Google Scholar
B. Liu, Z. Qin, and J. Zhang, “Cognitive bias in citizens’ perceptions of government performance in response to COVID-19: evidence from a large-scale survey experiment in China,” International Public Management Journal, vol. 25, no. 7, pp. 1072–1093, 2022.
View at: Publisher Site | Google Scholar
C. York and J. Turcotte, “Vacationing from Facebook: adoption, temporary discontinuance, and readoption of an innovation,” Communication Research Reports, vol. 32, no. 1, pp. 54–62, 2015.
View at: Publisher Site | Google Scholar
K. W. Deutsch, The Nerves of Government; Models of Political Communication and Control, Free Press of Glencoe, New York, 1963.

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