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Climate change is a critical global problem that requires immediate action to mitigate its effects. In recent years, youth climate activists have mobilized worldwide protests to demand action, using social media platforms to communicate and broadcast their message. This study examines Greta Thunberg's rise to global prominence through an analysis of her first year and a half of Instagram posts from June 2018 to January 2020, including visual and textual elements. First, we explore how climate change is communicated on social media by youth activists, and then examine these concepts through the unique case of Thunberg’s Instagram. Then, through qualitative content analysis, this study elucidates her communication strategy by applying the concept of framing to unpack how she frames climate change as a moral and ethical issue, uses an emotional appeal of hope, and visually frames motivational collective action to mobilize her audience. Finally, we discuss the implications of our findings to explore the complexities of communicating climate change through social media and how Thunberg's activism on Instagram may provide an example for future generations.

We examined initial newspaper coverage of the COVID-19 outbreak (January–May 2020) in the United States and China, countries with contrasting media systems and pandemic experiences. We join the context-rich media systems literature and the longitudinal nature of the issue-attention literature to expand each by providing more system-level context for explaining how media cover an issue over time. U.S. coverage peaked later and stayed consistently high, while Chinese coverage was more variable. The most prominent topics in Chinese coverage were related to domestic outbreak response, while U.S. coverage focused on politics, highlighting how issue-attention cycles differ across countries.

When and how can researchers synthesize survey data with analyses of social media content to study public opinion, and when and how can social media data complement surveys to better inform researchers and policymakers? This paper explores how public opinions might differ between survey and social media platforms in terms of content and audience, focusing on the test case of opinions about autonomous vehicles. The paper first extends previous overviews comparing surveys and social media as measurement tools to include a broader range of survey types, including surveys that result from public deliberation, considering the dialogic characteristics of different social media, and the range of issue publics and marginalized voices that different surveys and social media forums can attract. It then compares findings and implications from analyses of public opinion about autonomous vehicles from traditional surveys, results of public deliberation, and analyses of Reddit posts, applying a newly developed computational text analysis tool. Findings demonstrate that social media analyses can both help researchers learn more about issues that are uncovered by surveys and also uncover opinions from subpopulations with specialized knowledge and unique orientations toward a subject. In light of these findings, we point to future directions on how researchers and policymakers can synthesize survey and social media data, and the corresponding data integration techniques, to study public opinion.

In a rapidly changing public health crisis such as COVID-19, researchers need innovative approaches that can effectively link qualitative approaches and computational methods. In this article, computational and qualitative methods are used to analyze survey data collected in March 2020 ( n = 2,270) to explore the content of persuasive messages and their relationship with self-reported health behavior—that is, social distancing. Results suggest that persuasive messages, based on participants’ perspectives, vary by gender and race and are associated with self-reported health behavior. This article illustrates how qualitative analysis and structural topic modeling can be used in synergy in a public health study to understand the public’s perception and behavior related to science issues. Implications for health communication and future research are discussed.

The COVID-19 pandemic unleashed a torrent of conspiracy theories across different social media platforms. Parallel to this conspiracy wave was a heightened sense of nationalism, which manifested through both in-group solidarity and perceived out-group threats. In this study, we examine how individuals’ use of government social media to gather political information correlated with nation-related conspiracy beliefs during the pandemic. Data were collected from 745 subjects in China and analyzed through path analyses, which allowed us to examine the direct association with political information consumption from government social media and the indirect association with nationalism on conspiracy beliefs. The results indicated that the use of government social media to gather political information was associated with greater beliefs in nation-variant COVID-19 conspiracies, both directly and through different mediations of nationalism. Our findings highlight the importance of examining government social media use and how nationalism can have differentiated mediation effects on beliefs in conspiracy theories.

Gene editing in the environment must consider uncertainty about potential benefits and risks for different populations and under different conditions. There are disagreements about the weight and balance of harms and benefits. Deliberative and community-led approaches offer the opportunity to engage and empower diverse publics to co-create responses and solutions to controversial policy choices in a manner that is inclusive of diverse perspectives. Stories, understood as situated accounts that reflect a person's life experiences, can enable the articulation of nuanced perspectives, diversify how perspectives are communicated, encourage wider participation, open dominant perspectives to challenge, and invite participants to assess appropriate empathy and precaution in collective positions. An emphasis on storytelling in deliberations on gene editing of organisms emphasizes carefully designed recruitment and facilitation to support hearing from a range of perspectives, including those that present a different set of assumptions than those that may be held by experts or other stakeholders, among these, consideration of how to understand our relationships to nature.

Citizen participatory budgeting (CPB) is a mechanism to enhance governance, particularly regarding accountability and responsiveness. The growing literature on the topic, however, has not addressed the participation effectiveness of CPB in developing countries. Drawing mainly from first-hand data, this study examines the participation effectiveness of the recent CPB reform in Yanjin, a poor county in southwestern China. It is found that with a well-designed participatory mechanism, citizen representatives of the Yanjin County have effectively participated in public budgeting. This study, therefore, has important implications for other localities in China as well as other developing countries that are interested in using CPB to improve local governance.

Deliberative exercises may reinvigorate civic life by building citizens’ capacity to engage in other types of civic activities. This study examines members of a citizens’ panel ( n = 56) who participated in a 6-day deliberative event on climate change and energy transition in Edmonton, Alberta (Canada), in 2012. We compared panellists’ civic engagement, political interest, and political knowledge with those of the general population using a concurrent random digit dialling survey conducted 2.5 years after the event ( n = 405). Panellists are more likely to talk about politics, and volunteer in the community compared to their counterparts in the larger population. Examining three points in time, we reveal a trajectory of increasing political knowledge and civic engagement. Finally, we examine the mechanisms that mobilize panellists into greater civic engagement. This study illustrates how deliberative events could strengthen engagement in civic and political life, depending on the degree to which deliberation was perceived to have occurred.

Social media have become popular channels for sharing and discussing science issues. Drawing from the classic communication theory, Public Arena Model, this paper examines how issue entrepreneurs influenced the Chinese public's cognition of GMO, especially the role of celebrities and scientists in controversial science communication. To answer this question, we used the structural topic modeling method to examine public discussion about GMO on a popular Q&A site in China (Zhihu) from 2014 to 2019 (N=40,101). In study 1, we investigated what the major themes of public discourse are about GMO and the evolution of these themes in general. In study 2, we investigated public discourse in a more specific context, an iconic event in China's GMO history, a debate between a TV celebrity and a scientist, to examine how two major issue entrepreneurs influenced what and how the public deliberated GMO\@. We found that the issue entrepreneurs' debate increased public discussion on the ‘science communication’ aspect of GMO yet decreased public discussion on the ‘science’ of GMO. Supporters of different entrepreneurs are divided in their attitudes and rhetoric toward GMO. These findings shed new light on how social media is a digital embodiment of the public arena where public deliberation about controversial science occur and evolve.

With the rise of digital media, conspiracy theories infamous for their emotional manipulation have challenged science epistemology and democratic discourse. Despite extensive literature on misinformation and the role of emotion in persuasion, less is understood about how emotion is used in conspiracy and debunking messages on video platforms and the impact of emotional framing on public engagement with science on social media. Our article fills this gap by analyzing thousands of YouTube videos that propagate or debunk COVID-19 conspiracy theories from March to May 2020. We found that conspiracy and debunking videos used the emotions of trust and fear differently depending on the issue framing of the conspiracy. Our article also reveals a dilemma facing debunking messages—when debunking videos used more trust-related emotions, these videos received more likes yet fewer views. These findings shed new light on the role of emotion on user engagement with misinformation and its correction on digital platforms.

The novel coronavirus disease (COVID-19) pandemic is a global threat presenting health, economic and social challenges that continue to escalate. Meta-population epidemic modeling studies in the susceptible-exposed-infectious-removed (SEIR) style have played important roles in informing public health and shaping policy making to mitigate the spread of COVID-19. These models typically rely on a key assumption on the homogeneity of the population. This assumption certainly cannot be expected to hold true in real situations; various geographic, socioeconomic and cultural environments affect the behaviors that drive the spread of COVID-19 in different communities. What’s more, variation of intra-county environments creates spatial heterogeneity of transmission in different sub-regions. To address this issue, we develop a new human mobility flow-augmented stochastic SEIR-style epidemic modeling framework with the ability to distinguish different regions and their corresponding behavior. This new modeling framework is then combined with data assimilation and machine learning techniques to reconstruct the historical growth trajectories of COVID-19 confirmed cases in two counties in Wisconsin. The associations between the spread of COVID-19 and human mobility, business foot-traffic, race & ethnicity, and age-group are then investigated. The results reveal that in a college town (Dane County) the most important heterogeneity is spatial, while in a large city area (Milwaukee County) ethnic heterogeneity becomes more apparent. Scenario studies further indicate a strong response of the spread rate on various reopening policies, which suggests that policymakers may need to take these heterogeneities into account very carefully when designing policies for mitigating the spread of COVID-19 and reopening.

People are increasingly exposed to science and political information from social media. One consequence is that these sites play host to “alternative influencers,” who spread misinformation. However, content posted by alternative influencers on different social media platforms is unlikely to be homogenous. Our study uses computational methods to investigate how dimensions we refer to as audience and channel of social media platforms influence emotion and topics in content posted by “alternative influencers” on different platforms. Using COVID-19 as an example, we find that alternative influencers’ content contained more anger and fear words on Facebook and Twitter compared to YouTube. We also found that these actors discussed substantively different topics in their COVID-19 content on YouTube compared to Twitter and Facebook. With these findings, we discuss how the audience and channel of different social media platforms affect alternative influencers’ ability to spread misinformation online.

We propose a novel signal multiplexing and detection method for multiple-input multiple-output (MIMO) communication systems, especially when the number of transmitting and receiving antennas is limited. Inspired by the idea of Compressive Sensing (CS) which can recover a given signal vector from a vector of measurements with less dimensions, our proposed CS-based multiplexing scheme can deliver a modulated data vector with length l via a MIMO system with fewer transmitting/receiving antennas than l , offering higher multiplexing gain. On the receiving side, our proposed detection scheme has two steps, which resort the BCS algorithm and a Deep-Learning algorithm to recover the original modulated data vector. Analytical and simulation results show that the proposed multiplexing and detection method can achieve larger multiplexing gain while reserving good bit error rate (BER), offering a novel research paradigm to improve the utility rate of multiple antennas.

This paper synthesizes the efforts of an interdisciplinary, University-convened communication task force in the U.S. that used science communication theory to develop an effective strategy during the early stages of the COVID-19 pandemic. We outline recommendations for researchers and practitioners who are, or are interested in, implementing theory-based communication practices while describing how we dealt with the unforeseen realities we faced. Overall, we recommend that effective public health and science communication should be based on theory and formative evaluation while relying on established infrastructure, real-time data, a deep understanding of intended target audiences, and intentional coordination with community partners.

While crowdsourcing is an increasingly common method of open-government practices to strengthen participatory democracy, its impact on governance is unclear. Using data from a crowdsourced city-pla...

Paralleling very visible debates in psychology, some parts of the communication field have recently pushed for a wholesale endorsement of the principles of open science and its practices, including a particular focus on replicability and reproducibility as quality criteria. Unfortunately, these discussions have been plagued by a set of at least 3 interrelated problems: A lack of conceptual clarity when defining open science-related challenges to communication scholarship; the irony of using intuition rather than evidence when trying to improve communication science; and our field’s surprising lack of attention to nonreplicability in social media data as one of our field’s most rapidly growing data sources. In response to these problem areas, we argue that communication as a field proceed empirically as it applies open science practices to different subfields in communication and end our essay with pathways forward for a science of open (communication) science.

This paper studies conspiracy and debunking narratives about the origins of COVID-19 on a major Chinese social media platform, Weibo, from January to April 2020. Popular conspiracies about COVID-19 on Weibo, including that the virus is human-synthesized or a bioweapon, differ substan-tially from those in the United States. They attribute more responsibility to the United States than to China, especially following Sino-U.S. confrontations. Compared to conspiracy posts, debunking posts are associated with lower user participation but higher mobilization. Debunking narratives can be more engaging when they come from women and influencers and cite scientists. Our find-ings suggest that conspiracy narratives can carry highly cultural and political orientations. Correc-tion efforts should consider political motives and identify important stakeholders to reconstruct international dialogues toward intercultural understanding.

This paper studies conspiracy and debunking narratives about COVID-19 origination on a major Chinese social media platform, Weibo, from January to April 2020. Popular conspiracies about COVID-19 on Weibo, including that the virus is human-synthesized or a bioweapon, differ substantially from those in the US. They attribute more responsibility to the US than to China, especially following Sino-US confrontations. Compared to conspiracy posts, debunking posts are associated with lower user participation but higher mobilization. Debunking narratives can be more engaging when they come from women and influencers and cite scientists. Our findings suggest that conspiracy narratives can carry highly cultural and political orientations. Correction efforts should consider political motives and identify important stakeholders to reconstruct international dialogues toward intercultural understanding.

Empowering ordinary citizens with the capacity to deliberate is a core issue in science communication. Despite growing deliberative practices in developed nations, it is significantly less understood how public deliberation can happen among populations who live with limited educational resources and poor urban infrastructure in developing countries. This article studied a case of a well-designed deliberation method, Deliberative Poll, in Tamale, Ghana. I analyzed the stimulus information video and thousands of speech acts from deliberation transcripts to examine how expertise was used and what was deliberated in public dialogue. A broad range of expertise and interests were represented. Participants had thoughtful discussions on complex policy issues and their discussion results were considered by local policymakers. This article contributes to our understanding of how to effectively foster public deliberation among populations in the Global South and measure the nuances of expertise and public reasoning on science.

Supplemental material, K_Chen_supplemental_material for How deliberative designs empower citizens’ voices: A case study on Ghana’s deliberative poll on agriculture and the environment by Kaiping Chen in Public Understanding of Science

The recent decade has witnessed a resurgence of nationalism across the world, which is evident in numerous sites such as offline protests to online discourse, from politics to science. Anecdotal evidence shows that nationalism narratives have become prevalent in dis(mis)information campaigns. The challenges posed by nationalism and misinformation have become more salient in the context of an increasingly fragmented, high-choice media environment. However, researchers know little about how one’s pride in their national identity and out-group derogation can influence one’s perception of misinformation and the role of media exposure in moderating the relationship between one’s nationalist attitudes and misinformation. Moreover, despite extensive studies on nationalism and misinformation in political communication, the role of nationalism in one’s processing of science misinformation is still not well-understood, which poses a critical challenge for informed citizenship. This paper theorizes the relationship between misinformation and nationalism in communication research by distinguishing various dimensions of nationalism and how they affect one’s belief in various types of science misinformation. Surveying a diverse sample of participants across mainland China (N=984), we find that pride in national identity does not always increase the misperception of science knowledge. However, out-group derogation substantially boosts one’s misperception of factual knowledge of science, epistemic knowledge of science, and conspiratorial thinking. Interestingly, out-group derogation also decreases certainty perception of misinformation. We also find that people’s exposure to social and traditional media strengthens the impact of out-group derogation on misperception of science knowledge. These findings suggest that nationalism is a central critical vector for misinformation to affect knowledge beyond the domain of political communication. Our findings provide important suggestions for fostering an informed citizenry and correcting misperceptions in a high-choice media environment.

A prerequisite for the durability of authoritarian regimes as well as their effective governance is the regime’s ability to gather reliable information about the actions of lower-tier officials. Allowing public participation in the form of online complaints is one approach authoritarian regimes have taken to improve monitoring of lower-tier officials. In this paper, we gain rare access to internal communications between a monitoring agency and upper-level officials in China. We show that citizen grievances posted publicly online that contain complaints of corruption are systematically concealed from upper-level authorities when they implicate lower-tier officials or associates connected to lower-tier officials through patronage ties. Information manipulation occurs primarily through omission of wrongdoing rather than censorship or falsification, suggesting that even in the digital age, in a highly determined and capable regime where reports of corruption are actively and publicly voiced, monitoring the behavior of regime agents remains a challenge.

Diversity in knowledge production is a core challenge facing science communication. Despite extensive works showing how diversity has been undermined in science communication, little is known about to what extent social media augments or hinders diversity for science communication. This article addresses this gap by examining the profile and network diversities of knowledge producers on a popular social media platform—YouTube. We revealed the pattern of the juxtaposition of inclusiveness and segregation in this digital platform, which we define as “segregated inclusion.” We found that diverse profiles are presented in digital knowledge production. However, the network among these knowledge producers reveals the rich-get-richer effect. At the intersection of profile and network diversities, we found a decrease in the overall profile diversity when we moved toward the center of the core producers. This segregated inclusion phenomenon questions how inequalities in science communication are replicated and amplified in relation to digital platforms.

While national and local governments increasingly deploy crowdsourcing in lawmaking as an open government practice, it remains unclear how crowdsourcing creates value when it is applied in policyma...

The development of computational data science techniques in natural language processing and machine learning algorithms to analyze large and complex textual information opens new avenues for studying the interaction between economics and politics. We apply these techniques to analyze the design of financial regulatory structure in the United States since 1950. The analysis focuses on the delegation of discretionary authority to regulatory agencies in promulgating, implementing, and enforcing financial sector laws and overseeing compliance with them. Combining traditional studies with the new machine learning approaches enables us to go beyond the limitations of both methods and offer a more precise interpretation of the determinants of financial regulatory structure.

This theoretical viewpoint paper presents a new perspective on urban governance in an information age. Smart city governance is not only about technology but also about re-organizing collaboration between a variety of actors. The introduction of new tools for open collaboration in the public domain is rapidly changing the way collaborative action is organized. These technologies reduce the transaction costs for massive collaboration dramatically and thus facilitate new forms of collaboration that we could call ‘open governance’: new innovative forms of collective action aimed at solving complex public policy issues, contributing to public knowledge, or replacing traditional forms of public service provision. These innovative open and collaborative organisational forms in cities seem to point towards not only a wide variety of digitally connected actors but also to a fundamentally different and more invisible role of government in these arrangements. We argue that the recently emerging paradigm of New Public Governance (NPG) (Osborne 2010) also fails to capture the dynamics of open governance since it does not acknowledge the emergent – pop-up – character of the new collaborations; neither does it present an understanding of massive individualized collaboration in cities. This paper aims to theoretically and empirically explore the core elements and the underlying socio-technical developments of this new Open Governance (OG) paradigm and compare and contrast OG with existing governance paradigms. Based on illustrative real-life cases, we will argue that we need a new paradigm that is better capable of explaining these emerging innovative forms of governing cities. We will argue that this requires an understanding of governance as a platform that facilitates an urban ecosystem. By connecting new insights from studies on digital governance to the debate about governance paradigms, this paper results in a set crucial empirical and normative questions about governance of cities and also in guidelines for urban governance that builds upon the rich, emerging interactions in cities that are facilitated by new technologies.

The Internet has provided more opportunities for the expression of diverse viewpoints. However, it also contributes to the rise of incivility and polarization. This paper speaks to this debate by showing that the network structure of how conversations happen affect the quality of the discourse. Using the reddit/politics 2014 data to examine this relationship, we find that 1) when the interaction among the users is more extensive, their discourses tend to be more emotionally polarized but more diverse as well and 2) conversations that follow more of power law distribution are also more emotionally polarized.

Understanding how individuals perceive the barriers and benefits of precautionary actions is key for effective communication about public health crises, such as the COVID-19 outbreak. This study used innovative computational methods to analyze 30,000 open-ended responses from a large-scale survey to track how Wisconsin (U.S.A.) residents' perceptions of the benefits of and barriers to performing social distancing evolved over a critical time period (March 19th to April 1st, 2020). Initially, the main barrier was practical related, however, individuals later perceived more multifaceted barriers to social distancing. Communication about COVID-19 should be dynamic and evolve to address people's experiences and needs overtime.