Framing genetically modified mosquitoes in the online news and Twitter: Intermedia frame setting in the issue-attention cycle

Twitter as research data Tools, costs, skill sets, and lessons learned

Scholars increasingly use Twitter data to study the life sciences and politics. However, Twitter data collection tools often pose challenges for scholars who are unfamiliar with their operation. Equally important, although many tools indicate that they offer representative samples of the full Twitter archive, little is known about whether the samples are indeed representative of the targeted population of tweets. This article evaluates such tools in terms of costs, training, and data quality as a means to introduce Twitter data as a research tool. Further, using an analysis of COVID-19 and moral foundations theory as an example, we compared the distributions of moral discussions from two commonly used tools for accessing Twitter data (Twitter's standard APIs and third-party access) to the ground truth, the Twitter full archive. Our results highlight the importance of assessing the comparability of data sources to improve confidence in findings based on Twitter data. We also review the major new features of Twitter's API version 2.

Examining the Intermedia Agenda Setting Effects amid the Changsheng Vaccine Crisis: A Computational Approach

Scholars have long questioned whether the traditional media effects approach can still be applied in the current digital media era, especially in the non-Western, state-regulated Chinese media environment. This study examines the intermedia agenda setting of traditional media sources and we-media sources in the WeChat Official Accounts through a computational look at the Changsheng Bio-technology vaccine (CBV) crisis. Utilizing LDA topic modeling and Granger causality analysis, results show that both traditional media and we-media (i.e., online news sources operated by individuals or collectives) focus more consistently on two frames, the news facts and the countermeasure and suggestion frames. Interestingly, the traditional media agenda impacts the we-media agenda under the news fact and the countermeasure and suggestion frames, while the we-media agenda influences the traditional media agenda under the moral judgment and causality background frames. Overall, our study demonstrates the mutual effects between the traditional media agenda and the we-media agenda. This study sheds light on the theoretical meaning of network agenda setting and extends its application to social media platforms in Eastern countries and health-related fields.

Communicating Scientific Uncertainty in an Age of COVID-19: An Investigation into the Use of Preprints by Digital Media Outlets

In this article, we investigate the surge in use of COVID-19-related preprints by media outlets. Journalists are a main source of reliable public health information during crises and, until recently, journalists have been reluctant to cover preprints because of the associated scientific uncertainty. Yet, uploads of COVID-19 preprints and their uptake by online media have outstripped that of preprints about any other topic. Using an innovative approach combining altmetrics methods with content analysis, we identified a diversity of outlets covering COVID-19-related preprints during the early months of the pandemic, including specialist medical news outlets, traditional news media outlets, and aggregators. We found a ubiquity of hyperlinks as citations and a multiplicity of framing devices for highlighting the scientific uncertainty associated with COVID-19 preprints. These devices were rarely used consistently (e.g., mentioning that the study was a preprint, unreviewed, preliminary, and/or in need of verification). About half of the stories we analyzed contained framing devices emphasizing uncertainty. Outlets in our sample were much less likely to identify the research they mentioned as preprint research, compared to identifying it as simply "research." This work has significant implications for public health communication within the changing media landscape. While current best practices in public health risk communication promote identifying and promoting trustworthy sources of information, the uptake of preprint research by online media presents new challenges. At the same time, it provides new opportunities for fostering greater awareness of the scientific uncertainty associated with health research findings.

The state of GMOs on social media An analysis of state-level variables and discourse on Twitter in the United States

This study analyzes the relationship between state-level variables and Twitter discourse on genetically modified organisms (GMOs). Using geographically identified tweets related to GMOs, we examined how the sentiments expressed about GMOs related to education levels, news coverage, proportion of rural and urban counties, state-level political ideology, amount of GMO-related legislation introduced, and agricultural dependence of each U.S. state. State-level characteristics predominantly did not predict the sentiment of the discourse. Instead, the topics of tweets predicted the majority of variance in tweet sentiment at the state level. The topics that tweets within a state focused on were related to state-level characteristics in some cases.

COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication

BACKGROUND

COVID-19, caused by SARS-CoV-2, has led to a global pandemic. The World Health Organization has also declared an infodemic (ie, a plethora of information regarding COVID-19 containing both false and accurate information circulated on the internet). Hence, it has become critical to test the veracity of information shared online and analyze the evolution of discussed topics among citizens related to the pandemic.

OBJECTIVE

This research analyzes the public discourse on COVID-19. It characterizes risk communication patterns in four Asian countries with outbreaks at varying degrees of severity: South Korea, Iran, Vietnam, and India.

METHODS

We collected tweets on COVID-19 from four Asian countries in the early phase of the disease outbreak from January to March 2020. The data set was collected by relevant keywords in each language, as suggested by locals. We present a method to automatically extract a time-topic cohesive relationship in an unsupervised fashion based on natural language processing. The extracted topics were evaluated qualitatively based on their semantic meanings.

RESULTS

This research found that each government's official phases of the epidemic were not well aligned with the degree of public attention represented by the daily tweet counts. Inspired by the issue-attention cycle theory, the presented natural language processing model can identify meaningful transition phases in the discussed topics among citizens. The analysis revealed an inverse relationship between the tweet count and topic diversity.

CONCLUSIONS

This paper compares similarities and differences of pandemic-related social media discourse in Asian countries. We observed multiple prominent peaks in the daily tweet counts across all countries, indicating multiple issue-attention cycles. Our analysis identified which topics the public concentrated on; some of these topics were related to misinformation and hate speech. These findings and the ability to quickly identify key topics can empower global efforts to fight against an infodemic during a pandemic.

Public perceptions of threats from mosquitoes in the U.S. using online media analytics

Mosquito-borne illnesses present a public health threat. This analysis quantifies general online mosquito media, and the Zika virus [ZIKV) specifically, from 7-20-2016 to 10-20-2018 in five U.S. geographies. The ZIKV sub-search comprised a shrinking share of online media about mosquitoes over time. Net sentiment, numerical scoring of search result positivity/negativity bounded between -100 and +100, was assessed. Mean net sentiment for the general mosquitoes search was -51; -55 for ZIKV. The ZIKV search revealed more variation in weekly net sentiment with a standard deviation of 14, compared to 10 for mosquitoes. Seventy-seven percent of the weeks had a net sentiment for the mosquito search that was more positive than the ZIKV search. For the 23% of the time the ZIKV search net sentiment was more positive than the general mosquito search, there were mentions of scientific advances, such as the potential for vaccine development associated with the post. Greater emphasis on public health threats from mosquitoes may be necessary to stimulate public action on mosquito-borne illness control. This analysis serves as an illustration of the potential for online/social media analysis to inform health officials of public interest/focus, and perhaps inform effective communication campaigns to combat public health threats.

Scientists vs laypeople: How genetically modified food is discussed on a Chinese Q&A website

This study examines messages contributed by scientists and laypeople to an online discussion about genetically modified food in China with the aim to understand whether and how scientists and laypeople apply different communication strategies with regard to framing, interaction features, and writing style. Both answers (N = 100) and comments (N = 2416) related to genetically modified food on Zhihu, the most popular social Q&A site in China, were analyzed. The analysis reveals that though there were no significant attitude differences between scientists and laypeople, the two groups tended to frame genetically modified food from quite different perspectives. Also, although scientist users were not perfect rationalists during online discussions, they were more likely to be both high-quality content contributors and active discussion facilitators.