Leona Yi-Fan Su

Building Buzz: (Scientists) Communicating Science in New Media Environments

Public communication about science faces novel challenges, including the increasing complexity of research areas and the erosion of traditional journalistic infrastructures. Although scientists have traditionally been reluctant to engage in public communication at the expense of focusing on academic productivity, our survey of highly cited U.S. nano-scientists, paired with data on their social media use, shows that public communication, such as interactions with reporters and being mentioned on Twitter, can contribute to a scholar’s scientific impact. Most importantly, being mentioned on Twitter amplifies the effect of interactions with journalists and other non-scientists on the scholar’s scientific impact.

Inequalities in Scientific Understanding: Differentiating Between Factual and Perceived Knowledge Gaps

This study assesses two key types of knowledge assessments, factual and perceived knowledge, in the study of knowledge gaps. In addition, we distinguish between communication channels in exploring the phenomenon, examining nanotechnology knowledge gaps based on levels of attention to traditional media, science blog use, and the frequency of interpersonal discussion. Using regression analysis, we find that how researchers measure knowledge can significantly affect the discovery of gaps. We also find differential effects based on communication channels, including evidence that the direction of perceived gaps in knowledge can be reversed as media consumption increases. Implications of these findings are discussed.

Analyzing public sentiments online: combining human- and computer-based content analysis

ABSTRACT Recent technological developments have created novel opportunities for analyzing and identifying patterns in large volumes of digital content. However, many content analysis tools require researchers to choose between the validity of human-based coding and the ability to analyze large volumes of content through computer-based techniques. This study argues for the use of supervised content analysis tools that capitalize on the strengths of human- and computer-based coding for assessing opinion expression. We begin by outlining the key methodological issues surrounding content analysis as performed by human coders and existing computational algorithms. After reviewing the most popular analytic approaches, we introduce an alternative, hybrid method that is aimed at improving reliability, validity, and efficiency when analyzing social media content. To demonstrate the usefulness of this method, we track nuclear energy- and nanotechnology-related opinion expression on Twitter surrounding the Fukushima Daiichi accident to examine the extent to which the volume and tone of tweets shift in directions consistent with the expected external influence of the event. Our analysis revealed substantial shifts in both the volume and tone of nuclear power-related tweets that were consistent with our expectations following the disaster event. Conversely, there was decidedly more stability in the volume and tone of tweets for our comparison issue. These analyses provide an empirical demonstration of how the presented hybrid method can analyze defined communication sentiment and topics from large-scale social media data sets. The implications for communication scholars are discussed.

Science News Consumption Patterns and Their Implications for Public Understanding of Science

Due to changes in the media landscape, the vast majority of the public now depends on a mix of media formats for science news. This study analyzes audiences’ repertoires of science media consumption, and the effect of these consumption patterns on public understanding of science. We also profile those who rely on a mix of online-only sources and traditional media for science news. Our findings indicate that primarily relying on online-only sources is positively associated with a higher understanding of science, even when pertaining to respondents’ level of education and scientific training in the past.

Information-Sharing and Community-Building: Exploring the Use of Twitter in Science Public Relations

Social media have given rise to new opportunities for science organizations to communicate with the public. Building on theories of science communication and public relations, this study examined scientific institutions’ use of Twitter for one-way and two-way communication in connection with science festivals over the period 2012 to 2015, using NanoDays as a case study. It identified three communicative functions of tweets by organizations—information, participation, and community—with most tweets being informational and containing hyperlinks. Nevertheless, longitudinal analyses indicated that organizations have increasingly incorporated community-building practices such as hashtags. Findings help clarify how social media engender science communication paradigms.

Tweeting disaster: an analysis of online discourse about nuclear power in the wake of the Fukushima Daiichi nuclear accident

Of all the online information tools that the public relies on to collect information and share opinions about scientific and environmental issues, Twitter presents a unique venue to assess the spontaneous and genuine opinions of networked publics, including those about a focusing event like the Fukushima Daiichi nuclear accident following the 2011 Tohoku earthquake and tsunami. Using computational linguistic algorithms, this study analyzes a census of English-language tweets about nuclear power before, during, and after the Fukushima nuclear accident. Results show that although discourse about the event may have faded rapidly from the news cycle on traditional media, it evoked concerns about reactor safety and the environmental implications of nuclear power, particularly among users in U.S. states that are geographically closer to the accident site. Also, while the sentiment of the tweets was primarily pessimistic about nuclear power weeks after the accident, overall sentiment became increasingly neutral and uncertain over time. This study reveals there is a group of concerned citizens and stakeholders who are using online tools like Twitter to communicate about global and local environmental and health risks related to nuclear power. The implications for risk communication and public engagement strategies are discussed. Abstract

Policy decision-making, public involvement and nuclear energy: what do expert stakeholders think and why?

Despite renewed interest in involving the general public in energy and environmental policymaking, little is known about how policy stakeholders with specialized knowledge and extensive experiences perceive the value of such activity. This study seeks to explore how a series of social, cognitive, and communication factors relates to expert stakeholders’ attitudes toward public involvement in energy policymaking. Using data from a national survey of key stakeholders involved in making high-level decisions on nuclear energy, we find governmental stakeholders are more likely to think public involvement is important when perceiving public opinion as being split. Scientists and non-profit stakeholders, however, attach high-level importance to public involvement regardless of their perception of public opinion. Additionally, the perception of a divided public for the issue of nuclear energy is driven by frequent use of online media. Perceived importance of a salient media agenda – the economics of nuclear facil...

Scientists Joking on Social Media: An Empirical Analysis of #overlyhonestmethods:

The #overlyhonestmethods trend on Twitter is a space used by many scientists to peel back the curtain on their work and share observations and insights into the research world. We employ computer-assisted coding to assess the themes of 58,125 #overlyhonestmethods posts from January 7, 2013—the hashtag’s inception—to January 6, 2016. We additionally manually code a random sample of the census of tweets to evaluate the types of humor employed, as well as the targets of jokes and exclusivity of language. We offer analyses of this self-deprecating, insider conversation and an assessment of the associated ethical implications.

Uncivil and personal? Comparing patterns of incivility in comments on the Facebook pages of news outlets:

Social media and its embedded user commentary are playing increasingly influential roles in the news process. However, researchers’ understanding of the social media commenting environment remains limited, despite rising concerns over uncivil comments. Accordingly, this study used a supervised machine learning–based method of content analysis to examine the extent and patterns of incivility in the comment sections of 42 US news outlets’ Facebook pages over an 18-month period in 2015–2016. These outlets were selected as being broadly representative of national, local, conservative, and liberal-news media. The findings provide the first empirical evidence that both the level and the targets of incivility in the comments posted on news outlets’ Facebook pages vary greatly according to such entities’ general type and ideological stance.

The influence of temperature on #ClimateChange and #GlobalWarming discourses on Twitter

Research suggests non-experts associate different content with the terms “global warming” and “climate change.” We test this claim with Twitter content using supervised learning software to categorize tweets by topic and explore differences between content using “global warming” and “climate change” between 1 January 2012 and 31 March 2014. Twitter data were combined with temperature records to observe the extent to which temperature was associated with Twitter discussions. We then used two case studies to examine the relationship between extreme temperature events and Twitter content. Our findings underscore the importance of considering climate change communication on social media. Abstract