All author's publications are listed below.
Inequalities in scientific knowledge are the subject of increasing attention, so how factual science knowledge is measured, and any inconsistencies in said measurement, is extremely relevant to the field of science communication. Different operationalizations of factual science knowledge are used interchangeably in research, potentially resulting in artificially comparable knowledge levels among respondents. Here, we present data from an experiment embedded in an online survey conducted in the United States (N = 1,530) that examined the distribution of factual science knowledge responses on a 3- vs. 5-point response scale. Though the scale did not impact a summative knowledge index, significant differences emerged when knowledge items were analyzed individually or grouped based on whether the correct response was “true” or “false.” Our findings emphasize the necessity for communicators to consider the goals of knowledge assessment when making operationalization decisions.
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.
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.