ABSTRACT
The corona pandemic, like many other crises, caused a high demand for information among citizens. At the same time, a large amount of science information was disseminated through various channels, often includ¬ing social media. Thus, new opportunities to observe users arose for research on information behaviour, but also new methodological challenges to relate this behaviour to other consumption of news and science communication. This paper presents a mixed-methods approach that combines a survey on the use and evaluation of information sources with observations from a user study. For the latter, result lists of various web and video searches were used in an ex¬periment as a starting point to determine selection methods and quality criteria for science communication. Both meth¬odological approaches showed that the reliability and fa¬miliarity of a source play a dominant role in selection de¬cisions. © 2023 De Gruyter Saur. All rights reserved.
ABSTRACT
The corona pandemic, like many other crises, caused a high demand for information among citizens. At the same time, a large amount of science information was disseminated through various channels, often including social media. Thus, new opportunities to observe users arose for research on information behaviour, but also new methodological challenges to relate this behaviour to other consumption of news and science communication. This paper presents a mixed-methods approach that combines a survey on the use and evaluation of information sources with observations from a user study. For the latter, result lists of various web and video searches were used in an experiment as a starting point to determine selection methods and quality criteria for science communication. Both methodological approaches showed that the reliability and familiarity of a source play a dominant role in selection decisions.
ABSTRACT
During the COVID-19 pandemic, large amounts of data have been generated in social media, for the processing of which automatic methods such as topic modeling become necessary. In various studies, this has already provided fundamental insights into the topics discussed in different geographical regions and at different points in time. Other parameters such as authorship have also taken into account for additional differentiation, or individual sub-areas of corona discourse have been considered separately. Another interesting subfield here is science communication, whose importance for successful pandemic response is often mentioned. Here, too, topic modeling can serve as an approach in the future to examine science communication in the COVID-19 pandemic and its effects in more detail.