Researching the virtual: A framework for reflexivity in qualitative social media research

Understanding public perceptions in social media responses to posts about acute severe hepatitis of unknown etiology in Indonesia: a qualitative study

BACKGROUND

Acute Severe Hepatitis of Unknown Etiology (ASHUE) emerged as a new global outbreak in Indonesia early May 2022, coinciding with the COVID-19 pandemic. This study aimed to understand public reactions and responses to the emergence of ASHUE Indonesia and to Government-led disease prevention responses. Understanding how the public perceived government-led preventive messaging about the hepatitis outbreak is crucial to controlling viral spread - particularly given the rapid and unforeseen emergence of ASHUE coincided with COVID-19 and public trust in the Indonesian Government to manage health outbreaks was already tenuous.

METHODS

Social media users' responses to information disseminated via Facebook, YouTube, and Twitter were analyzed to understand public perceptions about ASHUE outbreak and their attitudes toward Government-led prevention measures. Data were extracted on a daily basis from 1st May 2022 to 30th May 2022 and analyzed manually. We inductively generated the codes, from which we formed a construct and then grouped to identify themes.

RESULTS

A total of 137 response comments collected from 3 social medial platforms were analyzed. Of these, 64 were from Facebook, 57 were from YouTube, and 16 were from Twitter. We identified 5 main themes, including (1) disbelief in the existence of the infection; (2) suspicion about a potential new business after COVID-19; (3) suspicion that COVID-19 vaccine(s) are the cause; (4) religion-related fatalism and (5) trust in government measures.

CONCLUSIONS

The findings advance knowledge about public perceptions, reactions and attitudes towards the emergence of ASHUE and the efficacy of disease countermeasures. The knowledge from this study will provide an understanding of why disease prevention measures might not be followed. It can be used to develop public awareness programs in Indonesia about both the ASHUE and its possible consequences and the available healthcare support.

A systematic review of the use of topic models for short text social media analysis

Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures do not inform whether the topics produced can yield meaningful insights for those examining social media data. Efforts to address this issue, including gauging the alignment between automated and human evaluation tasks, are hampered by a lack of knowledge about how researchers use topic models. Further problems could arise if researchers do not construct topic models optimally or use them in a way that exceeds the models' limitations. These scenarios threaten the validity of topic model development and the insights produced by researchers employing topic modelling as a methodology. However, there is currently a lack of information about how and why topic models are used in applied research. As such, we performed a systematic literature review of 189 articles where topic modelling was used for social media analysis to understand how and why topic models are used for social media analysis. Our results suggest that the development of topic models is not aligned with the needs of those who use them for social media analysis. We have found that researchers use topic models sub-optimally. There is a lack of methodological support for researchers to build and interpret topics. We offer a set of recommendations for topic model researchers to address these problems and bridge the gap between development and applied research on short text topic models.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10462-023-10471-x.