The interplay between social media virality metrics and message framing in influence perception of pro-environmental messages and behavioral intentions

Building entrepreneurship with sustainable environmental resources is a solution for the socio-economic and ecological conditions of suburban areas. This study aims to analyze public interest in processing alternative feed pellets made from organic waste and its determining factors. Data was taken from interviews with 31 respondents participating in organic waste treatment training in Brajan Tamantirto Kasihan Bantul, Yogyakarta. The results of the analysis showed that their interest in processing organic waste for alternative feed pellets was very high. Factors that influence their interests are environmental awareness, social media activity and participation in groups. Therefore, intensive assistance is needed to the community in the implementation of pellet processing as feed from basic organic waste materials. Thus, this program will contribute to the control of environmental, social and economic problems simultaneously so that this can improve their welfare and quality of life.

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Why People Accept Mental Health-Related Misinformation: Role of Social Media Metrics in Users’ Information Processing

Zhang,

Zhou,

Zhu

2024

Social Science Computer Review

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Drawing on dual-process theories, this study aims to investigate the factors associated with social media users’ acceptance of mental health-related misinformation (MHRM). We conducted a case study of Chinese microblogging Weibo on conversations that emerged following a publicised celebrity suicide of South Korean superstar Sulli. This incident sparked an extensive discussion on mental health issues as Sulli was reported to have suffered from depression prior to her death. Whilst previous studies on users’ information acceptance mainly adopted survey methods, our study employs a mixed-method approach (i.e. computational data collection method, content analysis and statistical analysis), which opens up new directions to utilise secondary social media data. We identified MHRM from the discussions on Weibo and labelled the responses to the misinformation as whether they indicate an acceptance of the MHRM. Binary logistic regression was used to examine the associations of receivers’ acceptance of MHRM with its information features (e.g. number of likes) and information sources (e.g. gender). Inconsistent with previous studies, our findings suggest that MHRM is less likely to be accepted when published by male users, underscoring the context-specific nature of heuristic cues. This study also revealed some novel findings, such as MHRM with more pictures or with more words is less likely to be accepted. A theoretical model was proposed based on the findings, which highlights the importance of heuristic cues and individuals’ pre-existing knowledge in information processing.

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The interplay between social media virality metrics and message framing in influence perception of pro-environmental messages and behavioral intentions

Cited by 6 publications

References 61 publications

How does user-generated content on Social Media affect stock predictions? A case study on GameStop

How does user-generated content on Social Media affect stock predictions? A case study on GameStop

Environmental Awareness and Public Interest in Processing Organic Waste in Suburban Areas: Findings in the Special Region of Yogyakarta, Indonesia

Why People Accept Mental Health-Related Misinformation: Role of Social Media Metrics in Users’ Information Processing

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