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Guided by the risk information-seeking and processing model, this study examines positive and negative affect separately in their influence on information-seeking intentions and avoidance through structural equation analyses. The highlight is that information avoidance seems to be driven by positive affect, while information seeking seems to be more heavily influenced by negative affect. Another interesting finding is that informational subjective norms are positively related to both seeking and avoidance, which suggests that one’s social environment has the potential to strongly influence the way he or she handles climate change information. Implications for theory and practice are discussed.
J. Eberle, M. Schwinger, and H. Zwenzner. Proceedings of the 2021 conference on Big Data from Space, page 89--92. Publications Office of the European Union, (May 2021)
J. Eberle, M. Schwinger, and H. Zwenzner. Proceedings of the 2021 conference on Big Data from Space, page 89--92. Publications Office of the European Union, (May 2021)
J. Eberle, M. Schwinger, and H. Zwenzner. Proceedings of the 2021 conference on Big Data from Space, page 89--92. Publications Office of the European Union, (May 2021)
M. Schwab, R. Jäschke, and F. Fischer. Proceedings of the 6th International Conference on Natural Language and Speech Processing, page 99--109. Association for Computational Linguistics, (2023)