Research on Risk Warning of Network Public Opinion for Forest Fires from the Perspective for Information Ecology

doi:10.12068/j.issn.1005-3026.2023.08.019

Abstract

Abstract: To address the risk warning of network public opinion for forest fires under uncertain information， a risk warning evaluation model based on evidential reasoning and intuitionistic fuzziness was established. Firstly， a network public opinion risk evaluation index system of forest fires was identified based on the perspective of the information ecosystem. Secondly， given the uncertainty and incompleteness of the index information in the evaluation process， the number of intuitionistic fuzziness was used to describe multiple index information by fuzzy rules. Then， the weight of the index system was calculated via intuitionistic fuzzy entropy and fuzzy analytic hierarchy process， and evidential reasoning theory was used to complete the integration of index information. Finally， the network public opinion risk level was determined by measuring the distances of intuitionistic fuzziness， and the ranking of network public opinion risks was determined by the utility value method. The practicability and effectiveness of the model were validated through three practical cases， providing new ideas and methods for the risk warning assessment of network public opinion for forest fires.

Key words: forest fire; information ecology; network public opinion risk assessment; uncertainty; evidential reasoning

CLC Number:

ZHU Guo-qing， CHEN Yan， LANG Kun， WANG Shu-tian. Research on Risk Warning of Network Public Opinion for Forest Fires from the Perspective for Information Ecology[J]. Journal of Northeastern University(Natural Science), 2023, 44(8): 1208-1216.

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