MPSR: A Multi-Perspective Self-Reflection Framework for Public Opinion Report Generation

Crisis events generate massive information flows from diverse sources, which need to be consolidated into public opinion reports to enable timely response by governments and enterprises. Current LLMs, despite strong generation capabilities, fail to achieve perspective diversity, maintain factual consistency, and perform coherent high-level planning. To address these gaps, we propose MPSR: a multi-perspective self-reflection framework. Our framework first assigns diverse stakeholder personas to agents who independently generate initial writing plans from complementary viewpoints. Subsequently, a three-stage debate mechanism refines these plans by identifying conflicts, formulates resolution strategies, and produces a consensus plan, thereby enhancing factual consistency. Finally, we introduce a Report Fusion mechanism to synthesize reports across temporal batches, ensuring comprehensive event coverage. Extensive experiments demonstrate that MPSR significantly outperforms baselines, achieving Date F1 of 0.67, G-Eval of 4.54, and MiniCheck score of 79.43, which represent improvements of 17.5%, 70.0%, and 25.8% over the strongest baseline, respectively.

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Publication Details

Journal
Electronics
Published
2026-01-16
DOI
https://doi.org/10.3390/electronics15020404
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00
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article

MPSR: A Multi-Perspective Self-Reflection Framework for Public Opinion Report Generation

Jia Luo, Weijian Fan, Ying Xu, Jinzheng Yu et al.
Electronics
Sentiment Analysis and Opinion Mining
article

MPSR: A Multi-Perspective Self-Reflection Framework for Public Opinion Report Generation

Jia Luo, Weijian Fan, Ying Xu, Jinzheng Yu, Yifan Feng, Hao Shen, Ligu Zhu
article en

Abstract

Crisis events generate massive information flows from diverse sources, which need to be consolidated into public opinion reports to enable timely response by governments and enterprises. Current LLMs, despite strong generation capabilities, fail to achieve perspective diversity, maintain factual consistency, and perform coherent high-level planning. To address these gaps, we propose MPSR: a multi-perspective self-reflection framework. Our framework first assigns diverse stakeholder personas to agents who independently generate initial writing plans from complementary viewpoints. Subsequently, a three-stage debate mechanism refines these plans by identifying conflicts, formulates resolution strategies, and produces a consensus plan, thereby enhancing factual consistency. Finally, we introduce a Report Fusion mechanism to synthesize reports across temporal batches, ensuring comprehensive event coverage. Extensive experiments demonstrate that MPSR significantly outperforms baselines, achieving Date F1 of 0.67, G-Eval of 4.54, and MiniCheck score of 79.43, which represent improvements of 17.5%, 70.0%, and 25.8% over the strongest baseline, respectively.

ElectronicsVol. 15(2)
Santa Clara University (US), Chongqing University of Science and Technology (CN), Harbin Institute of Technology (CN), Beijing University of Technology (CN), Chongqing University of Technology (CN), Communication University of China (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 86%
Sentiment Analysis and Opinion Mining
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MPSR: A Multi-Perspective Self-Reflection Framework for Public Opinion Report Generation — Jia Luo, Weijian Fan, et al. · Electronics (2026) | TGRS Research Map | TGRS