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Synapse
May 7, 2026International Journal of Information and Communication Technology0 citationsOpen Access

Managing digital public opinion: a case study on developing a deep learning monitoring system for Weibo

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LZLin ZhuZLZhuang Li

Key Points

  • The study aims to develop a deep learning-based system to monitor digital public opinion on Weibo.
  • Developed a deep learning monitoring system for social media analysis.
  • Analyzed data from Weibo to assess public sentiment and opinion trends.
  • Utilized algorithms to process and categorize digital opinions.
  • The system successfully identified sentiment patterns with high accuracy.
  • Demonstrated timely insights into public opinions related to specific topics.
  • Facilitated improved strategies for managing digital public perceptions.

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Cite This Study

Zhu et al. (2026) studied this question.

synapsesocial.com/papers/69fc2c718b49bacb8b347f3fhttps://doi.org/10.1504/ijict.2026.10078157
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Monitoring and Analysis of Public Opinion in Social Networks Based on Weibo Data Mining2026
  2. 2A Network Public Opinion Analysis System based on Natural Language Processing2026
  3. 3Dynamic evolution monitoring of brand sentiment based on causal discovery neural networks2026
  4. 4Research on deep learning-based evaluation mechanisms for ideological and political education2026
  5. 5Analysis of online public opinion for public crisis events: a case study of the COVID-19 pandemic in Shanghai2026