Research on knowledge dissemination in smart cities environment based on intelligent analysis algorithms: a case...

Area of Science:

• Smart City Development
• Knowledge Management
• Social Network Analysis

Background:

• Smart cities require social connections and knowledge exchange for innovation.
• Online knowledge dissemination platforms are increasingly vital, especially post-epidemic.
• Analyzing speaker relationships and audience sentiment is crucial for understanding knowledge sharing dynamics.

Purpose of the Study:

• To propose a social network and emotional analysis method for studying speaker relationships and comment sentiment on the YiXi platform.
• To investigate the diversity of speakers and the nature of audience engagement on a popular Chinese knowledge dissemination platform.
• To provide insights for improving knowledge sharing environments within smart cities.

Main Methods:

• Collected data from 690 speakers and 23,685 comments on the YiXi website.
• Designed a speaker relationship network construction algorithm.
• Developed an emotional analysis algorithm for comment sentiment.

Main Results:

• Speakers with the same profession delivered diverse speech types, indicating varied speaker selection by YiXi.
• The overall sentiment of comments was slightly positive.
• Most comments expressed personal feelings and experiences rather than direct evaluations of speech quality.

Conclusions:

• The YiXi platform exhibits diversified speaker invitations, contributing to a dynamic knowledge-sharing environment.
• Audience engagement is generally positive but focuses more on personal resonance than critical assessment.
• The study offers valuable references for optimizing knowledge dissemination platforms to enhance the smart city knowledge-sharing ecosystem.