Abstract

In developing smart cities, the implementation of social connections, collaboration, innovation, exchange of views by observing, exploiting and integrating various types of knowledge is required. The smart cities concept that employs knowledge sharing mechanism can be defined as the concept of a city that utilizes information technology to increase citizens' awareness, intelligence as well as community's participation. The knowledge dissemination via online sharing platforms has been becoming more popular in recent years, especially during the epidemic of infectious diseases. Thus, the social network and emotional analysis method based on intelligent data analysis algorithms is proposed to study the speaker relationship and comment sentiment tendency of a Chinese popular speech (knowledge dissemination) platform: YiXi. In our research, 690 speakers' information and 23,685 comments' information are collected from YiXi website as the data source. The speaker relationship network construction algorithm and emotional analysis algorithm are designed in details respectively. Experiments show that speakers who have the same profession can deliver different types of speeches, indicating that selection of YiXi platform in the invitation of speakers is diversified. In addition, overall sentiment tendency of comments on speeches seem to be slightly positive and most of them are the personal feelings according to their experience after watching speech videos instead of the direct evaluations of speech quality. The research aims to gain an insight into the popular knowledge sharing phenomenon and is expected to provide reference for knowledge dissemination platforms in order to improve the knowledge sharing environment in smart cities.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.