English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Hot words are the topic of concern of the netizens, which can help the management department to monitor the public opinion of the network. Due to the large degree of freedom, irregular syntax and immediacy of data, it is difficult for data engine to grasp text hotspots accurately through traditional text analysis. This paper deals with the text features of a time span, and determines whether it is a hot word by adding the time information of the span. Through experiments, the hot words excavated correspond to the corresponding hot events. This shows that the method proposed in this paper has a good effect and can be further studied. Keywords—network public opinion; hot words; data mining; university

Research on Hot Words Mining Algorithm of University Network Public Sentiment