yuankeyi/2019-SOHU-Contest
2019年4月8日，第三届搜狐校园内容识别算法大赛。
This project helps media companies or content analysts automatically understand news articles. It takes raw news text as input and identifies the top three most important entities (people, organizations, places, etc.) mentioned in the article, along with the sentiment (positive, neutral, negative) expressed towards each of them. News editors, content strategists, or market researchers can use this to efficiently monitor public opinion and trending topics in vast amounts of content.
No commits in the last 6 months.
Use this if you need to quickly extract key entities and understand the emotional tone surrounding them from a large volume of Chinese news articles.
Not ideal if your primary goal is nuanced sentiment analysis beyond general positive, neutral, or negative, or if you are working with non-news content or other languages.
Stars
26
Forks
6
Language
Python
License
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Category
Last pushed
May 14, 2019
Commits (30d)
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