Commonly used sentiment lexicons.

<div><p>The absence of a sentiment lexicon tailored to agricultural product reviews presents significant challenges for accurate sentiment analysis in this domain. Existing general-purpose lexicons, such as NTUSD, HOWNET, and BosonNLP, fail to capture the unique linguistic features of ag...

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Bibliographic Details
Main Author:	Jinghua Wu (436901) (author)
Other Authors:	Peng Qiu (162135) (author), Xun Jia (364226) (author)
Published:	2025
Subjects:	Developmental Biology Science Policy Biological Sciences not elsewhere classified unique linguistic features taobao &# 8217 experimental results demonstrate based term frequency lexicon &# 8217 44 %, respectively 21 %, 91 sentiment lexicon tailored bsts sentiment lexicon negative seed words 843 preprocessed reviews calculate sentiment scores specific sentiment lexicon suboptimal classification performance accurate sentiment analysis pmi </ p sentiment classification effective lexicon sentiment analysis 92 %, specific tool pmi algorithm performance metrics f1 scores candidate words agricultural reviews xlink "> study constructs purpose lexicons optimal threshold f1 score existing general commerce platforms additional experiments
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Commonly used sentiment lexicons.

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