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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Aspect-based sentiment analysis aims to identify the sentiment polarity of aspecific aspect in product reviews. We notice that about 30% of reviews do notcontain obvious opinion words, but still convey clear human-aware sentimentorientation, which is known as implicit sentiment. However, recent neuralnetwork-based approaches paid little attention to implicit sentiment entailedin the reviews. To overcome this issue, we adopt Supervised ContrastivePre-training on large-scale sentiment-annotated corpora retrieved fromin-domain language resources. By aligning the representation of implicitsentiment expressions to those with the same sentiment label, the pre-trainingprocess leads to better capture of both implicit and explicit sentimentorientation towards aspects in reviews. Experimental results show that ourmethod achieves state-of-the-art performance on SemEval2014 benchmarks, andcomprehensive analysis validates its effectiveness on learning implicitsentiment.

Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training