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

Past work in computational sarcasm deals primarily with sarcasm detection. Inthis paper, we introduce a novel, related problem: sarcasm targetidentification i.e., extracting the target of ridicule in a sarcasticsentence). We present an introductory approach for sarcasm targetidentification. Our approach employs two types of extractors: one based onrules, and another consisting of a statistical classifier. To compare ourapproach, we use two baselines: a na\"ive baseline and another baseline basedon work in sentiment target identification. We perform our experiments on booksnippets and tweets, and show that our hybrid approach performs better than thetwo baselines and also, in comparison with using the two extractorsindividually. Our introductory approach establishes the viability of sarcasmtarget identification, and will serve as a baseline for future work.

Automatic Identification of Sarcasm Target: An Introductory Approach