Automatic Sarcasm Detection [PDF]
ACM Computing Surveys, 2017 Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing text. Beginning with an approach that used speech-based features, automatic sarcasm detection has witnessed great interest from the sentiment analysis community.
Aditya Joshi 0001 +2 more
core +8 more sources
Self-attention bidirectional long Short-Term memory assisted natural language processing on sarcasm detection and classification in social media platforms [PDF]
Scientific ReportsSarcasm is a form of irony that expresses negative opinions. Sarcasm poses a linguistic problem owing to its symbolic nature, where deliberate meaning challenges correct understanding.
Jihen Majdoubi +7 more
doaj +2 more sources
Humor Styles Predict Self-Reported Sarcasm Use in Interpersonal Communication [PDF]
Behavioral SciencesWe investigated how participants’ humor styles impact their sarcasm use. English-speaking participants (N = 179) completed online self-report measures of humor styles and sarcasm use.
Liberty McAuley, Melanie Glenwright
doaj +2 more sources
Was that Sarcasm?: A Literature Survey on Sarcasm Detection
CoRRSarcasm is hard to interpret as human beings. Being able to interpret sarcasm is often termed as a sign of intelligence, given the complex nature of sarcasm. Hence, this is a field of Natural Language Processing which is still complex for computers to decipher.
Harleen Kaur Bagga +3 more
openaire +3 more sources
An emoji centric approach to sarcasm detection in online discourse [PDF]
Scientific ReportsSarcasm detection has gained significance in sentiment analysis, especially when social media is rife with cyberbullying and trolling. Emojis have garnered researchers’ interest as they are polysemic.
V. Grover, H. Banati
doaj +2 more sources
Enhancing sarcasm detection in sentiment analysis for cyberspace safety using advanced deep learning techniques [PDF]
Sci RepSocial media has become an integral part of daily life, with platforms like Twitter serving as popular outlets for users to share information and express grievances.
Raghu Dhumpati +6 more
semanticscholar +2 more sources
Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm [PDF]
Sci RepIn the era of rapid digital communication, vast amounts of textual data are generated daily, demanding efficient methods for latent content analysis to extract meaningful insights. Large Language Models (LLMs) offer potential for automating this process,
Ljubiša Bojić +6 more
semanticscholar +2 more sources
SARCASM DETECTION IN ONLINE REVIEW TEXT [PDF]
ICTACT Journal on Soft Computing, 2018 Sarcasm is a type of sentiment where people express negative sentiment using positive connotation words in text and vice-versa. In this work, we propose a cross-domain sarcasm detection framework that allows acquisition, storage and processing of tweets ...
Srishti Sharma, Shampa Chakraverty
doaj +2 more sources
A Survey of Multimodal Sarcasm Detection [PDF]
International Joint Conference on Artificial IntelligenceSarcasm is a rhetorical device that is used to convey the opposite of the literal meaning of an utterance. Sarcasm is widely used on social media and other forms of computer-mediated communication motivating the use of computational models to identify it
Shafkat Farabi +4 more
semanticscholar +5 more sources
Enhancing sarcasm detection on social media: A comprehensive study using LLMs and BERT with multi-headed attention on SARC [PDF]
PLoS OneSarcasm detection in natural language processing (NLP) remains a complex challenge, especially in social media, where contextual clues are often subtle.
Lihong Zhang +4 more
semanticscholar +2 more sources