An Emoticon-Based Novel Sarcasm Pattern Detection Strategy to Identify Sarcasm in Microblogging Social Networks
Bibliographic Data
| ID | 22106955 |
|---|---|
| Authors | M Nirmala (0000-0002-1166-7885, Vellore Institute of Technology University), Amir H Gandomi (0000-0002-2798-0104, University of Technology Sydney), M Rajasekhara Babu (0000-0002-3557-1917, Vellore Institute of Technology University), L D Dhinesh Babu (0000-0002-3354-8713, Vellore Institute of Technology University), Rizwan Patan (0000-0003-4878-1988, Kennesaw State University) |
| Year | 2024 |
| Volume | 11 |
| Issue | 4 |
| Pages | 5319-5326 |
| Publication date | 2024-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Computational Social Systems (JOURNAL) |
| Journal identifiers | ISSN: 2329-924X • E-ISSN: 2373-7476 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/tcss.2023.3306908 |
| OpenAlex | W4386524143 |
| Language | EN |
| Citations received | 2 |
| References cited | 18 |
Online social networks are one of the prime modes of communication used by people to voice their opinions and sentiments, especially after the advancement of digital gadgets and overall technology. Mining such sentiments and analyzing the polarity of user opinions is a trending research issue with high business value. Identifying, detecting, and understanding sarcasm is an important topic in the field of sentiment analysis. Despite being complex and challenging, automated detection of sarcasm is also a relatively less explored research area. In this article, we present a novel sarcasm pattern detection technique using emoticons to identify sarcasm in microblogging social networks like Twitter. Initially, we classify the tweets only with emoticons based on a decision tree classification approach. Afterward, we incorporate the SentiWordNet library and a separate emoticon library to find the polarities of the tokenized words and emoticons. Finally, we present a comparison of the polarity of the tweets and the polarity of the emoticons to detect sarcasm in tweets
Irony · Linguistics · Machine learning · Microblogging · Natural language processing · Sarcasm · Social media · World Wide Web · Computer Science · Digital Communication and Language · Sentiment Analysis and Opinion Mining · Spam and Phishing Detection · Artificial Intelligence
Sentiment strength detection in short informal text
“Turn that frown upside-down”
Opinion Mining and Sentiment Analysis
Irony in Talk Among Friends
Recognizing Verbal Irony in Spontaneous Speech
Contagious laughter
Sarcasm detection in microblogs using Naïve Bayes and fuzzy clustering
Emotional Expression Online
| Unique citing works | 2 |
|---|---|
| Citations per year | 2 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |