A Deep Learning Approach for Multimodal Deception Detection

no code implementations • 1 Mar 2018 • Gangeshwar Krishnamurthy, Navonil Majumder, Soujanya Poria, Erik Cambria

Automatic deception detection is an important task that has gained momentum in computational linguistics due to its potential applications.

Deception Detection

Modeling Inter-Aspect Dependencies for Aspect-Based Sentiment Analysis

1 code implementation • NAACL 2018 • Devamanyu Hazarika, Soujanya Poria, Prateek Vij, Gangeshwar Krishnamurthy, Erik Cambria, Roger Zimmermann

Aspect-based Sentiment Analysis is a fine-grained task of sentiment classification for multiple aspects in a sentence.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +4

Towards Verifying Semantic Roles Co-occurrence

no code implementations • 9 Oct 2018 • Aliaksandr Huminski, Hao Zhang, Gangeshwar Krishnamurthy

Semantic role theory considers roles as a small universal set of unanalyzed entities.

Variational Fusion for Multimodal Sentiment Analysis

no code implementations • 13 Aug 2019 • Navonil Majumder, Soujanya Poria, Gangeshwar Krishnamurthy, Niyati Chhaya, Rada Mihalcea, Alexander Gelbukh

Multimodal fusion is considered a key step in multimodal tasks such as sentiment analysis, emotion detection, question answering, and others.

Multimodal Sentiment Analysis Question Answering

SocCogCom at SemEval-2020 Task 11: Characterizing and Detecting Propaganda using Sentence-Level Emotional Salience Features

1 code implementation • SEMEVAL 2020 • Gangeshwar Krishnamurthy, Raj Kumar Gupta, Yinping Yang

We focus on examining how emotional salience features extracted from a news segment can help to characterize and predict the presence of propaganda techniques.

Sentence