2 citations · 2 across the 7 of their papers we have counts for
7 papers
Semantically Enriching Investor Micro-blogs for Opinion-Aware Emotion Analysis: A Practical Approach
Gaurav Negi, Paul Buitelaar
While sentiment analysis is the staple of financial NLP, capturing the nuances of 'why' behind that sentiment remains a challenge. There have been attempts to address this by analy…
Large Language Models as Automatic Annotators and Annotation Adjudicators for Fine-Grained Opinion Analysis
Gaurav Negi, MA Waskow, John McCrae +2
Fine-grained opinion analysis of text provides a detailed understanding of expressed sentiments and their targets. Although this level of detail is valuable, annotating opinions in…
Towards Temporal Knowledge-Base Creation for Fine-Grained Opinion Analysis with Language Models
Gaurav Negi, Atul Kr. Ojha, Omnia Zayed +1
We propose a scalable method for constructing a temporal opinion knowledge base with large language models (LLMs) as automated annotators. Despite the demonstrated utility of time-…
LTG at SemEval-2025 Task 10: Optimizing Context for Classification of Narrative Roles
Egil Rønningstad, Gaurav Negi
Our contribution to the SemEval 2025 shared task 10, subtask 1 on entity framing, tackles the challenge of providing the necessary segments from longer documents as context for cla…
Towards Semantic Integration of Opinions: Unified Opinion Concepts Ontology and Extraction Task
Gaurav Negi, Dhairya Dalal, Omnia Zayed +1
This paper introduces the Unified Opinion Concepts (UOC) ontology to integrate opinions within their semantic context. The UOC ontology bridges the gap between the semantic represe…
A Hybrid Approach To Aspect Based Sentiment Analysis Using Transfer Learning
Gaurav Negi, Rajdeep Sarkar, Omnia Zayed +1
Aspect-Based Sentiment Analysis (ABSA) aims to identify terms or multiword expressions (MWEs) on which sentiments are expressed and the sentiment polarities associated with them. T…
MaCmS: Magahi Code-mixed Dataset for Sentiment Analysis
Priya Rani, Gaurav Negi, Theodorus Fransen +1
The present paper introduces new sentiment data, MaCMS, for Magahi-Hindi-English (MHE) code-mixed language, where Magahi is a less-resourced minority language. This dataset is the…