Entity-level sentiment analysis predicts the sentiment about entities mentioned in a given text. It is very useful in a business context to understand user emotions towards certain entities, such as products or companies. In this paper, we demonstrate how we developed an entity-level sentiment analysis system that analyzes English telephone conversation transcripts in contact centers to provide business insight. We present two approaches, one entirely based on the transformer-based DistilBERT model, and another that uses a convolutional neural network supplemented with some heuristic rules.
@article{arxiv.2210.13401,
title = {Entity-level Sentiment Analysis in Contact Center Telephone Conversations},
author = {Xue-Yong Fu and Cheng Chen and Md Tahmid Rahman Laskar and Shayna Gardiner and Pooja Hiranandani and Shashi Bhushan TN},
journal= {arXiv preprint arXiv:2210.13401},
year = {2022}
}