Sentiment Analysis of Helpdesk Calls: Enhancing Customer Support through Natural Language Processing

DOI

10.2991/978-94-6463-716-8_31How to use a DOI?

Keywords

Sentiment Analysis; Helpdesk; NLP; Audio Mining; Customer Service; Emotion Detection; Machine Learning

Abstract

Helpdesks occupy a strategic position in managing customer relations in today’s organizations. Managing the caller primarily is very important in reducing call time to maximize customer satisfaction. The fields of natural language processing (NLP) house sentiment analysis as a sub-discipline, and the insights it offers are relevant to understanding emotional tendencies during these interactions. The following paper aims to study the application of sentiment analysis for the helpdesk call analysis and more specifically the speech data. In this paper, we introduce an automatic classification system of customers’ sentiments from voice-based interaction through enhanced audio analysis and NLP. Besides the conversation message, our model targets identification and analysis of emotions that may not be directly expressed in words by using complex parameters like pitch, tone and intonation. This system empowers the organizations to enhance customer services approach by providing real time information of the customer emotions regarding services hence enhancing service delivery. Therefore, this research paper assists to enhance the utilization of SA in voice-interaction and augment customer care by capturing the clients’ sentiments and emotions. These results suggest that there is a possibility of increasing customer satisfaction if only the helpdesk calls are addressed from the sentiment viewpoint.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Pritika Bahad
AU  - Dipti Chauhan
AU  - Diksha Bharawa
PY  - 2025
DA  - 2025/05/26
TI  - Sentiment Analysis of Helpdesk Calls: Enhancing Customer Support through Natural Language Processing
BT  - Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)
PB  - Atlantis Press
SP  - 385
EP  - 398
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-716-8_31
DO  - 10.2991/978-94-6463-716-8_31
ID  - Bahad2025
ER  -