Main Article Content

Abstract

Call centers are service centers that act as a bridge between enterprise and customers. Importance is being given to customer satisfaction and also to performance of call center agents. However, few researches are being done by taking both the customers and the call center agents as the end users. A system performing aspect-based sentiment analysis is being designed and implemented. The proposed system incorporates audio to text conversion, sentiment analysis and a separate customer-login module. It is able to represent sentiments of customers regarding any particular aspect using joint bar graphs.

Keywords

— Call center, customer satisfaction, Sentiment Analysis, Machine Learning, Audio to Text Conversion.

Article Details

How to Cite
[1]
Prof. Swati Powar, Ms. Srushti Tupsakhare, Mr. Sameer Sawant, and Ms. Shahista Shaikh, “CALL CENTER SENTIMENT ANALYSIS”, IEJRD - International Multidisciplinary Journal, vol. 5, no. 5, p. 7, Jun. 2020.

References

  1. Peijia Li, Yonghong Van, Chaomin Wang, Zhijie Ren, Pengyu Cong, Huixin Wang, Junlan Feng, Customer Voice Sensor: A Comprehensive Opinion Mining System for Call Center Conversation, 2016 IEEE International Conference on Cloud Computing and Big Data Analysis.
  2. Wanxiang Che, Yanyan Zhao, Honglei Guo, Zhong Su, Ting Liu, Sentence Compression for Aspect-Based Sentiment Analysis, IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 23, NO. 12, DECEMBER 2015.
  3. Marvin Hagge, Moritz von Hoffen, Jan H. Betzing, Jorg Becker, Design and Implementation of a Toolkit for the Aspect-based Sentiment Analysis of Tweets, 2017 IEEE 19th Conference on Business Informatics (CBI).
  4. Isidoros Perikos, Ioannis Hatzilygeroudis, Aspect based Sentiment Analysis in Social Media with Classifier Ensembles, 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS).
  5. Betl KARAKUS, Galip AYDIN, Call Center Performance Evaluation Using Big Data Analytics, 2016 International Symposium on Networks, Computers and Communications (ISNCC).
  6. Yoko Kobayashi, Kazuhiko Tsuda, Extraction of the Customer Satisfaction in the Call Center Using Feelings Dictionary, 2016 5th IIAI International Congress on Advanced Applied Informatics.
  7. Dimitris Pappas, Ion Androutsopoulos, Haris Papageorgiou, Anger Detection in Call Center Dialogues, 2015 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom).
  8. Susanti Gojali, Masayu Leylia Khodra , Aspect Based Sentiment Analysis for Review Rating Prediction, 2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA).
  9. Souraya Ezzat, Neamat El Gayar, Moustafa M. Ghanem, Sentiment Analysis of Call Centre Conversations using Text Classification, International Journal of Computer Information Systems and
  10. Industrial Management Applications, ISSN 2150-7988 Volume 4 (2012) pp. 619 -627.
  11. Gilad Mishne, David Carmel, Ron Hoory, Alexey Roytman, Aya Soffer, Automatic Analysis of Call-center Conversations, CIKM 05 Proceedings of the 14th ACM international conference on Information and knowledge management, October 31November 5, 2005, Bremen, Germany.
  12. Swati Powar, Subhash Shinde, Named Entity Recognition and Tweet Sentiment Derived from Tweet Segmentation Using Hadoop, IEEE and CSI Sponsored 1st International Conference On Intelligence System and Information Management, October 2

Most read articles by the same author(s)