An NLP Approach in Sentiment Analysis, Detecting Emotion, and Classifying Attitude for Measurement of Company^s Online Reputation
Nindya Athifa Khalisa- Gadang Ramantoko- Siska Noviaristanti

Magister Manajemen, School of Economic and Business, Telkom University

Abstract

In a world already dominated by the internet, a new concept emerged that defines customer opinion in cyberspace as a company^s reputation. Today all institutions, authorities, organizations, and even individuals have an online reputation. A company^s online reputation can be seen from reviews, comments, and social media posts made by consumers. It is important to collect, process, and analyze comments left on online media, as it can affect the credibility, sales, and progress of a company especially in the digital banking industry. This research offers a new conceptual method that operationalizes research concepts from previous research to measure online corporate reputation using three frameworks namely experience, emotion, and attitude of consumers. This conceptual method is rooted from NLP for sentiment analysis of experience, detection of emotion, and classification of attitude. From these three-components framework, the score will be made in the aggregate to explain the reputation of the company as well as in a unit of data for descriptive analysis. The conceptual method sees an application opportunity in digital banking sector, where the outcome can then be compared with the rating, number of reviews, and maturity of the digital bank.

Keywords: Digital bank, online reputation, emotion detection, attitude classification, conceptual method.

Topic: Digital Business Strategy