Banca de QUALIFICAÇÃO: Ricardo Cordeiro Galvão Sant'Ana Van Erven

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : Ricardo Cordeiro Galvão Sant'Ana Van Erven
DATE: 28/08/2023
TIME: 10:00
LOCAL: Teams
TITLE:

Measurement of Satisfaction of Users of Digital Products through Emotion Recognition

KEY WORDS:

Emotion Recognition, User Satisfaction Measurement, Artificial Intelligence

PAGES: 67
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
SPECIALTY: Engenharia de Software
SUMMARY:

\textbf{Context:} Measuring user satisfaction is an important tool to create value in the context of digital transformation. Measurement allows you to identify future purchase intentions, user loyalty, and retention. The traditional way of measuring satisfaction using self-assessment has problems, such as subjectivity. Therefore, a more objective approach is needed that allows automatic measurement of satisfaction.
\textbf{Objective:} Implement and validate a tool that automatically calculates the satisfaction rating of a user when using a digital product and that presents positive, neutral and negative points in using this product. A model with tool and experiment was proposed and, subsequently, the implementation and validation of this model will be carried out.
\textbf{Methods:} A systematic literature mapping was used to identify the main studies related to techniques, benefits, and challenges that associate the measurement of user satisfaction through the recognition of emotions with the use of Artificial Intelligence (AI). In the proposed model, an experiment was planned in two phases to validate research hypotheses related to the objective of the work. The experiment, which will apply the tool that will use AI, will be carried out by videoconferencing with the approach of exploratory usability testing on a Brazilian Superior Court web product.
\textbf{Results:} 10 primary studies were identified in different areas of knowledge: restaurants, television systems, retail stores, artistic shows, and usability testing in a call centre system. Two systematic reviews of the literature were also identified. The technique most commonly used in primary studies is the convolutional neural network (CNN). The use of cloud services for emotion recognition was also verified. Benefits related to user feedback, such as user profile mapping, were reported, and challenges for emotion recognition were found, such as user privacy and capture environment inadequacies.
\textbf{Conclusions:} The possibilities of applying emotion recognition are countless in terms of contexts, techniques, forms, and components. Despite this, it was possible to identify good practices that could guide the creation of a tool to measure the satisfaction of using a digital product through emotion recognition and Artificial Intelligence. The main contribution of this work is the proposal of a model that guides the creation of an automatic satisfaction measurement tool to identify positive, neutral, and negative points in the use of a digital product. This research also defines a measurement experimentation process that can be reproduced by any organisation or researcher.

 

COMMITTEE MEMBERS:
Interna - 1650604 - REJANE MARIA DA COSTA FIGUEIREDO
Externa à Instituição - ANA PAULA BERNARDI DA SILVA