Sentiment analysis for emotional navigation in written communication

Abstract

A subfield of artificial intelligence is that of natural language processing and sentiment analysis. The interest in sentiment analysis has increased with the development of the internet and web 2.0. With sentiment analysis it is possible to analyse the sentiment or emotions of written communication through dictionary-based sentiment analysis or machine learning algorithms. However, sentiment analysis also holds the potential of supporting people with disadvantages in interpreting the nuances in written communication. One such group is autistic people. The aim of the study is to examine autistic peoples’ perceptions of important design factors and functionality for an application with sentiment analysis to support emotional navigation in written communication. This study has been conducted with the first steps of design science to outline the requirements of a potential application that can support autistic people to navigate the emotions in written communication with sentiment analysis. The problem to be addressed was identified through related research and one of authors’ own experience of navigating written communications with autism. The requirements for the application were the main focus for this study and has been the primarily concern for data collection. Data have been collected through semi-structured interviews with autistic people and analysed with thematic analysis. Results of the study provide several important recommendations for the design of applications with sentiment analysis to support autistic people navigate the emotions in written communication. The study further provides an understanding of autistic peoples’ needs when navigating written communication. These findings can be used by researchers and developers to design support-applications with autistic peoples’ needs in the centre. An interesting next step of research would be to develop a prototype with the findings of this study addressed in the application’s functionality and design, which could then be evaluated on a larger scale.