Analysing Public Transport User Sentiment on Low Resource Multilingual Data

TL;DR

This paper applies multilingual opinion mining and NLP techniques to analyze public transport user sentiments in Sub-Saharan Africa, revealing insights into user experiences and highlighting the linguistic challenges of under-resourced languages.

Contribution

It introduces a multilingual sentiment analysis framework using PLMs for under-resourced languages in public transport opinion mining in Sub-Saharan Africa.

Findings

Negative sentiments in South Africa and Kenya

Positive sentiments in Tanzania due to advertising tweets

Semantic themes identified via Word2Vec and K-Means clustering

Abstract

Public transport systems in many Sub-Saharan countries often receive less attention compared to other sectors, underscoring the need for innovative solutions to improve the Quality of Service (QoS) and overall user experience. This study explored commuter opinion mining to understand sentiments toward existing public transport systems in Kenya, Tanzania, and South Africa. We used a qualitative research design, analysing data from X (formerly Twitter) to assess sentiments across rail, mini-bus taxis, and buses. By leveraging Multilingual Opinion Mining techniques, we addressed the linguistic diversity and code-switching present in our dataset, thus demonstrating the application of Natural Language Processing (NLP) in extracting insights from under-resourced languages. We employed PLMs such as AfriBERTa, AfroXLMR, AfroLM, and PuoBERTa to conduct the sentiment analysis. The results revealed predominantly negative sentiments in South Africa and Kenya, while the Tanzanian dataset showed mainly positive sentiments due to the advertising nature of the tweets. Furthermore, feature extraction using the Word2Vec model and K-Means clustering illuminated semantic relationships and primary themes found within the different datasets. By prioritising the analysis of user experiences and sentiments, this research paves the way for developing more responsive, user-centered public transport systems in Sub-Saharan countries, contributing to the broader goal of improving urban mobility and sustainability.