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Commuter_sentiment_analysis

Multilingual Sentiment Analysis

Given the deprioritisation of public transport in most Sub-Saharan countries, increased resource allocation is unlikely to occur because other sectors such as healthcare and education are considered a higher priority. Given this challenge, improving the user experience within the public transport system would require innovative solutions that go beyond improving the QoS. Solutions that also elevate the user experience as they interact with the system could serve as potential short to medium term solutions. The study proposes focusing on the users’ experiential journey through the system by conducting qualitative research by extracting and analysing the public transport user sentiment on three major modes, namely rail, mini-bus taxis, and buses. The user data was sourced from Facebook commuter groups, Twitter, and Community engagement forums (blogs). The method of Multilingual Opinion mining was applied while considering possible code-switching in the data collected. The study also compared the accuracy of public transport provider ratings of their service provision compared to user sentiment. Furthermore, the study investigated the existence of opportunities of enhancing the commuter experience within the public transport space.

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Multilingual Sentiment Analysis

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