Mind-Map the Gap - Sentiment Analysis of Public Transport
This paper presents a case study where social media posts by individuals related to public transport companies in the United Kingdom are collected from social media sites such as Twitter using SAS®. The posts are then further processed in SAS® Text Miner to retrieve brand names, means of public transport (underground, trains, buses) and their attributes mentioned.
Relevant concepts and topics are identified using text mining techniques and visualized using concept links and word clouds.
Later we aim to identify and categorize sentiments against public transport in the corpus of the posts.
Finally, we approach to create an association map/mind-map of the different service dimensions/topics and the brands of public transport using correspondence analysis.