Trouble on the road: Finding reasons for commuter stress from tweets
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AbstractIntelligent Transportation Systems could benefit from harnessing social media content to get continuous feedback. In this work, we implement a system to identify reasons for stress in tweets related to traffic using a word vector strategy to select a reason from a predefined list generated by topic modeling and clustering. The proposed system, which performs better than standard machine learning algorithms, could provide inputs to warning systems for commuters in the area and feedback for the authorities.
CitationPillai, R. G., Thelwall, M. and Orasan, C. (2018) Trouble on the road: Finding reasons for commuter stress from tweets, Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG), 5th November 2018, Tillburg, Netherlands, pp. 20-25.
JournalProceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG)
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0/