Trouble on the road: Finding reasons for commuter stress from tweets

Reshmi Gopalakrishna Pillai; Mike Thelwall; Constantin Orasan

Trouble on the road: Finding reasons for commuter stress from tweets

Reshmi Gopalakrishna Pillai, Mike Thelwall, Constantin Orasan

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Intelligent 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.

Original language	English
Title of host publication	2IS and NLG 2018 - Workshop on Intelligent Interactive Systems and Language Generation, Proceedings of the Workshop
Publisher	Association for Computational Linguistics (ACL)
Pages	20-25
ISBN (Electronic)	9781948087889
Publication status	Published - 2018
Externally published	Yes
Event	2018 Workshop on Intelligent Interactive Systems and Language Generation, 2IS and NLG 2018, collocated with the 11th International Conference on Natural Language Generation, INLG 2018 - Tilburg, Netherlands Duration: 5 Nov 2018 → …

Conference

Conference	2018 Workshop on Intelligent Interactive Systems and Language Generation, 2IS and NLG 2018, collocated with the 11th International Conference on Natural Language Generation, INLG 2018
Country/Territory	Netherlands
City	Tilburg
Period	5/11/18 → …

Funding

This research was supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No 636160-2, the Optimum project www.optimumproject.eu.

Funders	Funder number
Horizon 2020 Framework Programme	636160-2

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@inproceedings{8b8bc0c910a940a2867a73444c360df3,

title = "Trouble on the road: Finding reasons for commuter stress from tweets",

abstract = "Intelligent 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.",

author = "Pillai, {Reshmi Gopalakrishna} and Mike Thelwall and Constantin Orasan",

year = "2018",

language = "English",

pages = "20--25",

booktitle = "2IS and NLG 2018 - Workshop on Intelligent Interactive Systems and Language Generation, Proceedings of the Workshop",

publisher = "Association for Computational Linguistics (ACL)",

note = "2018 Workshop on Intelligent Interactive Systems and Language Generation, 2IS and NLG 2018, collocated with the 11th International Conference on Natural Language Generation, INLG 2018 ; Conference date: 05-11-2018",

}

Pillai, RG, Thelwall, M & Orasan, C 2018, Trouble on the road: Finding reasons for commuter stress from tweets. in 2IS and NLG 2018 - Workshop on Intelligent Interactive Systems and Language Generation, Proceedings of the Workshop. Association for Computational Linguistics (ACL), pp. 20-25, 2018 Workshop on Intelligent Interactive Systems and Language Generation, 2IS and NLG 2018, collocated with the 11th International Conference on Natural Language Generation, INLG 2018, Tilburg, Netherlands, 5/11/18.

Trouble on the road: Finding reasons for commuter stress from tweets. / Pillai, Reshmi Gopalakrishna; Thelwall, Mike; Orasan, Constantin.
2IS and NLG 2018 - Workshop on Intelligent Interactive Systems and Language Generation, Proceedings of the Workshop. Association for Computational Linguistics (ACL), 2018. p. 20-25.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Trouble on the road

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AU - Pillai, Reshmi Gopalakrishna

AU - Thelwall, Mike

AU - Orasan, Constantin

PY - 2018

Y1 - 2018

N2 - Intelligent 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.

AB - Intelligent 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.

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M3 - Conference contribution

SP - 20

EP - 25

BT - 2IS and NLG 2018 - Workshop on Intelligent Interactive Systems and Language Generation, Proceedings of the Workshop

PB - Association for Computational Linguistics (ACL)

Y2 - 5 November 2018

ER -

Trouble on the road: Finding reasons for commuter stress from tweets

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