Recognizing counterfactual thinking in social media texts

Youngseo Son; Anneke Buffone; Anthony Janocko; Allegra Larche; Joseph Raso; Kevin Zembroski; H. Andrew Schwartz; Lyle Ungar

doi:10.18653/v1/P17-2103

Recognizing counterfactual thinking in social media texts

Youngseo Son
, Anneke Buffone
, Anthony Janocko
, Allegra Larche
, Joseph Raso
, Kevin Zembroski
, H. Andrew Schwartz
, Lyle Ungar

Computer Science

Stony Brook University
University of Pennsylvania

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

28 Scopus citations

Abstract

Counterfactual statements, describing events that did not occur and their con-sequents, have been studied in areas including problem-solving, affect management, and behavior regulation. People with more counterfactual thinking tend to perceive life events as more personally meaningful. Nevertheless, counterfactuals have not been studied in computational linguistics. We create a counterfactual tweet dataset and explore approaches for detecting counterfactuals using rule-based and supervised statistical approaches. A combined rule-based and statistical approach yielded the best results (F1 = 0.77) outperforming either approach used alone.

Original language	English
Title of host publication	ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers)
Publisher	Association for Computational Linguistics (ACL)
Pages	654-658
Number of pages	5
ISBN (Electronic)	9781945626760
DOIs	https://doi.org/10.18653/v1/P17-2103
State	Published - 2017
Event	55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, Canada Duration: Jul 30 2017 → Aug 4 2017

Publication series

Name	ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)
Volume	2

Conference

Conference	55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
Country/Territory	Canada
City	Vancouver
Period	07/30/17 → 08/4/17

Access to Document

10.18653/v1/P17-2103

Cite this

Son, Y., Buffone, A., Janocko, A., Larche, A., Raso, J., Zembroski, K., Schwartz, H. A., & Ungar, L. (2017). Recognizing counterfactual thinking in social media texts. In ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers) (pp. 654-658). (ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers); Vol. 2). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/P17-2103

Son, Youngseo ; Buffone, Anneke ; Janocko, Anthony et al. / Recognizing counterfactual thinking in social media texts. ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers). Association for Computational Linguistics (ACL), 2017. pp. 654-658 (ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)).

@inproceedings{2b6ae31c66464536bc09a1266bdb13ec,

title = "Recognizing counterfactual thinking in social media texts",

abstract = "Counterfactual statements, describing events that did not occur and their con-sequents, have been studied in areas including problem-solving, affect management, and behavior regulation. People with more counterfactual thinking tend to perceive life events as more personally meaningful. Nevertheless, counterfactuals have not been studied in computational linguistics. We create a counterfactual tweet dataset and explore approaches for detecting counterfactuals using rule-based and supervised statistical approaches. A combined rule-based and statistical approach yielded the best results (F1 = 0.77) outperforming either approach used alone.",

author = "Youngseo Son and Anneke Buffone and Anthony Janocko and Allegra Larche and Joseph Raso and Kevin Zembroski and Schwartz, \{H. Andrew\} and Lyle Ungar",

note = "Publisher Copyright: {\textcopyright} 2017 Association for Computational Linguistics.; 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 ; Conference date: 30-07-2017 Through 04-08-2017",

year = "2017",

doi = "10.18653/v1/P17-2103",

language = "English",

series = "ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)",

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

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Son, Y, Buffone, A, Janocko, A, Larche, A, Raso, J, Zembroski, K, Schwartz, HA & Ungar, L 2017, Recognizing counterfactual thinking in social media texts. in ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers). ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers), vol. 2, Association for Computational Linguistics (ACL), pp. 654-658, 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, 07/30/17. https://doi.org/10.18653/v1/P17-2103

Recognizing counterfactual thinking in social media texts. / Son, Youngseo; Buffone, Anneke; Janocko, Anthony et al.
ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers). Association for Computational Linguistics (ACL), 2017. p. 654-658 (ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers); Vol. 2).

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

TY - GEN

T1 - Recognizing counterfactual thinking in social media texts

AU - Son, Youngseo

AU - Buffone, Anneke

AU - Janocko, Anthony

AU - Larche, Allegra

AU - Raso, Joseph

AU - Zembroski, Kevin

AU - Schwartz, H. Andrew

AU - Ungar, Lyle

PY - 2017

Y1 - 2017

N2 - Counterfactual statements, describing events that did not occur and their con-sequents, have been studied in areas including problem-solving, affect management, and behavior regulation. People with more counterfactual thinking tend to perceive life events as more personally meaningful. Nevertheless, counterfactuals have not been studied in computational linguistics. We create a counterfactual tweet dataset and explore approaches for detecting counterfactuals using rule-based and supervised statistical approaches. A combined rule-based and statistical approach yielded the best results (F1 = 0.77) outperforming either approach used alone.

AB - Counterfactual statements, describing events that did not occur and their con-sequents, have been studied in areas including problem-solving, affect management, and behavior regulation. People with more counterfactual thinking tend to perceive life events as more personally meaningful. Nevertheless, counterfactuals have not been studied in computational linguistics. We create a counterfactual tweet dataset and explore approaches for detecting counterfactuals using rule-based and supervised statistical approaches. A combined rule-based and statistical approach yielded the best results (F1 = 0.77) outperforming either approach used alone.

UR - https://www.scopus.com/pages/publications/85040626625

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DO - 10.18653/v1/P17-2103

M3 - Conference contribution

AN - SCOPUS:85040626625

T3 - ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)

SP - 654

EP - 658

BT - ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers)

PB - Association for Computational Linguistics (ACL)

T2 - 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017

Y2 - 30 July 2017 through 4 August 2017

ER -

Son Y, Buffone A, Janocko A, Larche A, Raso J, Zembroski K et al. Recognizing counterfactual thinking in social media texts. In ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Short Papers). Association for Computational Linguistics (ACL). 2017. p. 654-658. (ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)). doi: 10.18653/v1/P17-2103

Recognizing counterfactual thinking in social media texts

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