HappyDB: A corpus of 100,000 crowdsourced happy moments

Akari Asai; Sara Evensen; Behzad Golshan; Alon Halevy; Vivian Li; Andrei Lopatenko; Daniela Stepanov; Yoshihiko Suhara; Wang Chiew Tan; Yinzhan Xu

HappyDB: A corpus of 100,000 crowdsourced happy moments

Akari Asai
, Sara Evensen
, Behzad Golshan
, Alon Halevy
, Vivian Li
, Andrei Lopatenko
, Daniela Stepanov
, Yoshihiko Suhara
, Wang Chiew Tan
, Yinzhan Xu

The University of Tokyo
Massachusetts Institute of Technology
Recruit Institute of Technology

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

Abstract

The science of happiness is an area of positive psychology concerned with understanding what behaviors make people happy in a sustainable fashion. Recently, there has been interest in developing technologies that help incorporate the findings of the science of happiness into users' daily lives by steering them towards behaviors that increase happiness. With the goal of building technology that can understand how people express their happy moments in text, we crowd-sourced HappyDB, a corpus of 100,000 happy moments that we make publicly available. This paper describes HappyDB and its properties, and outlines several important NLP problems that can be studied with the help of the corpus. We also apply several state-of-the-art analysis techniques to analyze HappyDB. Our results demonstrate the need for deeper NLP techniques to be developed which makes HappyDB an exciting resource for follow-on research.

Original language	English
Title of host publication	LREC 2018 - 11th International Conference on Language Resources and Evaluation
Editors	Nicoletta Calzolari, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Koiti Hasida, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis, Takenobu Tokunaga
Publisher	European Language Resources Association (ELRA)
Pages	647-655
Number of pages	9
ISBN (Electronic)	9791095546009
State	Published - 2018
Externally published	Yes
Event	11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan Duration: 7 May 2018 → 12 May 2018

Publication series

Name	LREC 2018 - 11th International Conference on Language Resources and Evaluation

Conference

Conference	11th International Conference on Language Resources and Evaluation, LREC 2018
Country/Territory	Japan
City	Miyazaki
Period	7/05/18 → 12/05/18

Bibliographical note

Publisher Copyright:
© LREC 2018 - 11th International Conference on Language Resources and Evaluation. All rights reserved.

Keywords

Crowdsourcing
HappyDB corpus
Positive psychology
Science of happiness

Cite this

Asai, A., Evensen, S., Golshan, B., Halevy, A., Li, V., Lopatenko, A., Stepanov, D., Suhara, Y., Tan, W. C., & Xu, Y. (2018). HappyDB: A corpus of 100,000 crowdsourced happy moments. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), LREC 2018 - 11th International Conference on Language Resources and Evaluation (pp. 647-655). (LREC 2018 - 11th International Conference on Language Resources and Evaluation). European Language Resources Association (ELRA).

Asai, Akari ; Evensen, Sara ; Golshan, Behzad et al. / HappyDB : A corpus of 100,000 crowdsourced happy moments. LREC 2018 - 11th International Conference on Language Resources and Evaluation. editor / Nicoletta Calzolari ; Khalid Choukri ; Christopher Cieri ; Thierry Declerck ; Sara Goggi ; Koiti Hasida ; Hitoshi Isahara ; Bente Maegaard ; Joseph Mariani ; Helene Mazo ; Asuncion Moreno ; Jan Odijk ; Stelios Piperidis ; Takenobu Tokunaga. European Language Resources Association (ELRA), 2018. pp. 647-655 (LREC 2018 - 11th International Conference on Language Resources and Evaluation).

@inproceedings{c617c6f078fa45e6954be5d607fc6845,

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abstract = "The science of happiness is an area of positive psychology concerned with understanding what behaviors make people happy in a sustainable fashion. Recently, there has been interest in developing technologies that help incorporate the findings of the science of happiness into users' daily lives by steering them towards behaviors that increase happiness. With the goal of building technology that can understand how people express their happy moments in text, we crowd-sourced HappyDB, a corpus of 100,000 happy moments that we make publicly available. This paper describes HappyDB and its properties, and outlines several important NLP problems that can be studied with the help of the corpus. We also apply several state-of-the-art analysis techniques to analyze HappyDB. Our results demonstrate the need for deeper NLP techniques to be developed which makes HappyDB an exciting resource for follow-on research.",

keywords = "Crowdsourcing, HappyDB corpus, Positive psychology, Science of happiness",

author = "Akari Asai and Sara Evensen and Behzad Golshan and Alon Halevy and Vivian Li and Andrei Lopatenko and Daniela Stepanov and Yoshihiko Suhara and Tan, \{Wang Chiew\} and Yinzhan Xu",

note = "Publisher Copyright: {\textcopyright} LREC 2018 - 11th International Conference on Language Resources and Evaluation. All rights reserved.; 11th International Conference on Language Resources and Evaluation, LREC 2018 ; Conference date: 07-05-2018 Through 12-05-2018",

year = "2018",

language = "אנגלית",

series = "LREC 2018 - 11th International Conference on Language Resources and Evaluation",

publisher = "European Language Resources Association (ELRA)",

pages = "647--655",

editor = "Nicoletta Calzolari and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga",

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Asai, A, Evensen, S, Golshan, B, Halevy, A, Li, V, Lopatenko, A, Stepanov, D, Suhara, Y, Tan, WC & Xu, Y 2018, HappyDB: A corpus of 100,000 crowdsourced happy moments. in N Calzolari, K Choukri, C Cieri, T Declerck, S Goggi, K Hasida, H Isahara, B Maegaard, J Mariani, H Mazo, A Moreno, J Odijk, S Piperidis & T Tokunaga (eds), LREC 2018 - 11th International Conference on Language Resources and Evaluation. LREC 2018 - 11th International Conference on Language Resources and Evaluation, European Language Resources Association (ELRA), pp. 647-655, 11th International Conference on Language Resources and Evaluation, LREC 2018, Miyazaki, Japan, 7/05/18.

HappyDB: A corpus of 100,000 crowdsourced happy moments. / Asai, Akari; Evensen, Sara; Golshan, Behzad et al.
LREC 2018 - 11th International Conference on Language Resources and Evaluation. ed. / Nicoletta Calzolari; Khalid Choukri; Christopher Cieri; Thierry Declerck; Sara Goggi; Koiti Hasida; Hitoshi Isahara; Bente Maegaard; Joseph Mariani; Helene Mazo; Asuncion Moreno; Jan Odijk; Stelios Piperidis; Takenobu Tokunaga. European Language Resources Association (ELRA), 2018. p. 647-655 (LREC 2018 - 11th International Conference on Language Resources and Evaluation).

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

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AU - Asai, Akari

AU - Evensen, Sara

AU - Golshan, Behzad

AU - Halevy, Alon

AU - Li, Vivian

AU - Lopatenko, Andrei

AU - Stepanov, Daniela

AU - Suhara, Yoshihiko

AU - Tan, Wang Chiew

AU - Xu, Yinzhan

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N2 - The science of happiness is an area of positive psychology concerned with understanding what behaviors make people happy in a sustainable fashion. Recently, there has been interest in developing technologies that help incorporate the findings of the science of happiness into users' daily lives by steering them towards behaviors that increase happiness. With the goal of building technology that can understand how people express their happy moments in text, we crowd-sourced HappyDB, a corpus of 100,000 happy moments that we make publicly available. This paper describes HappyDB and its properties, and outlines several important NLP problems that can be studied with the help of the corpus. We also apply several state-of-the-art analysis techniques to analyze HappyDB. Our results demonstrate the need for deeper NLP techniques to be developed which makes HappyDB an exciting resource for follow-on research.

AB - The science of happiness is an area of positive psychology concerned with understanding what behaviors make people happy in a sustainable fashion. Recently, there has been interest in developing technologies that help incorporate the findings of the science of happiness into users' daily lives by steering them towards behaviors that increase happiness. With the goal of building technology that can understand how people express their happy moments in text, we crowd-sourced HappyDB, a corpus of 100,000 happy moments that we make publicly available. This paper describes HappyDB and its properties, and outlines several important NLP problems that can be studied with the help of the corpus. We also apply several state-of-the-art analysis techniques to analyze HappyDB. Our results demonstrate the need for deeper NLP techniques to be developed which makes HappyDB an exciting resource for follow-on research.

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A2 - Calzolari, Nicoletta

A2 - Choukri, Khalid

A2 - Cieri, Christopher

A2 - Declerck, Thierry

A2 - Goggi, Sara

A2 - Hasida, Koiti

A2 - Isahara, Hitoshi

A2 - Maegaard, Bente

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ER -

Asai A, Evensen S, Golshan B, Halevy A, Li V, Lopatenko A et al. HappyDB: A corpus of 100,000 crowdsourced happy moments. In Calzolari N, Choukri K, Cieri C, Declerck T, Goggi S, Hasida K, Isahara H, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, Tokunaga T, editors, LREC 2018 - 11th International Conference on Language Resources and Evaluation. European Language Resources Association (ELRA). 2018. p. 647-655. (LREC 2018 - 11th International Conference on Language Resources and Evaluation).

HappyDB: A corpus of 100,000 crowdsourced happy moments

Abstract

Publication series

Conference

Bibliographical note

Keywords

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Cite this