Demographic inference on twitter using recursive neural networks

Sunghwan Mac Kim; Qiongkai Xu; Lizhen Qu; Stephen Wan; Cécile Paris

doi:10.18653/v1/P17-2075

Demographic inference on twitter using recursive neural networks

Sunghwan Mac Kim, Qiongkai Xu, Lizhen Qu, Stephen Wan, Cécile Paris

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

38 Citations (Scopus)

Abstract

In social media, demographic inference is a critical task in order to gain a better understanding of a cohort and to facilitate interacting with one’s audience. Most previous work has made independence assumptions over topological, textual and label information on social networks. In this work, we employ recursive neural networks to break down these independence assumptions to obtain inference about demographic characteristics on Twitter. We show that our model performs better than existing models including the state-of-the-art.

Original language	English
Title of host publication	Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (volume 2: short papers)
Place of Publication	Stroudsburg, PA
Publisher	Association for Computational Linguistics (ACL)
Pages	471-477
Number of pages	7
ISBN (Electronic)	9781945626760
DOIs	https://doi.org/10.18653/v1/P17-2075
Publication status	Published - 2017
Externally published	Yes
Event	55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, Canada Duration: 30 Jul 2017 → 4 Aug 2017

Conference

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

Access to Document

10.18653/v1/P17-2075Licence: Unspecified

Cite this

@inproceedings{76a497a85efd4e0eb1896f49f83aeb56,

title = "Demographic inference on twitter using recursive neural networks",

abstract = "In social media, demographic inference is a critical task in order to gain a better understanding of a cohort and to facilitate interacting with one{\textquoteright}s audience. Most previous work has made independence assumptions over topological, textual and label information on social networks. In this work, we employ recursive neural networks to break down these independence assumptions to obtain inference about demographic characteristics on Twitter. We show that our model performs better than existing models including the state-of-the-art.",

author = "Kim, {Sunghwan Mac} and Qiongkai Xu and Lizhen Qu and Stephen Wan and C{\'e}cile Paris",

year = "2017",

doi = "10.18653/v1/P17-2075",

language = "English",

pages = "471--477",

booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (volume 2: short papers)",

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

address = "United States",

note = "55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 ; Conference date: 30-07-2017 Through 04-08-2017",

}

Kim, SM, Xu, Q, Qu, L, Wan, S & Paris, C 2017, Demographic inference on twitter using recursive neural networks. in Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (volume 2: short papers). Association for Computational Linguistics (ACL), Stroudsburg, PA, pp. 471-477, 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, 30/07/17. https://doi.org/10.18653/v1/P17-2075

Demographic inference on twitter using recursive neural networks. / Kim, Sunghwan Mac; Xu, Qiongkai; Qu, Lizhen et al.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (volume 2: short papers). Stroudsburg, PA: Association for Computational Linguistics (ACL), 2017. p. 471-477.

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

TY - GEN

T1 - Demographic inference on twitter using recursive neural networks

AU - Kim, Sunghwan Mac

AU - Xu, Qiongkai

AU - Qu, Lizhen

AU - Wan, Stephen

AU - Paris, Cécile

PY - 2017

Y1 - 2017

N2 - In social media, demographic inference is a critical task in order to gain a better understanding of a cohort and to facilitate interacting with one’s audience. Most previous work has made independence assumptions over topological, textual and label information on social networks. In this work, we employ recursive neural networks to break down these independence assumptions to obtain inference about demographic characteristics on Twitter. We show that our model performs better than existing models including the state-of-the-art.

AB - In social media, demographic inference is a critical task in order to gain a better understanding of a cohort and to facilitate interacting with one’s audience. Most previous work has made independence assumptions over topological, textual and label information on social networks. In this work, we employ recursive neural networks to break down these independence assumptions to obtain inference about demographic characteristics on Twitter. We show that our model performs better than existing models including the state-of-the-art.

UR - http://www.scopus.com/inward/record.url?scp=85040608860&partnerID=8YFLogxK

U2 - 10.18653/v1/P17-2075

DO - 10.18653/v1/P17-2075

M3 - Conference proceeding contribution

SP - 471

EP - 477

BT - Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (volume 2: short papers)

PB - Association for Computational Linguistics (ACL)

CY - Stroudsburg, PA

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

Y2 - 30 July 2017 through 4 August 2017

ER -

Demographic inference on twitter using recursive neural networks

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this