#WhoAmI in 160 characters?: Classifying social identities based on Twitter profile descriptions

Anna Priante; Djoerd Hiemstra; Tijs Adriaan van den Broek; Aaqib Saeed; Michel Léon Ehrenhard; Ariana Need

doi:10.18653/v1/W16-5608

#WhoAmI in 160 characters? Classifying social identities based on Twitter profile descriptions

Anna Priante
, Djoerd Hiemstra
, Tijs Adriaan van den Broek
, Aaqib Saeed
, Michel Léon Ehrenhard
, Ariana Need

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

19 Citations (Scopus)

260 Downloads (Pure)

Abstract

We combine social theory and NLP methods to classify English-speaking Twitter users’ online social identity in profile descriptions. We conduct two text classification experiments. In Experiment 1 we use a 5-category online social identity classification based on identity and self-categorization theories. While we are able to automatically classify two identity categories (Relational and Occupational), automatic classification of the other three identities (Political, Ethnic/religious and Stigmatized) is challenging. In Experiment 2 we test a merger of such identities based on theoretical arguments. We find that by combining these identities we can improve the predictive performance of the classifiers in the experiment. Our study shows how social theory can be used to guide NLP methods, and how such methods provide input to revisit traditional social theory that is strongly consolidated in offline setting

Original language	English
Title of host publication	Workshop on Natural Language Processing and Computational Social Science
Subtitle of host publication	NLP+CSS, EMNLP
Place of Publication	Austin, Texas
Publisher	Association for Computational Linguistics (ACL)
Pages	55-65
Number of pages	11
ISBN (Print)	978-1-945626-26-5
DOIs	https://doi.org/10.18653/v1/W16-5608
Publication status	Published - Nov 2016
Event	Conference on Empirical Methods in Natural Language Processing, EMNLP 2016 - Austin, United States Duration: 1 Nov 2016 → 5 Nov 2016 https://www.aclweb.org/mirror/emnlp2016/

Other

Other	Conference on Empirical Methods in Natural Language Processing, EMNLP 2016
Abbreviated title	EMNLP 2016
Country/Territory	United States
City	Austin
Period	1/11/16 → 5/11/16
Other	Doctoral Consortium EMNLP 2016
Internet address	https://www.aclweb.org/mirror/emnlp2016/

Keywords

EWI-27810
IR-102356
METIS-319140

Access to Document

10.18653/v1/W16-5608

W16-560

Cite this

Priante, A., Hiemstra, D., van den Broek, T. A., Saeed, A., Ehrenhard, M. L., & Need, A. (2016). #WhoAmI in 160 characters? Classifying social identities based on Twitter profile descriptions. In Workshop on Natural Language Processing and Computational Social Science: NLP+CSS, EMNLP (pp. 55-65). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/W16-5608

@inproceedings{b33495df5a2844a9987d6ab7c2b0ce3b,

title = "\#WhoAmI in 160 characters?: Classifying social identities based on Twitter profile descriptions",

abstract = "We combine social theory and NLP methods to classify English-speaking Twitter users{\textquoteright} online social identity in profile descriptions. We conduct two text classification experiments. In Experiment 1 we use a 5-category online social identity classification based on identity and self-categorization theories. While we are able to automatically classify two identity categories (Relational and Occupational), automatic classification of the other three identities (Political, Ethnic/religious and Stigmatized) is challenging. In Experiment 2 we test a merger of such identities based on theoretical arguments. We find that by combining these identities we can improve the predictive performance of the classifiers in the experiment. Our study shows how social theory can be used to guide NLP methods, and how such methods provide input to revisit traditional social theory that is strongly consolidated in offline setting",

keywords = "EWI-27810, IR-102356, METIS-319140",

author = "Anna Priante and Djoerd Hiemstra and \{van den Broek\}, \{Tijs Adriaan\} and Aaqib Saeed and Ehrenhard, \{Michel L{\'e}on\} and Ariana Need",

year = "2016",

month = nov,

doi = "10.18653/v1/W16-5608",

language = "English",

isbn = "978-1-945626-26-5",

pages = "55--65",

booktitle = "Workshop on Natural Language Processing and Computational Social Science",

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

address = "United States",

note = "Conference on Empirical Methods in Natural Language Processing, EMNLP 2016, EMNLP 2016 ; Conference date: 01-11-2016 Through 05-11-2016",

url = "https://www.aclweb.org/mirror/emnlp2016/",

}

Priante, A, Hiemstra, D, van den Broek, TA, Saeed, A, Ehrenhard, ML & Need, A 2016, #WhoAmI in 160 characters? Classifying social identities based on Twitter profile descriptions. in Workshop on Natural Language Processing and Computational Social Science: NLP+CSS, EMNLP. Association for Computational Linguistics (ACL), Austin, Texas, pp. 55-65, Conference on Empirical Methods in Natural Language Processing, EMNLP 2016, Austin, Texas, United States, 1/11/16. https://doi.org/10.18653/v1/W16-5608

#WhoAmI in 160 characters? Classifying social identities based on Twitter profile descriptions. / Priante, Anna; Hiemstra, Djoerd; van den Broek, Tijs Adriaan et al.
Workshop on Natural Language Processing and Computational Social Science: NLP+CSS, EMNLP. Austin, Texas: Association for Computational Linguistics (ACL), 2016. p. 55-65.

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

TY - GEN

T1 - #WhoAmI in 160 characters?

T2 - Conference on Empirical Methods in Natural Language Processing, EMNLP 2016

AU - Priante, Anna

AU - Hiemstra, Djoerd

AU - van den Broek, Tijs Adriaan

AU - Saeed, Aaqib

AU - Ehrenhard, Michel Léon

AU - Need, Ariana

PY - 2016/11

Y1 - 2016/11

N2 - We combine social theory and NLP methods to classify English-speaking Twitter users’ online social identity in profile descriptions. We conduct two text classification experiments. In Experiment 1 we use a 5-category online social identity classification based on identity and self-categorization theories. While we are able to automatically classify two identity categories (Relational and Occupational), automatic classification of the other three identities (Political, Ethnic/religious and Stigmatized) is challenging. In Experiment 2 we test a merger of such identities based on theoretical arguments. We find that by combining these identities we can improve the predictive performance of the classifiers in the experiment. Our study shows how social theory can be used to guide NLP methods, and how such methods provide input to revisit traditional social theory that is strongly consolidated in offline setting

AB - We combine social theory and NLP methods to classify English-speaking Twitter users’ online social identity in profile descriptions. We conduct two text classification experiments. In Experiment 1 we use a 5-category online social identity classification based on identity and self-categorization theories. While we are able to automatically classify two identity categories (Relational and Occupational), automatic classification of the other three identities (Political, Ethnic/religious and Stigmatized) is challenging. In Experiment 2 we test a merger of such identities based on theoretical arguments. We find that by combining these identities we can improve the predictive performance of the classifiers in the experiment. Our study shows how social theory can be used to guide NLP methods, and how such methods provide input to revisit traditional social theory that is strongly consolidated in offline setting

KW - EWI-27810

KW - IR-102356

KW - METIS-319140

U2 - 10.18653/v1/W16-5608

DO - 10.18653/v1/W16-5608

M3 - Conference contribution

SN - 978-1-945626-26-5

SP - 55

EP - 65

BT - Workshop on Natural Language Processing and Computational Social Science

PB - Association for Computational Linguistics (ACL)

CY - Austin, Texas

Y2 - 1 November 2016 through 5 November 2016

ER -