@inproceedings{jaech-etal-2018-community,
title = "Community Member Retrieval on Social Media Using Textual Information",
author = "Jaech, Aaron and
Hathi, Shobhit and
Ostendorf, Mari",
editor = "Walker, Marilyn and
Ji, Heng and
Stent, Amanda",
booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N18-2094",
doi = "10.18653/v1/N18-2094",
pages = "595--601",
abstract = "This paper addresses the problem of community membership detection using only text features in a scenario where a small number of positive labeled examples defines the community. The solution introduces an unsupervised proxy task for learning user embeddings: user re-identification. Experiments with 16 different communities show that the resulting embeddings are more effective for community membership identification than common unsupervised representations.",
}
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%0 Conference Proceedings
%T Community Member Retrieval on Social Media Using Textual Information
%A Jaech, Aaron
%A Hathi, Shobhit
%A Ostendorf, Mari
%Y Walker, Marilyn
%Y Ji, Heng
%Y Stent, Amanda
%S Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F jaech-etal-2018-community
%X This paper addresses the problem of community membership detection using only text features in a scenario where a small number of positive labeled examples defines the community. The solution introduces an unsupervised proxy task for learning user embeddings: user re-identification. Experiments with 16 different communities show that the resulting embeddings are more effective for community membership identification than common unsupervised representations.
%R 10.18653/v1/N18-2094
%U https://aclanthology.org/N18-2094
%U https://doi.org/10.18653/v1/N18-2094
%P 595-601
Markdown (Informal)
[Community Member Retrieval on Social Media Using Textual Information](https://aclanthology.org/N18-2094) (Jaech et al., NAACL 2018)
ACL
- Aaron Jaech, Shobhit Hathi, and Mari Ostendorf. 2018. Community Member Retrieval on Social Media Using Textual Information. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 595–601, New Orleans, Louisiana. Association for Computational Linguistics.