@inproceedings{wood-doughty-etal-2018-johns,
title = "{J}ohns {H}opkins or johnny-hopkins: Classifying Individuals versus Organizations on {T}witter",
author = "Wood-Doughty, Zach and
Mahajan, Praateek and
Dredze, Mark",
editor = "Nissim, Malvina and
Patti, Viviana and
Plank, Barbara and
Wagner, Claudia",
booktitle = "Proceedings of the Second Workshop on Computational Modeling of People{'}s Opinions, Personality, and Emotions in Social Media",
month = jun,
year = "2018",
address = "New Orleans, Louisiana, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-1108",
doi = "10.18653/v1/W18-1108",
pages = "56--61",
abstract = "Twitter user accounts include a range of different user types. While many individuals use Twitter, organizations also have Twitter accounts. Identifying opinions and trends from Twitter requires the accurate differentiation of these two groups. Previous work (McCorriston et al., 2015) presented a method for determining if an account was an individual or organization based on account profile and a collection of tweets. We present a method that relies solely on the account profile, allowing for the classification of individuals versus organizations based on a single tweet. Our method obtains accuracies comparable to methods that rely on much more information by leveraging two improvements: a character-based Convolutional Neural Network, and an automatically derived labeled corpus an order of magnitude larger than the previously available dataset. We make both the dataset and the resulting tool available.",
}
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<abstract>Twitter user accounts include a range of different user types. While many individuals use Twitter, organizations also have Twitter accounts. Identifying opinions and trends from Twitter requires the accurate differentiation of these two groups. Previous work (McCorriston et al., 2015) presented a method for determining if an account was an individual or organization based on account profile and a collection of tweets. We present a method that relies solely on the account profile, allowing for the classification of individuals versus organizations based on a single tweet. Our method obtains accuracies comparable to methods that rely on much more information by leveraging two improvements: a character-based Convolutional Neural Network, and an automatically derived labeled corpus an order of magnitude larger than the previously available dataset. We make both the dataset and the resulting tool available.</abstract>
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%0 Conference Proceedings
%T Johns Hopkins or johnny-hopkins: Classifying Individuals versus Organizations on Twitter
%A Wood-Doughty, Zach
%A Mahajan, Praateek
%A Dredze, Mark
%Y Nissim, Malvina
%Y Patti, Viviana
%Y Plank, Barbara
%Y Wagner, Claudia
%S Proceedings of the Second Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana, USA
%F wood-doughty-etal-2018-johns
%X Twitter user accounts include a range of different user types. While many individuals use Twitter, organizations also have Twitter accounts. Identifying opinions and trends from Twitter requires the accurate differentiation of these two groups. Previous work (McCorriston et al., 2015) presented a method for determining if an account was an individual or organization based on account profile and a collection of tweets. We present a method that relies solely on the account profile, allowing for the classification of individuals versus organizations based on a single tweet. Our method obtains accuracies comparable to methods that rely on much more information by leveraging two improvements: a character-based Convolutional Neural Network, and an automatically derived labeled corpus an order of magnitude larger than the previously available dataset. We make both the dataset and the resulting tool available.
%R 10.18653/v1/W18-1108
%U https://aclanthology.org/W18-1108
%U https://doi.org/10.18653/v1/W18-1108
%P 56-61
Markdown (Informal)
[Johns Hopkins or johnny-hopkins: Classifying Individuals versus Organizations on Twitter](https://aclanthology.org/W18-1108) (Wood-Doughty et al., PEOPLES 2018)
ACL