@inproceedings{tomlinson-etal-2014-mygoal,
title = "{\#}mygoal: Finding Motivations on {T}witter",
author = "Tomlinson, Marc and
Bracewell, David and
Krug, Wayne and
Hinote, David",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/1120_Paper.pdf",
pages = "469--474",
abstract = "Our everyday language reflects our psychological and cognitive state and effects the states of other individuals. In this contribution we look at the intersection between motivational state and language. We create a set of hashtags, which are annotated for the degree to which they are used by individuals to mark-up language that is indicative of a collection of factors that interact with an individual{'}s motivational state. We look for tags that reflect a goal mention, reward, or a perception of control. Finally, we present results for a language-model based classifier which is able to predict the presence of one of these factors in a tweet with between 69{\%} and 80{\%} accuracy on a balanced testing set. Our approach suggests that hashtags can be used to understand, not just the language of topics, but the deeper psychological and social meaning of a tweet.",
}
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<abstract>Our everyday language reflects our psychological and cognitive state and effects the states of other individuals. In this contribution we look at the intersection between motivational state and language. We create a set of hashtags, which are annotated for the degree to which they are used by individuals to mark-up language that is indicative of a collection of factors that interact with an individual’s motivational state. We look for tags that reflect a goal mention, reward, or a perception of control. Finally, we present results for a language-model based classifier which is able to predict the presence of one of these factors in a tweet with between 69% and 80% accuracy on a balanced testing set. Our approach suggests that hashtags can be used to understand, not just the language of topics, but the deeper psychological and social meaning of a tweet.</abstract>
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%0 Conference Proceedings
%T #mygoal: Finding Motivations on Twitter
%A Tomlinson, Marc
%A Bracewell, David
%A Krug, Wayne
%A Hinote, David
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F tomlinson-etal-2014-mygoal
%X Our everyday language reflects our psychological and cognitive state and effects the states of other individuals. In this contribution we look at the intersection between motivational state and language. We create a set of hashtags, which are annotated for the degree to which they are used by individuals to mark-up language that is indicative of a collection of factors that interact with an individual’s motivational state. We look for tags that reflect a goal mention, reward, or a perception of control. Finally, we present results for a language-model based classifier which is able to predict the presence of one of these factors in a tweet with between 69% and 80% accuracy on a balanced testing set. Our approach suggests that hashtags can be used to understand, not just the language of topics, but the deeper psychological and social meaning of a tweet.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/1120_Paper.pdf
%P 469-474
Markdown (Informal)
[#mygoal: Finding Motivations on Twitter](http://www.lrec-conf.org/proceedings/lrec2014/pdf/1120_Paper.pdf) (Tomlinson et al., LREC 2014)
ACL
- Marc Tomlinson, David Bracewell, Wayne Krug, and David Hinote. 2014. #mygoal: Finding Motivations on Twitter. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 469–474, Reykjavik, Iceland. European Language Resources Association (ELRA).