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#mygoal: Finding Motivations on Twitter

Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014)

DOI:10.63317/4rqefh8bomdy

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.

Details

Paper ID
lrec2014-main-088
Pages
pp. 469-474
BibKey
tomlinson-etal-2014-mygoal
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
978-2-9517408-8-4
Conference
Ninth International Conference on Language Resources and Evaluation
Location
Reykjavik, Iceland
Date
26 May 2014 31 May 2014

Authors

  • MT

    Marc Tomlinson

  • DB

    David Bracewell

  • WK

    Wayne Krug

  • DH

    David Hinote

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