Summary of the paper
| Title | #mygoal: Finding Motivations on Twitter |
|---|---|
| Authors | Marc Tomlinson, David Bracewell, Wayne Krug and David Hinote |
| 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. |
| Topics | Cognitive Methods, Language Modelling |
Full paper  |
#mygoal: Finding Motivations on Twitter |
| Bibtex | @InProceedings{TOMLINSON14.1120, author = {Marc Tomlinson and David Bracewell and Wayne Krug and David Hinote}, title = {#mygoal: Finding Motivations on Twitter}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |