Summary of the paper

Title Sentiment Analysis and the Use of Extrinsic Datasets in Evaluation
Authors Ann Devitt and Khurshid Ahmad
Abstract The field of automated sentiment analysis has emerged in recent years as an exciting challenge to the computational linguistics community. Research in the field investigates how emotion, bias, mood or affect is expressed in language and how this can be recognised and represented automatically. To date, the most successful applications have been in the classification of product reviews and editorials. This paper aims to open a discussion about alternative evaluation methodologies for sentiment analysis systems that broadens the scope of this new field to encompass existing work in other domains such as psychology and to exploit existing resources in diverse domains such as finance or medicine. We outline some interesting avenues for research which investigate the impact of affective text content on the human psyche and on external factors such as stock markets.
Topics Emotions, Evaluation methodologies, Document Classification, Text categorisation
Full paper Sentiment Analysis and the Use of Extrinsic Datasets in Evaluation
Slides -
Bibtex @InProceedings{DEVITT08.276,
  author = {Ann Devitt and Khurshid Ahmad},
  title = {Sentiment Analysis and the Use of Extrinsic Datasets in Evaluation},
  booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},
  year = {2008},
  month = {may},
  date = {28-30},
  address = {Marrakech, Morocco},
  editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-4-0},
  note = {},
  language = {english}

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