@inproceedings{ahmad-etal-2006-sentiments,
    title = "Sentiments on a Grid: Analysis of Streaming News and Views",
    author = "Ahmad, Khurshid  and
      Gillam, Lee  and
      Cheng, David",
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Gangemi, Aldo  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Odijk, Jan  and
      Tapias, Daniel",
    booktitle = "Proceedings of the Fifth International Conference on Language Resources and Evaluation ({LREC}{'}06)",
    month = may,
    year = "2006",
    address = "Genoa, Italy",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://preview.aclanthology.org/fix-sig-urls/L06-1231/",
    abstract = "In this paper we report on constructing a finite state automaton comprising automatically extracted terminology and significant collocation patterns from a training corpus of specialist news (Reuters Financial News). The automaton can be used to unambiguously identify sentiment-bearing words that might be able to make or break people, companies, perhaps even governments. The paper presents the emerging face of corpus linguistics where a corpus is used to bootstrap both the terminology and the significant meaning bearing patterns from the corpus. Much of the current content analysis software systems require a human coder to eyeball terms and sentiment words. Such an approach might yield very good quality results on small text collections but when confronted with a 40-50 million word corpus such an approach does not scale, and a large-scale computer-based approach is required. We report on the use of Grid computing technologies and techniques to cope with this analysis."
}