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|Full Title:||2nd Workshop on Practice and Theory of Opinion Mining and Sentiment Analysis|
|Start Date:||23-Sep-2013 - 23-Sep-2013|
|Meeting Email:||click here to access email|
|Meeting Description:||This workshop aims for providing a platform for researchers interested in the upcoming challenges of sentiment analysis and opinion mining. It intends to attract researchers settled in computational linguistics, natural language processing, and artificial intelligence alike. The workshop will be organized by the recently founded GSCL-Interest Group on German Sentiment Analysis (IGGSA): http://www.gscl.org/ak-stimmungsanalyse-en.html.
Scope of the Workshop:
The abundance of opinions available on the World Wide Web represents an information repository of enormous intellectual and economic value. Automated methods to exploit this rich knowledge mine have become more and more relevant within the last decade and the availability of large amounts of data is an ideal premise for the application of empirical methods.
Although many researchers from different nations and institutes intensively work on the development of these techniques, many challenges have been left uncovered: Among the highly relevant social media are new text types that are fairly different from the types on which research in natural language processing has been conducted for the last 20 years. The most prominent example may be Twitter; with its condensed tweets it presents a sublanguage of its own. Traditional approaches often leave questions about the true nature of opinions unanswered. The actual emotion hidden in opinionated text is still hard to uncover; current lexical resources for sentiment analysis mostly only contain information about the polarity or subjectivity of terms, lacking relevant information of their emotional category. Fear or anger are treated equally, as are hope and joy. Emotional categories are projected onto two polarities, i.e. positive and negative, which oversimplifies reality. A further important aspect requiring methodological coverage is the exact analysis of the entities participating in the event evoked by an opinion. Robust linguistic techniques embedded in data-driven methods will possibly guide the way to answer questions on the actual target of an opinion or on the peer group holding this opinion. Another challenge is the automated assignment of polarity or subjectivity labels to the plethora of sentiment-related textual data readily available on the Web. State-of-the-art learning approaches, such as weakly-supervised or semi-supervised methods or distant supervision still need to be thoroughly examined for this purpose.
Another important aspect of this workshop is its focus on multi-linguality. Therefore, discussions on approaches devised and applied on languages other than English, in particular German, are strongly encouraged.
|Linguistic Subfield:||Computational Linguistics|
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