22 May 2012

2 questions about Language technology challenges

I have two questions about sentiment analysis: 

First, how to assign the correct sentiment to a comment when "dictionaries used for automatic analysis of sentiments should be able to take account of: polarity of feeling and the degree of positivity, detection of subjectivity and identification of an opinion, the point of view,  the non-factual informations (related to the six universal emotions: anger, disgust, fear, joy, sadness and surprise), syntax and negation"?

Second, how to sort and value the comments that "deserve more interest than others, and [that] can be crucial in the establishment of a new strategy"?

For now, the answer to both questions is: human analysis. Although they have their own interpretation, they apprehend posts subjectively and are slower, human analysts remain today the most efficient in awarding the correct tone to a comment. Tomorrow, technologies as used by Watson, the IBM supercomputer, will able to achieve a degree of precision so that they will become ready to take over  the human analysis.

Source : Master Thesis "Mobility sector in Belgium : social media monitoring to built an efficient marketing strategy" 2011, ULB.

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