2014年10月3日星期五

  One months has passed by, and we have all been more familiar with our courses, our teachers, and certainly our classmates. through the discussion with each other, some basic conceptions have been more explicit. And just see what we’ve learned these days.


Sentiment Analysis and Opinion Mining 
In last lesson, we have learned sentiment analysis and opinion mining, the introduction of this class makes me feel like being a certain of psychological class, we even take a glance at how human beings exact their belief from what they think of things happened surrounded, no matter what angle we use to learn what the world actually is, there always exist two sides of information -----facts and opinions & feelings. And the latter one always have different polarity, how can we tell one from the other? Although it seems all the abstract things, we also developed some math methods to analyze them. That’s all of great use and the fundamental tools even in some famous tech company, so it’s really great fun for us to step into the world of social media.
the pic above showed a general structure of sentiment analysis system in some certain of elearning website overseas.from the pic,we can tell the goals is Enabling subjectivity and sentiment analysis for generating feedback from user generated discourse and for supporting information search in this eLearning website
  • investigate knowledge- and corpus-based methods for subjectivity and sentiment analysis
  • determine the semantic orientation and strength of the opinions
  • identify the targets of the opinions
  • identify the holders of the opinions
A specific score can be given to word
Here we introduce a very interesting pic to show how different score can be given to word in three dimension according to The SentiWordNet.
the vertical dimension showed the score of SO(subjective and objective)popularity, while the horizon axe showed the score of PN(positive and negative)popularity, what may be confused is that there is much more wide range of subjective words when comparing to objective words, and it's all got well explanation during our class. however the dictionary of sentiwordnet cannot cover all the words, and this noticeable problem is yet to be addressed by other methods.




2 条评论:

  1. Analyzing other people's minds makes it easier to have better understandings about them.

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  2. Analysis of Twitter consists of searching the tweets on a topic and analyzing their text. Many tweets do not have enough textual content – they may just contain a URL pointing somewhere and a couple of words. So the engine needs to extract a decent volume of tweets and parse them for sentiment expressions, and for key concepts that are being discussed (semantics).

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