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We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity and strength), and incorporates intensification and negation. SO-CAL is applied to the polarity classification task, the process of assigning a positive or negative(More)
We describe and compare different methods for creating a dictionary of words with their corresponding semantic orientation (SO). We tested how well different dictionaries helped determine the SO of entire texts. To extract SO for each individual word, we used a common method based on pointwise mutual information. Mutual information between a set of seed(More)
We present an approach to extracting sentiment from texts that makes use of con-textual information. Using two di¤erent approaches, we extract the most relevant sentences of a text, and calculate semantic orientation weighing those more heavily. The …rst approach makes use of discourse structure via Rhetorical Structure Theory, and extracts nuclei as the(More)
Semantic orientation (SO) for texts is often determined on the basis of the positive or negative polarity, or sentiment, found in the text. Polarity is typically extracted using the positive and negative words in the text, with a particular focus on adjectives, since they convey a high degree of opinion. Not all adjectives are created equal, however.(More)
We describe extensive modifications made over time to a first year computer science course at the University of British Columbia covering logic and digital circuits (among other topics). Smoothly integrating the hardware-based labs with the more theory-based lectures into a cohesive picture of computation has always been a challenge in this course. The(More)
Despite the potential to dominate radiology reporting, current speech recognition technology is thus far a weak and inconsistent alternative to traditional human transcription. This is attributable to poor accuracy rates, in spite of vendor claims, and the wasted resources that go into correcting erroneous reports. A solution to this problem is(More)