By James G. Shanahan, Yan Qu, Janyce Wiebe
The chapters during this publication tackle perspective, have an effect on, and subjective opinion. numerous conceptual types and computational tools are offered, together with distinguishing attitudes from uncomplicated genuine assertions; distinguishing among the author’s stories from studies of alternative people’s reviews; and distinguishing among explicitly and implicitly said attitudes. moreover, many functions are defined that promise to profit from the power to appreciate attitudes and have an effect on, corresponding to indexing and retrieval of files by means of opinion; automated query answering approximately reviews; research of sentiment within the media and in chat groups; interpreting purchaser discourse in treatment and counseling; making a choice on kin among clinical texts; producing extra acceptable texts; and growing writers’ aids. as well as English texts, the gathering comprises reports of French, eastern, and Portuguese texts. The chapters are prolonged and revised models of papers awarded on the American organization for man made Intelligence (AAAI) Spring Symposium on Exploring perspective and have an effect on in textual content, which happened in March 2004 at Stanford college. The symposium, and the ebook which grew out it, signify a primary foray into this zone and a stability between conceptual types, computational equipment, and functions.
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Additional info for Computing Attitude and Affect in Text: Theory and Applications (The Information Retrieval Series)
These levels of embedding have to be chosen for each agent, since some agent may not consider different newspapers differently and can thus drop one level of embedding. For agent A, Ø has been asserted under (P’,R’,C’), where P’ is agent A’s assessment of paper P’s credibility, R’ is the agent’s assessment of the reporter’s credibility, and C’ is the agent’s assessment of the source S’s credibility combined with the pragmatic force of the reported speech verb and other circumstantial information.
In the most stringent criterion the overlap is slightly lower – only five out of the top ten are shared. The top ten adjective lists give the same impression as the lists in Figure 2: the more restrictive contexts seem to be loci for attitudinal expression, and the expressions found give purchase to our claim that adjectives gain their attitudinal loading from being used in certain expressions. This would also seem to point at the potential for mining attitudinally loaded items from expressions, if some statistical finesse is observed.
Birnbaum, h, n, n, n)] [Republicans can garner a majority in the 100-member Senate for a capital-gains tax cut. Source-list(Republicans, Reporter Jeffrey H. Birnbaum, n, n, n, n)] [the Democrats are unfairly using Senate rules to erect a 60-vote hurdle. Source-list(Republicans, Reporter Jeffrey H. Birnbaum, n, h, n, n)] [the proposal, which also would create a new type of individual retirement account, was fraught with budget gimmickry that would lose billions of dollars in the long run. Source-list(Democrats, Reporter Jeffrey H.