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| 02037cam 2200349za 4500 |
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| 001 | 9.858177 |
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| 003 | CaOODSP |
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| 005 | 20221107155930 |
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| 007 | cr ||||||||||| |
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| 008 | 180627s2018 onc |otb f|0| 0 eng d |
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| 040 | |aCaOODSP|beng |
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| 043 | |an-cn--- |
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| 086 | 1 |aD68-11/9-2018E-PDF |
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| 100 | 1 |aUpal, M. Afzal, |d1970- |
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| 245 | 10|aDetecting sociostructural beliefs about group status differences in online discussions |h[electronic resource] / |cAfzal Upal, Brian Riordan and Heather Wade. |
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| 260 | |a[Toronto] : |bDefence Research and Development Canada, |c2018. |
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| 300 | |a6 p. |
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| 490 | 1 |aExternal Literature (N) ; |vDRDC-RDDC-2018-N009 |
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| 500 | |aCover title. |
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| 500 | |a"Can unclassified." |
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| 500 | |a"February 2018." |
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| 500 | |a"Date of Publication from Ext Publisher: June 2014." |
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| 504 | |aIncludes bibliographic references. |
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| 520 | 3 |a"Detection of fine-grained opinions and beliefs holds promise for improved social media analysis for social science research, business intelligence, and government decision-makers. While commercial applications focus on mapping landscapes of opinions towards brands and products, our goal is to map “sociostructural” landscapes of perceptions of social groups. In this work, we focus on the detection of views of social group status differences. We report an analysis of methods for detecting views of the legitimacy of income inequality in the U.S. from online discussions, and demonstrate detection rates competitive with results from similar tasks such as debate stance classification"--Abstract. |
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| 692 | 07|2gccst|aSocial media |
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| 692 | 07|2gccst|aPublic opinion |
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| 692 | 07|2gccst|aComputer science |
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| 700 | 1 |aRiordan, Brian. |
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| 700 | 1 |aWade, Heather. |
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| 710 | 2 |aDefence R&D Canada. |bToronto Research Centre. |
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| 830 | #0|aExternal literature (N) (Defence R&D Canada)|vDRDC-RDDC-2018-N009.|w(CaOODSP)9.858173 |
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| 856 | 40|qPDF|s465 KB|uhttps://publications.gc.ca/collections/collection_2018/rddc-drdc/D68-11-9-2018-eng.pdf |
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