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LINGUISTIC PARAMETERS OF THE CONCEPTS LIST AND CATALOG: LANGUAGE PROCESSING VERSION FOR COMPUTER SYSTEMS
NOSOV ANDREY V.. - : Федеральное государственное бюджетное образовательное учреждение высшего профессионального образования «Пермский государственный национальный исследовательский университет», 2016
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2
Comparing C-tests and Yes/No vocabulary size tests as predictors of receptive language skills
In: Language testing 33 (2016) 4, S. 555-575 (2016)
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3
Frequency and predictability effects on event-related potentials during reading
Dambacher, Michael; Kliegl, R.; Hofmann, M.. - : Elsevier, 2016
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4
Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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6
Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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7
Data from: Impact of lexical and sentiment factors on the popularity of scientific papers ...
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Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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9
Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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10
Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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11
Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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12
Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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13
Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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14
Metaanalysis of psychoanalysis ...
Poleev, Andrej. - : Zenodo, 2016
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15
Conducting sparse feature selection on arbitrarily long phrases in text corpora with a focus on interpretability
Miratrix, Luke Weisman; Ackerman, Robin. - : Wiley-Blackwell, 2016
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16
Assessing Sentiment In Conflict Zones Through Social Media
Abstract: While it is widely accepted that polling can assess levels of popular support in a geographic area by surveying a cross-segment of its population, it is less well accepted that analysts can use social media analysis to assess sentiment or popular support within the same space. We examine this question by comparing geographically anchored polling and social media data, utilizing over 1.4million geo-referenced messages sent through the Twitter network from Yemen over the period from October 2013 to January 2014, to assess both support for extremist groups and support to the Yemeni government. From our research, we conclude that social media data, when combined with polling, has a positive impact on analysis. It can also be a reliable source of stand-alone data for evaluating popular support under certain conditions. Therefore, we recommend future research projects focus on improving the quality of social media data and on operational changes to improve the integration of social media analysis into assessment plans.
Keyword: artificial intelligence; artificial neural networks; computational linguistics; counterterrorism; data acquisition; demography; information exchange; Information Science; military organizations; natural language computing; polling; regression analysis; sentiment; social media; surveys; terrorism; Twitter; unconventional warfare; yemen
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=AD1030712
http://www.dtic.mil/docs/citations/AD1030712
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17
Untangling synchronic and diachronic variation : verb agreement in Palmerston English
Hendery, Rachel (R17913). - : Melbourne, Vic., Routledge, 2016
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18
Short persistent sleep duration is associated with poor receptive vocabulary performance in middle childhood
Seegers, V.; Touchette, E.; Dionne, G.. - : Blackwell Publishing Ltd, 2016
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