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Promoting English movie as a means of enhancing EFL learners’ cultural competence
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In: Journal of Applied Linguistics and Literature, Vol 7, Iss 1, Pp 186-201 (2022) (2022)
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British English in American Movies: the Smart, the Bad and the Exotic
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The American Movie Corpus
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Forchini, Pierfranca (orcid:0000-0003-1900-9825). - : Educatt Università Cattolica del Sacro Cuore, 2021. : country:ITA, 2021. : place:Milano, 2021
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British English and Characterization in American Movies
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Seracini, Francesca (orcid:0000-0003-3769-773X). - : EDUCatt, 2021. : country:ITA, 2021. : place:Milano, 2021
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The language of leadership in American movies: a corpus-driven analysis with the AntConc concordancer
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Seracini, Francesca (orcid:0000-0003-3769-773X). - : EDUCatt, 2021. : country:ITA, 2021. : place:Milano, 2021
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The American Movie Corpus: A Tool for the Development of Spoken Lexico-Grammatical Competence
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Learning the Genre “Summary” by Undergraduate French Language Students: A Didactic Device at the Service of Academic Literacy
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In: Signum: Estudos da Linguagem, Vol 24, Iss 1, Pp 117-135 (2021) (2021)
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Subjective Evaluation of Comprehensibility in Movie Interactions
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In: Proceedings of the 12th Language Resources and Evaluation Conference ; 12th Conference on Language Resources and Evaluation (LREC 2020) ; https://hal.archives-ouvertes.fr/hal-03536555 ; 12th Conference on Language Resources and Evaluation (LREC 2020), European Language Resources Association (ELRA), May 2020, Marseille, France. pp.2348-2357 ; https://aclanthology.org/2020.lrec-1.286/ (2020)
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Analysis of Deixis in the Subtitle Movie of “First Kiss”
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In: LET: Linguistics, Literature and English Teaching Journal, Vol 10, Iss 1, Pp 111-132 (2020) (2020)
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The Jews in Hollywood: Altering Image through Religious Movies
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In: Celt: A Journal of Culture, English Language Teaching & Literature, Vol 19, Iss 2, Pp 202-221 (2020) (2020)
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STRATEGIES AND TECHNIQUES IN THE TRANSLATION OF MOVIE TITLES (AN ENGLISH-RUSSIAN COMPARATIVE CASE STUDY)
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In: Studies in Linguistics, Culture, and FLT, Vol 7, Pp 59-70 (2019) (2019)
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Ethical Dilemmas as Seen Through the Major Characters Reflected in "The Danish Girl" Movie Screenplay Written by Lucinda Coxon
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In: Rainbow: Journal of Literature, Linguistics and Culture, Vol 8, Iss 2, Pp 75-84 (2019) (2019)
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Supplementary Materials For "Creating A Frequency Dictionary Of Spoken Hebrew" ...
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Supplementary Materials For "Creating A Frequency Dictionary Of Spoken Hebrew" ...
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The Study of Translation Strategies of Oscar Movie Titles
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Zhu, Mengtang. - : The University of Queensland, School of Languages and Cultures, 2018
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SHORT MOVIE PRODUCTION TO ENCOURAGE ASIAN DIGITAL NATIVES TO SPEAK ENGLISH
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In: LET: Linguistics, Literature and English Teaching Journal, Vol 8, Iss 1, Pp 78-90 (2018) (2018)
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A Study of English to Chinese Translated Movie Titles Perceptions in China
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Guo, Shangyang. - : The University of Queensland, School of Languages and Cultures, 2015
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Analyse et création de films d'animation en Français Langue Etrangère (FLE).
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In: ISSN: 0023-8376 ; Les Langues Modernes ; https://hal.archives-ouvertes.fr/hal-00877206 ; Les Langues Modernes, Association des professeurs de langues vivantes (APLV), 2013, 2, pp.69-80 (2013)
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The teaching applicability of movies and the strength of Multi-Dimensional Analysis (MDA)
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Forchini, Pierfranca (orcid:0000-0003-1900-9825). - : EDUCatt, 2013. : country:ITA, 2013. : place:Milano, 2013
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Adding a Capability to Extract Sentiment from Text Using HanDles
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In: DTIC (2012)
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Abstract:
HanDles is a document visualization tool developed by Ohio State University for DRDC Toronto. One aspect of documents that might be of interest to analysts is the extent to which they express positive or negative opinion or sentiment toward some issue or group. In this report, we describe how HanDles was extended to include the ability to classify documents as containing predominantly positive or negative sentiment. The capability was added to the tool so that it could be used in Influence Operations contexts. As a test case, we trained HanDles to distinguish good and poor film reviews, and then tested it three times to see how well it classified documents. The first test was conducted on reviews of the Amazon Kindle. The second test was run on text segments of the original training set of movie reviews, and finally, it was tested on a set of movie reviews that it had not seen before. In general, HanDles did a poor job detecting the sentiment associated with the reviews of the Amazon Kindle. We attribute the poor performance to the fact that movie and product reviews discuss different issues, and as such, there is limited similarity in the two classes of document. Not surprisingly, HanDles did a good job classifying text segments of the original training set. Also, the finding demonstrated that, unlike many other sentiment analysis tools that only classify text at the whole-document level, HanDles can be used effectively to extract the issues being discussed within documents, and assign sentiment to those. For example, a review of a film might be classified as negative overall, but HanDles can determine that the acting was good, but the directing was poor. Finally, when we tested HanDles on a new set of movie reviews it had not seen before, it performed with 93.3% accuracy. The results of our trial suggest that there must be some similarity between the documents used during training and those used in the operational context for HanDles to work properly. ; Text in English; abstract and executive summary in English and French. Contract No. W7711-088147/001/TOR.
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Keyword:
*ATTITUDES(PSYCHOLOGY); *CLASSIFICATION; *DATA MINING; *DOCUMENT VISUALIZATION; *DOCUMENTS; *EXTRACTION; *HANDLES VISUALIZATION TOOL; *INFORMATION RETRIEVAL; *OPINION MINING; *SEMANTICS; *SENTIMENT ANALYSIS; AMAZON KINDLE REVIEW CLASSIFICATION; ARTIFICIAL INTELLIGENCE; AUGMENTATION; AUTOMATION; CANADA; Cybernetics; FILM REVIEW CLASSIFICATION; FOREIGN REPORTS; INFLUENCE OPERATIONS; INFORMATION PROCESSING; Information Science; INTERNET MOVIE DATABASE; LANGUAGE PROCESSING; LEARNING MACHINES; Linguistics; MOTION PICTURES; NEGATIVE SENTIMENT; POSITIVE SENTIMENT; Psychology; SENTIMENT EXTRACTION; SUPPORT VECTOR MACHINES; TOOL AUGMENTATION; TRAINING
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA568477 http://www.dtic.mil/docs/citations/ADA568477
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