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Multilingual support is based on the first unified cross-lingual dataset of word vectors for representing texts in multiple languages. The classification model based on the proposed cross-lingual word vectors outperforms the \u201cnative\u201d and \u201ctranslated\u201d approaches based on monolingual word vectors. Furthermore, it does not require the creation of a separate training set in a local language or its translation to English.<\/p>","DOI":"10.4018\/ijiscram.2018100103","type":"journal-article","created":{"date-parts":[[2019,8,13]],"date-time":"2019-08-13T16:57:30Z","timestamp":1565715450000},"page":"47-64","source":"Crossref","is-referenced-by-count":1,"title":["Mining Twitter Data for Landslide Events Reported Worldwide"],"prefix":"10.4018","volume":"10","author":[{"given":"Aibek","family":"Musaev","sequence":"first","affiliation":[{"name":"The University of Alabama, Tuscaloosa, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0970-3816","authenticated-orcid":true,"given":"Pezhman","family":"Sheinidashtegol","sequence":"additional","affiliation":[{"name":"The University of Alabama, Tuscaloosa, USA"}]},{"given":"Elizabeth","family":"Conrad","sequence":"additional","affiliation":[{"name":"The University of Alabama, Tuscaloosa, USA"}]},{"given":"Shamkant B.","family":"Navathe","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, USA"}]}],"member":"2432","reference":[{"key":"IJISCRAM.2018100103-0","unstructured":"Wikipedia. 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