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It is noted that millions of tweets regarding Clinton and Trump were produced per day on Twitter during the 2016 United States presidential election campaign, and thus it is used as a test use case because of its significant and unique counter-factual properties. In addition, stance detection can be utilized to imply the political tendency of the general public. Experimental results show that the proposed framework achieves high accuracy results when compared to several existing stance detection methods.<\/jats:p>","DOI":"10.4018\/ijmdem.2018070101","type":"journal-article","created":{"date-parts":[[2018,12,21]],"date-time":"2018-12-21T09:27:23Z","timestamp":1545384443000},"page":"1-16","source":"Crossref","is-referenced-by-count":6,"title":["Efficient Large-Scale Stance Detection in Tweets"],"prefix":"10.4018","volume":"9","author":[{"given":"Yilin","family":"Yan","sequence":"first","affiliation":[{"name":"University of Miami, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan","family":"Chen","sequence":"additional","affiliation":[{"name":"Miami Palmetto Senior High School, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0902-0844","authenticated-orcid":true,"given":"Mei-Ling","family":"Shyu","sequence":"additional","affiliation":[{"name":"University of Miami, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJMDEM.2018070101-0","first-page":"30","article-title":"Sentiment analysis of twitter data.","author":"A.Agarwal","year":"2011","journal-title":"Proceedings of the Workshop on Languages in Social Media"},{"key":"IJMDEM.2018070101-1","doi-asserted-by":"crossref","unstructured":"Augenstein, I., Rockt\u00e4schel, T., Vlachos, A., & Bontcheva, K. 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