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The primary entities of such language are the out-of-vocabulary (OOV) words. ... In this paper, we study various sociolinguistic properties of the OOV words and propose a classification model to categorize them into at least six categories. ... It is really difficult to disambiguate the words like LOL, ROFL, WASSUP etc. by just writing a regular expression. ...arXiv:1602.00293v1 fatcat:pqetz3mhufbf3mymfun4uafe3i
The article is devoted to the consideration of the problem of intercultural communication in the Internet space. ... Communication with foreign citizens allows you to learn about the culture of different peoples, adopt foreign words and expressions and introduce them into your own language and culture. ... Lexeme "lol" -from the English abbreviation of the expression laughing out loud with the meaning of 'violent laughter'. ...doi:10.5281/zenodo.6601801 fatcat:vc7jbgsdyfacnoa4t6ugnbrmue
To address the possibility of bias in this sensitive application, we developed an approach to systematically interpret the state of the art model. ... aggression and loss in posts. ... We ask them to annotate the "minimum set of words" that is important for their final decision, thus excluding words that are not very meaningful, such as "on", "basically", "lol", etc. ...arXiv:1908.11474v2 fatcat:5sonf5zgvrf6hhgoimpmz5feti
How can automatic text analysis algorithms efficiently and reliably analyze the social processes revealed in language production? ... This is illustrated through three case studies: first, examining whether sentiment expressed in social media can track opinion polls on economic and political topics (Chapter 3); second, analyzing how ... For each user's Twitter feed, we combine all messages into a single "document." We remove word types that appear in fewer than 40 feeds, yielding a vocabulary of 5,216 words. ...doi:10.1184/r1/6723179 fatcat:eybyauanyve45lxvaf2nr6p7du