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PRODID;X-RICAL-TZSOURCE=TZINFO:-//com.denhaven2/NONSGML ri_cal gem//EN
CALSCALE:GREGORIAN
VERSION:2.0
BEGIN:VEVENT
DTEND;VALUE=DATE-TIME:20260515T130000Z
DTSTART;VALUE=DATE-TIME:20260515T123000Z
DTSTAMP;VALUE=DATE-TIME:20260420T130137Z
UID:620a46dc-351d-47a8-95f0-386dbc9306be@talks.stuts.de
DESCRIPTION:Virtual space is one of the domains undergoing rapid developm
 ent and transformation. Given that it is characterized by a fairly free 
 expression of emotions and creativity\, within the Internet discourse ce
 rtain linguistic phenomena are more emphasized than anywhere else. The s
 ubject of this paper\, the paradoxical use of words with negative connot
 ations in a positive context\, is one of them. Therefore\, the goal is t
 o understand the practical value of negative lexis on social media: surv
 ey and software analysis are carried out to verify the assumption that c
 ontextually positive sentences containing negative words are perceived a
 s more intense compared to the ones without such words. Also\, the poten
 tial of software-conducted sentiment analysis\, in this case the SentiSt
 rength program\, to detect this difference in intensity is tested. The r
 esults indicate that negative lexis contributes to the strength of the p
 ositive content of the sentence\, and that the software is unable to det
 ect this phenomenon. The implications of the research refer to the neces
 sity of analysing linguistic phenomena within internet discourse in orde
 r to properly understand this dynamic variety of language\, but also to 
 develop the potential of sentiment analysis software to recognize more c
 omplex linguistic phenomena.
URL:programm.stuts79.de/events/1525.html
SUMMARY:When ‘Bad’ Means Good: Reframing Negative Lexicon in Online Commu
 nities
ORGANIZER:stuts79
LOCATION:stuts79 - DOR 24 1.501
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