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ADAPTATION OF DOMAIN-SPECIFIC TRANSFORMER MODELS WITH TEXT OVERSAMPLING FOR SENTIMENT ANALYSIS OF SOCIAL MEDIA POSTS ON COVID-19 VACCINE.

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Title: ADAPTATION OF DOMAIN-SPECIFIC TRANSFORMER MODELS WITH TEXT OVERSAMPLING FOR SENTIMENT ANALYSIS OF SOCIAL MEDIA POSTS ON COVID-19 VACCINE.
Authors: BANSAL, ANMOL1, anmolbansal_2k18it025@dtu.ac.in, CHOUDHRY, ARJUN1, arjunchoudhry_2k18it031@dtu.ac.in, SHARMA, ANUBHAV1, anubhavsharma_2k18it029@dtu.ac.in, SUSAN, SEBA1, seba_406@yahoo.in
Source: Computer Science; 2023, Vol. 24 Issue 2, p167-186, 20p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: <searchLink fieldCode="JN" term="%22Computer+Science%22">Computer Science</searchLink>; 2023, Vol. 24 Issue 2, p167-186, 20p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=163064596
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        Value: 10.7494/csci.2023.24.2.4761
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      – Code: eng
        Text: English
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        PageCount: 20
        StartPage: 167
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      – TitleFull: ADAPTATION OF DOMAIN-SPECIFIC TRANSFORMER MODELS WITH TEXT OVERSAMPLING FOR SENTIMENT ANALYSIS OF SOCIAL MEDIA POSTS ON COVID-19 VACCINE.
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              Text: 2023
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              Y: 2023
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              Value: 24
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