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1
SentiStance : quantifying the intertwined changes of sen..:
, In:
Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
,
Tachaiya, Jakapun
;
Irani, Arman
;
Esterling, Kevin M.
. - p. 361-368 , 2021
Link:
https://dl.acm.org/doi/10.1145/3487351.3490966
RT T1 <cTitle>Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining</cTitle>: T1 <Title>SentiStance : quantifying the intertwined changes of sentiment and stance in response to an event in online forums</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3490966&Exemplar=1&LAN=DE A1 Tachaiya, Jakapun A1 Irani, Arman A1 Esterling, Kevin M. A1 Faloutsos, Michalis PB ACM YR 2021 K1 aspect-based sentiment analysis K1 elections K1 online communities mining K1 stance detection K1 Human-centered computing K1 Human computer interaction (HCI) K1 Interaction paradigms K1 Web-based interaction SP 361 OP 368 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3487351.3490966 DO https://dl.acm.org/doi/10.1145/3487351.3490966 SF ELIB - SuUB Bremen
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