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TrendTracker: Temporal, network-based exploration of long-t..:
, In:
Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
,
Ziegler, John
;
Sindlinger, Johannes
;
Walther, Marina
. - p. 441-444 , 2023
Link:
https://dl.acm.org/doi/10.1145/3625007.3627335
RT T1 <cTitle>Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining</cTitle>: T1 <Title>TrendTracker: Temporal, network-based exploration of long-term Twitter trends</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3627335&Exemplar=1&LAN=DE A1 Ziegler, John A1 Sindlinger, Johannes A1 Walther, Marina A1 Gertz, Michael PB ACM YR 2023 K1 social media analytics K1 trend analysis K1 trend visualization K1 twitter data K1 Information systems K1 Human-centered computing K1 Information systems applications K1 World Wide Web K1 Information retrieval K1 Human computer interaction (HCI) K1 Interaction paradigms SP 441 OP 444 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3625007.3627335 DO https://dl.acm.org/doi/10.1145/3625007.3627335 SF ELIB - SuUB Bremen
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