Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Attention-enhanced BiLSTM for causal sentiment mining in noisy social-media streams

Saved in:
Bibliographic Details
Published in:JDSA
Format: Online Article RSS Article
Published: 2026
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1864030190648164354
collection WordPress RSS
FRELIP Feed Integration
container_title JDSA
description
discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
RSS Article
genre Journal Article
id rss_article:8065
institution FRELIP
journal_source_facet JDSA
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Attention-enhanced BiLSTM for causal sentiment mining in noisy social-media streams
Big data and Data science
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Big data and Data science
Computer Science & IT
Engineering & Technology
Big data and Data science
Computer Science & IT
Engineering & Technology
subject_facet Big data and Data science
Computer Science & IT
Engineering & Technology
title Attention-enhanced BiLSTM for causal sentiment mining in noisy social-media streams
title_auth Attention-enhanced BiLSTM for causal sentiment mining in noisy social-media streams
title_full Attention-enhanced BiLSTM for causal sentiment mining in noisy social-media streams
title_fullStr Attention-enhanced BiLSTM for causal sentiment mining in noisy social-media streams
title_full_unstemmed Attention-enhanced BiLSTM for causal sentiment mining in noisy social-media streams
title_short Attention-enhanced BiLSTM for causal sentiment mining in noisy social-media streams
title_sort attention-enhanced bilstm for causal sentiment mining in noisy social-media streams
topic Big data and Data science
Computer Science & IT
Engineering & Technology
url https://link.springer.com/article/10.1007/s41060-026-01027-7